From 6757c5cf682b48dca19c37a98e4ce56f4268d709 Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Wed, 7 May 2025 00:59:00 +0200 Subject: [PATCH 1/7] feat: added NDCG@all metric --- src/ml_filter/__init__.py | 0 src/ml_filter/analysis/interrater_reliability.py | 12 +++++++++--- 2 files changed, 9 insertions(+), 3 deletions(-) create mode 100644 src/ml_filter/__init__.py diff --git a/src/ml_filter/__init__.py b/src/ml_filter/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/ml_filter/analysis/interrater_reliability.py b/src/ml_filter/analysis/interrater_reliability.py index 02efdb83..9943f9d4 100644 --- a/src/ml_filter/analysis/interrater_reliability.py +++ b/src/ml_filter/analysis/interrater_reliability.py @@ -10,7 +10,7 @@ import numpy as np import pandas as pd from scipy.stats import kendalltau, spearmanr -from sklearn.metrics import cohen_kappa_score, f1_score +from sklearn.metrics import cohen_kappa_score, f1_score, ndcg_score from statsmodels.stats.inter_rater import fleiss_kappa from ml_filter.analysis.plot_score_distributions import plot_confusion_matrix @@ -191,6 +191,9 @@ def compute_gt_metrics( for valid_label, f1 in zip(valid_labels, class_f1_scores): gt_metrics[f"F1-{valid_label}"] = f1 + # NDCG@all + gt_metrics["NDCG@all"] = ndcg_score(y_true=[ground_truth_scores], y_score=[predicted_scores], k=None) + return gt_metrics @@ -215,7 +218,7 @@ def plot_invalid_docs_histogram( plt.hist(correct_scores_of_invalid_docs, bins=[0, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5], alpha=0.5, edgecolor="black") plt.xlabel("Scores") plt.ylabel("Frequency") - plt.title(f"Histogram of Invalid Scores for {annotator_name} and langauge {language}.") + plt.title(f"Histogram of invalid scores for {annotator_name} and language {language}.") plt.grid(True) plt.savefig(output_file_path) @@ -368,12 +371,15 @@ def compare_annotator_to_gt( gt_idx = 0 ground_truth_scores = valid_docs_df["score_0"].to_list() predicted_scores = valid_docs_df["score_1"].to_list() - else: + elif annotators[1] == "gt": annotator_idx = 0 gt_idx = 1 ground_truth_scores = valid_docs_df["score_1"].to_list() predicted_scores = valid_docs_df["score_0"].to_list() + else: + raise ValueError(f"Expected one of the annotators to be 'gt', but found {annotators[0]} and {annotators[1]}") + annotator_name = annotators[annotator_idx] gt_metrics = compute_gt_metrics( From 4db5eb8b3db3545a7a160feae91105b18026a8f6 Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Wed, 7 May 2025 00:59:50 +0200 Subject: [PATCH 2/7] feat: added some consistency checks for input data --- src/ml_filter/analysis/utils.py | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/src/ml_filter/analysis/utils.py b/src/ml_filter/analysis/utils.py index 8ef29199..06504586 100644 --- a/src/ml_filter/analysis/utils.py +++ b/src/ml_filter/analysis/utils.py @@ -6,6 +6,8 @@ import pandas as pd +from ml_filter.utils.logging import get_logger + def custom_round(x: int | float) -> int: """Rounds values > x.5 to x+1 and values < x.5 to x. @@ -83,6 +85,10 @@ def get_document_scores_df( with open(file_path, "r") as f: for line in f: json_obj = json.loads(line) + if "document_id" not in json_obj or json_obj["document_id"] is None: + raise ValueError( + f"Document ID is missing in the JSON object: {json_obj}. Please check the input file." + ) # replace invalid scores with None scores = [] @@ -124,6 +130,19 @@ def get_document_scores_df( ) document_scores_df = pd.DataFrame(document_scores) + + # make sure that we have the same number of documents with the same doc_id for each annotator + doc_ids_per_annotator = document_scores_df.groupby(by=["annotator", "prompt", "prompt_lang"])["doc_id"].apply(set) + first_doc_ids = next(iter(doc_ids_per_annotator)) + for index, doc_ids in zip(doc_ids_per_annotator.index, doc_ids_per_annotator): + if not doc_ids == first_doc_ids: + if len(doc_ids - first_doc_ids) > 0: + get_logger(name="main").warning( + f"{'__'.join(doc_ids_per_annotator.index[0])} misses: {doc_ids - first_doc_ids}" + ) + if len(first_doc_ids - doc_ids) > 0: + get_logger(name="main").warning(f"{'__'.join(index)} misses: {first_doc_ids - doc_ids}") + return document_scores_df @@ -173,6 +192,9 @@ def get_common_docs(document_scores_df: pd.DataFrame, annotator_0: str, annotato # only consider documents that are annotated by both annotators and have valid scores common_docs_df = pd.merge(annotator_0_df, annotator_1_df, on=["doc_id", "prompt"], suffixes=("_0", "_1")) + if len(common_docs_df) * 2 != len(document_scores_df): + get_logger(name="main").warning("Not all documents can be matched on columns doc_id and prompt.") + # add rounded scores for each annotator for idx in (0, 1): common_docs_df[f"rounded_score_{idx}"] = common_docs_df[f"score_{idx}"].apply(round_scores) From 3f2e74f35f9968e0e06cebc30c0a150d109c0de9 Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Wed, 7 May 2025 01:00:08 +0200 Subject: [PATCH 3/7] feat: added llm-as-a-judge evaluation --- notebooks/edu_content_human_as_a_judge.ipynb | 12094 ++++++++++++++++- 1 file changed, 12089 insertions(+), 5 deletions(-) diff --git a/notebooks/edu_content_human_as_a_judge.ipynb b/notebooks/edu_content_human_as_a_judge.ipynb index 15ec7af0..cb6b11a5 100644 --- a/notebooks/edu_content_human_as_a_judge.ipynb +++ b/notebooks/edu_content_human_as_a_judge.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 78, + "execution_count": 39, "id": "e32546d4", "metadata": {}, "outputs": [], @@ -11,7 +11,38 @@ "import numpy as np\n", "import json \n", "from pathlib import Path\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import seaborn as sns\n" + ] + }, + { + "cell_type": "markdown", + "id": "01335ae6", + "metadata": {}, + "source": [ + "# Globals" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "efba794a", + "metadata": {}, + "outputs": [], + "source": [ + "language_codes = {\n", + " \"en\": \"English\",\n", + " \"es\": \"Spanish\",\n", + " \"fr\": \"French\",\n", + " \"it\": \"Italian\",\n", + " \"pl\": \"Polish\",\n", + " \"el\": \"Greek\",\n", + " \"no\": \"Norwegian\",\n", + " \"hu\": \"Hungarian\",\n", + " \"fi\": \"Finnish\",\n", + " \"lt\": \"Lithuanian\",\n", + "}" ] }, { @@ -24,13 +55,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "e976311c", "metadata": {}, "outputs": [], "source": [ "gt_annotations_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_raw_scores/annotations__educational_content__en__gt.jsonl\")\n", - "en_documents_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_en.jsonl\")" + "en_documents_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_en.jsonl\")\n", + "llm_as_a_judge_metrics_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/output/llm_as_a_judge_metrics\")" ] }, { @@ -586,10 +618,12062 @@ "plt.show()\n" ] }, + { + "cell_type": "markdown", + "id": "197531d3", + "metadata": {}, + "source": [ + "# LLM-as-a-judge evaluation" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "c944d423", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'bg': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.16588711569468226,\n", + " 'Cohen': 0.19228036253776437,\n", + " 'Spearman': 0.5866735918259259,\n", + " 'Kendall': 0.4939727977473699,\n", + " 'Krippendorff': 0.5239927892374399,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.726027397260274,\n", + " 'TA-4.0': 0.9354207436399217,\n", + " 'Acc': 0.36007827788649704,\n", + " 'MAE': 0.8604044357469016,\n", + " 'MSE': 1.3792128723635573,\n", + " 'CA-0': 0.25806451612903225,\n", + " 'CA-1': 0.45,\n", + " 'CA-2': 0.33962264150943394,\n", + " 'CA-3': 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0.12763890893645932,\n", + " 'Micro-F1': 0.13333333333333333,\n", + " 'F1-0': 0.0,\n", + " 'F1-1': 0.08121827411167512,\n", + " 'F1-2': 0.12807881773399016,\n", + " 'F1-3': 0.27177700348432055,\n", + " 'F1-4': 0.10294117647058823,\n", + " 'F1-5': 0.18181818181818182,\n", + " 'NDCG@all': 0.8964794133440245},\n", + " 'CM': {'0': {'-1': 0, '0': 0, '1': 88, '2': 62, '3': 31, '4': 4, '5': 1},\n", + " '1': {'-1': 1, '0': 0, '1': 8, '2': 22, '3': 50, '4': 17, '5': 2},\n", + " '2': {'-1': 0, '0': 0, '1': 1, '2': 13, '3': 57, '4': 32, '5': 3},\n", + " '3': {'-1': 0, '0': 0, '1': 1, '2': 0, '3': 39, '4': 62, '5': 2},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 6, '4': 7, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.2030603423577392,\n", + " 'Cohen': 0.22911234389986457,\n", + " 'Spearman': 0.6802434122230671,\n", + " 'Kendall': 0.5809625091677925,\n", + " 'Krippendorff': 0.5942336007000478,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7573385518590998,\n", + " 'TA-4.0': 0.9158512720156555,\n", + " 'Acc': 0.38747553816046965,\n", + " 'MAE': 0.7886497064579254,\n", + " 'MSE': 1.1913459447706019,\n", + " 'CA-0': 0.25806451612903225,\n", + " 'CA-1': 0.41,\n", + " 'CA-2': 0.5377358490566038,\n", + " 'CA-3': 0.4807692307692308,\n", + " 'CA-4': 0.15384615384615385,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2863413518106297,\n", + " 'Micro-F1': 0.38747553816046965,\n", + " 'F1-0': 0.41025641025641024,\n", + " 'F1-1': 0.30711610486891383,\n", + " 'F1-2': 0.4253731343283582,\n", + " 'F1-3': 0.49019607843137253,\n", + " 'F1-4': 0.0851063829787234,\n", + " 'F1-5': 0.0,\n", + " 'NDCG@all': 0.8963016134450722},\n", + " 'CM': {'0': {'-1': 0, '0': 48, '1': 106, '2': 26, '3': 1, '4': 5, '5': 0},\n", + " '1': {'-1': 0, '0': 0, '1': 41, '2': 39, '3': 15, '4': 5, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 16, '2': 57, '3': 27, '4': 6, '5': 0},\n", + " '3': {'-1': 0, '0': 0, '1': 4, '2': 35, '3': 50, '4': 15, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 6, '4': 2, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", + " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.015194313931290941,\n", + " 'Cohen': 0.044031415001724694,\n", + " 'Spearman': 0.5190235352094755,\n", + " 'Kendall': 0.4223291996288165,\n", + " 'Krippendorff': 0.2244617734534572,\n", + " 'Invalid': 212,\n", + " 'TA-2.0': 0.5919732441471572,\n", + " 'TA-4.0': 0.7157190635451505,\n", + " 'Acc': 0.1939799331103679,\n", + " 'MAE': 1.4007803790412485,\n", + " 'MSE': 3.0723708658491273,\n", + " 'CA-0': 0.17094017094017094,\n", + " 'CA-1': 0.11666666666666667,\n", + " 'CA-2': 0.2857142857142857,\n", + " 'CA-3': 0.20754716981132076,\n", + " 'CA-4': 0.4,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.15272123502026536,\n", + " 'Micro-F1': 0.1939799331103679,\n", + " 'F1-0': 0.28776978417266186,\n", + " 'F1-1': 0.14285714285714285,\n", + " 'F1-2': 0.2222222222222222,\n", + " 'F1-3': 0.22,\n", + " 'F1-4': 0.043478260869565216,\n", + " 'F1-5': 0.0,\n", + " 'NDCG@all': 0.8499529631689791},\n", + " 'CM': {'0': {'-1': 69, '0': 20, '1': 29, '2': 46, '3': 9, '4': 12, '5': 1},\n", + " '1': {'-1': 40, '0': 0, '1': 7, '2': 23, '3': 9, '4': 19, '5': 2},\n", + " '2': {'-1': 43, '0': 2, '1': 2, '2': 18, '3': 17, '4': 24, '5': 0},\n", + " '3': {'-1': 51, '0': 0, '1': 0, '2': 10, '3': 11, '4': 29, '5': 3},\n", + " '4': {'-1': 8, '0': 0, '1': 0, '2': 2, '3': 1, '4': 2, '5': 0},\n", + " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.14013325530803808,\n", + " 'Cohen': 0.16073642259264187,\n", + " 'Spearman': 0.6592540559697546,\n", + " 'Kendall': 0.5434094381749343,\n", + " 'Krippendorff': 0.5721133943736478,\n", + " 'Invalid': 19,\n", + " 'TA-2.0': 0.7357723577235772,\n", + " 'TA-4.0': 0.8516260162601627,\n", + " 'Acc': 0.3231707317073171,\n", + " 'MAE': 0.9115853658536582,\n", + " 'MSE': 1.519817073170732,\n", + " 'CA-0': 0.33519553072625696,\n", + " 'CA-1': 0.23404255319148937,\n", + " 'CA-2': 0.38235294117647056,\n", + " 'CA-3': 0.30392156862745096,\n", + " 'CA-4': 0.5384615384615384,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.24914790780184184,\n", + " 'Micro-F1': 0.3231707317073171,\n", + " 'F1-0': 0.4819277108433735,\n", + " 'F1-1': 0.22,\n", + " 'F1-2': 0.32231404958677684,\n", + " 'F1-3': 0.3263157894736842,\n", + " 'F1-4': 0.14432989690721648,\n", + " 'F1-5': 0.0,\n", + " 'NDCG@all': 0.8989956000238616},\n", + " 'CM': {'0': {'-1': 7, '0': 60, '1': 67, '2': 38, '3': 9, '4': 4, '5': 1},\n", + " '1': {'-1': 6, '0': 8, '1': 22, '2': 43, '3': 11, '4': 9, '5': 1},\n", + " '2': {'-1': 4, '0': 2, '1': 11, '2': 39, '3': 31, '4': 19, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 6, '2': 20, '3': 31, '4': 43, '5': 2},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 6, '4': 7, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04149722289302098,\n", + " 'Cohen': 0.009967265498386335,\n", + " 'Spearman': 0.6197428534095925,\n", + " 'Kendall': 0.5264194487824005,\n", + " 'Krippendorff': 0.3479816108585173,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.6066536203522505,\n", + " 'TA-4.0': 0.7886497064579256,\n", + " 'Acc': 0.17416829745596868,\n", + " 'MAE': 1.2354859752120027,\n", + " 'MSE': 2.2722330941509026,\n", + " 'CA-0': 0.06451612903225806,\n", + " 'CA-1': 0.13,\n", + " 'CA-2': 0.2169811320754717,\n", + " 'CA-3': 0.2980769230769231,\n", + " 'CA-4': 0.7692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.14251999089643083,\n", + " 'Micro-F1': 0.17416829745596868,\n", + " 'F1-0': 0.12121212121212122,\n", + " 'F1-1': 0.12149532710280374,\n", + " 'F1-2': 0.18181818181818182,\n", + " 'F1-3': 0.27555555555555555,\n", + " 'F1-4': 0.15503875968992248,\n", + " 'F1-5': 0.0,\n", + " 'NDCG@all': 0.8871628544616091},\n", + " 'CM': {'0': {'-1': 0, '0': 12, '1': 86, '2': 62, '3': 20, '4': 5, '5': 1},\n", + " '1': {'-1': 0, '0': 0, '1': 13, '2': 47, '3': 26, '4': 14, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 11, '2': 23, '3': 41, '4': 31, '5': 0},\n", + " '3': {'-1': 0, '0': 0, '1': 4, '2': 15, '3': 31, '4': 54, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}}}" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results_complete = {}\n", + "for path in list(llm_as_a_judge_metrics_path.glob(\"**/*.json\")):\n", + " language = path.parts[-2]\n", + " model = path.stem.split(\"_\")[2]\n", + " if language not in results_complete:\n", + " results_complete[language] = {}\n", + " with open(path, 'r') as f:\n", + " data = json.load(f)\n", + " results_complete[language][model] = data\n", + "\n", + "results_complete" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "773163e1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'fi': {'Qwen2.5-14B-Instruct': 0.8868469034419542,\n", + " 'Llama-3.3-70B-Instruct': 0.8822406658180483,\n", + " 'gemma-2-27b-it': 0.8924107902654057,\n", + " 'Qwen2.5-32B-Instruct': 0.9113634731999892,\n", + " 'Qwen2.5-7B-Instruct': 0.89194524734931,\n", + " 'gemma-3-27b-it': 0.901604515831509,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8987635078006797,\n", + " 'Llama-3.2-3B-Instruct': 0.8257871100756643,\n", + " 'Llama-3.1-8B-Instruct': 0.9127026234342277,\n", + " 'Qwen2.5-72B-Instruct': 0.8849307457920452},\n", + " 'el': {'Qwen2.5-14B-Instruct': 0.8785970432710287,\n", + " 'Llama-3.3-70B-Instruct': 0.8917784896472812,\n", + " 'gemma-2-27b-it': 0.8975557679616587,\n", + " 'Qwen2.5-32B-Instruct': 0.9145076761966459,\n", + " 'Qwen2.5-7B-Instruct': 0.8884000858698269,\n", + " 'gemma-3-27b-it': 0.9090243751659209,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.9027732523608726,\n", + " 'Llama-3.2-3B-Instruct': 0.8384485864026487,\n", + " 'Llama-3.1-8B-Instruct': 0.9027368881716582,\n", + " 'Qwen2.5-72B-Instruct': 0.876186125820189},\n", + " 'pl': {'Qwen2.5-14B-Instruct': 0.8915379457181469,\n", + " 'Llama-3.3-70B-Instruct': 0.893028125368284,\n", + " 'gemma-2-27b-it': 0.9062881539149782,\n", + " 'Qwen2.5-32B-Instruct': 0.8845149553825653,\n", + " 'Qwen2.5-7B-Instruct': 0.885901770953761,\n", + " 'gemma-3-27b-it': 0.9018338533995509,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.9026522574185668,\n", + " 'Llama-3.2-3B-Instruct': 0.8339288289090923,\n", + " 'Llama-3.1-8B-Instruct': 0.914083301360287,\n", + " 'Qwen2.5-72B-Instruct': 0.8816677522551835},\n", + " 'es': {'Qwen2.5-14B-Instruct': 0.890918266071231,\n", + " 'Llama-3.3-70B-Instruct': 0.892492436917667,\n", + " 'gemma-2-27b-it': 0.9034092500125896,\n", + " 'Qwen2.5-32B-Instruct': 0.9027848177718728,\n", + " 'Qwen2.5-7B-Instruct': 0.8902914405546271,\n", + " 'gemma-3-27b-it': 0.8939431282681429,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8998704265053911,\n", + " 'Llama-3.2-3B-Instruct': 0.8523634509050897,\n", + " 'Llama-3.1-8B-Instruct': 0.9074997802988962,\n", + " 'Qwen2.5-72B-Instruct': 0.8957959135574456},\n", + " 'fr': {'Qwen2.5-14B-Instruct': 0.898344917756121,\n", + " 'Llama-3.3-70B-Instruct': 0.8934492839155558,\n", + " 'gemma-2-27b-it': 0.9001173990478823,\n", + " 'Qwen2.5-32B-Instruct': 0.9048978448480057,\n", + " 'Qwen2.5-7B-Instruct': 0.8841606882232718,\n", + " 'gemma-3-27b-it': 0.8943926676385515,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8965302081569092,\n", + " 'Llama-3.2-3B-Instruct': 0.8356932100976866,\n", + " 'Llama-3.1-8B-Instruct': 0.8985141342922355,\n", + " 'Qwen2.5-72B-Instruct': 0.8955451032568394},\n", + " 'it': {'Qwen2.5-14B-Instruct': 0.8913863623277738,\n", + " 'Llama-3.3-70B-Instruct': 0.8892769479381065,\n", + " 'gemma-2-27b-it': 0.8918213317029476,\n", + " 'Qwen2.5-32B-Instruct': 0.8949908435847219,\n", + " 'Qwen2.5-7B-Instruct': 0.8876000718308812,\n", + " 'gemma-3-27b-it': 0.9095851845950752,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8911118391489357,\n", + " 'Llama-3.2-3B-Instruct': 0.8822217327335828,\n", + " 'Llama-3.1-8B-Instruct': 0.9122718348963341,\n", + " 'Qwen2.5-72B-Instruct': 0.8963504900865995},\n", + " 'lt': {'Qwen2.5-14B-Instruct': 0.8861634817796046,\n", + " 'Llama-3.3-70B-Instruct': 0.8931184670401409,\n", + " 'gemma-2-27b-it': 0.8981452608867684,\n", + " 'Qwen2.5-32B-Instruct': 0.9004884899333929,\n", + " 'Qwen2.5-7B-Instruct': 0.8788953871955031,\n", + " 'gemma-3-27b-it': 0.9020748460084927,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.9095731186603835,\n", + " 'Llama-3.2-3B-Instruct': 0.8748732893918199,\n", + " 'Llama-3.1-8B-Instruct': 0.9084089471740812,\n", + " 'Qwen2.5-72B-Instruct': 0.9032752270312255},\n", + " 'hu': {'Qwen2.5-14B-Instruct': 0.888959762255007,\n", + " 'Llama-3.3-70B-Instruct': 0.8905951027249435,\n", + " 'gemma-2-27b-it': 0.8975707836309588,\n", + " 'Qwen2.5-32B-Instruct': 0.9146346250909738,\n", + " 'Qwen2.5-7B-Instruct': 0.8866072382281535,\n", + " 'gemma-3-27b-it': 0.8926916357304051,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.898176708232311,\n", + " 'Llama-3.2-3B-Instruct': 0.8561176100292405,\n", + " 'Llama-3.1-8B-Instruct': 0.8995136691627227,\n", + " 'Qwen2.5-72B-Instruct': 0.8815936325236656},\n", + " 'en': {'Qwen2.5-14B-Instruct': 0.9022943820962006,\n", + " 'Llama-3.3-70B-Instruct': 0.8974923026344537,\n", + " 'gemma-2-27b-it': 0.8960171839458505,\n", + " 'Qwen2.5-32B-Instruct': 0.8869894075669653,\n", + " 'Qwen2.5-7B-Instruct': 0.897278426639461,\n", + " 'gemma-3-27b-it': 0.8964794133440245,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8963016134450722,\n", + " 'Llama-3.2-3B-Instruct': 0.8499529631689791,\n", + " 'Llama-3.1-8B-Instruct': 0.8989956000238616,\n", + " 'Qwen2.5-72B-Instruct': 0.8871628544616091}}" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metric_name = \"NDCG@all\"\n", + "\n", + "metric_results = {lang: {model: subsubresult[\"metrics\"][metric_name] for model, subsubresult in subresult.items()} for lang,subresult in results_complete.items() if lang in language_codes.keys()}\n", + "metric_results" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "60f8ea85", + "metadata": {}, + "outputs": [], + "source": [ + "metric_df = pd.DataFrame.from_dict(metric_results)\n", + "metric_df[\"avg\"] = metric_df.mean(axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "id": "e9caf110", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "plt.figure(figsize=(12, 6))\n", + "metric_df = metric_df.sort_index() \n", + "ax = sns.heatmap(metric_df, annot=False, fmt=\".3f\", cmap=\"viridis\", linewidths=0.5, cbar=True)\n", + "\n", + "# Add text annotations with bold max values\n", + "for i, model in enumerate(metric_df.index):\n", + " for j, lang in enumerate(metric_df.columns):\n", + " value = metric_df.iloc[i, j]\n", + " max_val = metric_df[lang].max()\n", + " weight = 'bold' if np.isclose(value, max_val) else 'normal'\n", + " ax.text(j + 0.5, i + 0.5, f\"{value:.3f}\", \n", + " ha='center', va='center', color='black', fontsize=9, fontweight=weight)\n", + "\n", + "# Final touches\n", + "plt.title(f\"{metric_name}\")\n", + "# plt.ylabel(\"Model\")\n", + "# plt.xlabel(\"Language\")\n", + "plt.xticks(ticks=np.arange(len(metric_df.columns)) + 0.5, labels=metric_df.columns, rotation=45)\n", + "plt.yticks(ticks=np.arange(len(metric_df.index)) + 0.5, labels=metric_df.index, rotation=0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d7739ea", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, - "id": "a21457a3", + "id": "a7766cf9", "metadata": {}, "outputs": [], "source": [] From 8c9f50a5d1ab005f9709a62b7755b947ccde16ef Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Fri, 9 May 2025 10:22:35 +0200 Subject: [PATCH 4/7] feat: more diagrams in mlfilter paper notebook --- notebooks/edu_content_human_as_a_judge.ipynb | 20999 +++++++++++++---- 1 file changed, 15852 insertions(+), 5147 deletions(-) diff --git a/notebooks/edu_content_human_as_a_judge.ipynb b/notebooks/edu_content_human_as_a_judge.ipynb index cb6b11a5..0002db1e 100644 --- a/notebooks/edu_content_human_as_a_judge.ipynb +++ b/notebooks/edu_content_human_as_a_judge.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 39, + "execution_count": 1, "id": "e32546d4", "metadata": {}, "outputs": [], @@ -13,7 +13,9 @@ "from pathlib import Path\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", - "import seaborn as sns\n" + "import seaborn as sns\n", + "import re\n", + "from collections import Counter\n" ] }, { @@ -26,23 +28,25 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 77, "id": "efba794a", "metadata": {}, "outputs": [], "source": [ "language_codes = {\n", - " \"en\": \"English\",\n", + " \"en\": \"English\", # TODO: Remove English from the list?\n", " \"es\": \"Spanish\",\n", " \"fr\": \"French\",\n", " \"it\": \"Italian\",\n", " \"pl\": \"Polish\",\n", " \"el\": \"Greek\",\n", - " \"no\": \"Norwegian\",\n", + " \"nb\": \"Norwegian\", # Bokmal\n", " \"hu\": \"Hungarian\",\n", " \"fi\": \"Finnish\",\n", " \"lt\": \"Lithuanian\",\n", - "}" + "}\n", + "\n", + "ablated_models = [\"gemma-3-27b-it\", \"Llama-3.3-70B-Instruct\", \"Mistral-Small-3.1-24B-Instruct-2503\"]" ] }, { @@ -55,14 +59,19 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 78, "id": "e976311c", "metadata": {}, "outputs": [], "source": [ "gt_annotations_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_raw_scores/annotations__educational_content__en__gt.jsonl\")\n", "en_documents_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_en.jsonl\")\n", - "llm_as_a_judge_metrics_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/output/llm_as_a_judge_metrics\")" + "llm_as_a_judge_metrics_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/output/llm_as_a_judge_metrics\")\n", + "annotated_500k_samples_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content\")\n", + "plot_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/output/plots\")\n", + "\n", + "if not plot_path.exists():\n", + " plot_path.mkdir(parents=True)" ] }, { @@ -75,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 79, "id": "3467ff65", "metadata": {}, "outputs": [], @@ -86,7 +95,7 @@ " for line in f:\n", " obj = json.loads(line)\n", " row = obj.get(\"scores\")\n", - " cleaned = [int(x) if x is not None else None for x in row]\n", + " cleaned = [int(x) if x is not None else None for x in row] # we get three scores per document\n", " if cleaned: # ensure it’s not empty\n", " scores.append(cleaned)\n", " return scores\n", @@ -110,7 +119,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 80, "id": "57a95718", "metadata": {}, "outputs": [], @@ -124,8 +133,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "a9a6602c", + "execution_count": 81, + "id": "142a4b26", "metadata": {}, "outputs": [ { @@ -137,8 +146,7 @@ } ], "source": [ - "jsonl_path = \"annotations__educational_content__en__gt.jsonl\"\n", - "annotations = load_gt_annotations(jsonl_path)\n", + "annotations = load_gt_annotations(gt_annotations_path)\n", "alpha = compute_krippendorff_alpha(annotations)\n", "print(f\"Krippendorff’s alpha (ordinal): {alpha:.3f}\")" ] @@ -153,7 +161,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 82, "id": "c43d692e", "metadata": {}, "outputs": [ @@ -163,19 +171,19 @@ "np.float64(0.5627472794400139)" ] }, - "execution_count": 72, + "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gt_annotations = load_gt_annotations(gt_annotations_path)\n", - "np.array(gt_annotations).std(axis=1).mean()\n" + "np.array(gt_annotations).std(axis=1).mean()" ] }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 83, "id": "08d566f8", "metadata": {}, "outputs": [ @@ -204,6 +212,34 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "29c45956", + "metadata": {}, + "source": [ + "### Agreement Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "id": "3a5814db", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Agreement rate: 0.785\n" + ] + } + ], + "source": [ + "annotations = load_gt_annotations(gt_annotations_path)\n", + "at_least_two_equal = [int(len(set(row)) < 3) for row in annotations]\n", + "print(f\"Agreement rate: {sum(at_least_two_equal) / len(at_least_two_equal):.3f}\")" + ] + }, { "cell_type": "markdown", "id": "5bd0348d", @@ -214,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 85, "id": "5e1987d3", "metadata": {}, "outputs": [], @@ -225,55 +261,69 @@ }, { "cell_type": "code", - "execution_count": 77, - "id": "ce70f9a3", + "execution_count": 86, + "id": "99e69d68", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "
" + "[np.float64(27.59295499021526),\n", + " np.float64(62.230919765166334),\n", + " np.float64(86.10567514677103),\n", + " np.float64(97.84735812133071),\n", + " np.float64(100.0)]" ] }, + "execution_count": 86, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "\n", "# Sort the data\n", "sorted_arr = np.sort(spread)\n", "\n", "# Unique values and their cumulative percentages\n", "values = np.unique(sorted_arr)\n", "cdf = [np.mean(spread <= v) * 100 for v in values] # percentage of elements ≤ v\n", - "\n", + "cdf" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "ce70f9a3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ "# Plot CDF\n", - "plt.figure(figsize=(4, 4))\n", + "plt.figure(figsize=(6, 4))\n", "plt.ylim(0, 100)\n", "plt.step(values, cdf, where=\"post\")\n", "plt.xlabel(\"Spread\")\n", "plt.ylabel(\"Cumulative Percentage (%)\")\n", - "plt.title(\"Cumulative Distribution of the Spread of Annotations\")\n", + "# plt.title(\"Cumulative Distribution of the Spread of Annotations\")\n", "plt.grid(True)\n", "plt.tight_layout()\n", + "plt.savefig(plot_path / f\"human_annotations_cummulative_spread.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 68, - "id": "76a92eaa", - "metadata": {}, - "outputs": [], - "source": [ - "top_k_spread_doc_ids = spread.argsort()[::-1][:k]" - ] - }, - { - "cell_type": "code", - "execution_count": 70, + "execution_count": 88, "id": "4abce843", "metadata": {}, "outputs": [ @@ -542,7 +592,7 @@ ], "source": [ "# documents with largest spread\n", - "\n", + "top_k_spread_doc_ids = spread.argsort()[::-1][:k]\n", "documents = load_documents(en_documents_path)\n", "for doc_id in list(top_k_spread_doc_ids):\n", " document = documents[doc_id]\n", @@ -553,6 +603,92 @@ " print(\"========================================================================================================\")" ] }, + { + "cell_type": "markdown", + "id": "c8799cee", + "metadata": {}, + "source": [ + "### Filtering documents by given scores" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "id": "34ad74ff", + "metadata": {}, + "outputs": [], + "source": [ + "doc_ids = np.argwhere(np.all(np.array(gt_annotations) == [5,5,5], axis=1)).flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "id": "b3b5f51c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Document ID 1: 53\n", + "Document ID 2: 53\n", + "Scores: [5, 5, 5]\n", + "Text: Are you confused about how many ounces are in 1.2 liters? If you’re from a country that primarily uses the metric system, you might find it challenging to convert the volume measurements into imperial units. In this guide, we’ll discuss everything you need to know about converting liters to ounces and vice versa.\n", + "This guide will be helpful if you’re cooking something or working with ingredients that require a certain amount of liquid. By the end of this article, you’ll be able to convert liters to ounces effortlessly. Let’s get started!\n", + "What is a liter, and what is an ounce?\n", + "Before diving into conversions, let’s define what a liter and an ounce mean. A liter is a unit of volume in the metric system, and it’s equal to 1000 milliliters. An ounce, on the other hand, is a unit of volume in the imperial system, and it’s equal to 28.35 milliliters or 1/128th of a U.S. gallon.\n", + "How Many Ounces in 1.2 Liters?\n", + "To convert liters to ounces, you’ll need to know that one liter is equal to 33.814 ounces. Therefore, to calculate how many ounces are in 1.2 liters, you’ll need to multiply 1.2 by 33.814. The answer, in this case, is 40.5768 ounces.\n", + "How Many Ounces Are in 1/2 Liter?\n", + "To convert 1/2 liter to ounces, you’ll need to multiply 0.5 by 33.814. The result is 16.907 ounces.\n", + "How Many Ounces in 1 Liter?\n", + "If you want to know how many ounces are in one liter, you don’t have to do any calculations because we know that one liter equals 33.814 ounces. So, if you have one liter of liquid, it’s the same as having 33.814 ounces.\n", + "How Many Liters in 1 Ounce?\n", + "To convert ounces to liters, you’ll need to divide the number of ounces by 33.814. For example, if you have 16 ounces of liquid and want to know how many liters that is, you’ll need to divide 16 by 33.814. The answer is 0.473 liters.\n", + "How to Measure Liquid in Ounces and Liters\n", + "In cooking, measuring the right amount of liquid is crucial to ensure the recipe’s success. You can measure liquid in both ounces and liters, depending on the recipe’s requirements. Measuring cups and spoons are widely used to measure liquid in ounces, while measuring jugs or cups are used for liters. Here are some tips for measuring liquid:\n", + "Measuring Liquid in Ounces\n", + "- Fill the measuring cup to the desired amount, holding the cup at eye level to ensure accuracy.\n", + "- Avoid shaking the cup to level the liquid as it can introduce more air into the mixture.\n", + "Measuring Liquid in Liters\n", + "- Place the measuring jug or cup on a flat surface and make sure it’s stable.\n", + "- Pour the liquid slowly to the desired amount, making sure it’s level with the markings on the jug or cup.\n", + "Conversion Table for Liters to Ounces\n", + "To make the conversion process easier, we’ve created a table with some common conversions of liters to ounces. You can refer to this table whenever you need to make a quick conversion.\n", + "Why is it important to measure accurately?\n", + "Cooking is a science, and the success of the recipe depends on accurate measurement. If you add too much or too little liquid to a recipe, it can affect the texture, flavor, and consistency. For instance, if you add too much liquid to a cake recipe, it might turn out dense and chewy. On the other hand, if you add too little liquid, the cake might be dry and crumbly. Therefore, it’s essential to measure accurately to ensure the recipe’s success.\n", + "In conclusion, converting liters to ounces is simple if you know the conversion rate. One liter is equal to 33.814 ounces, and you can use this conversion rate to make any necessary calculations. It’s essential to measure liquid accurately in cooking to ensure the recipe’s success. Now that you’ve learned how to convert liters to ounces, you can use this knowledge in your cooking and baking endeavors!\n", + "Frequently Asked Questions\n", + "- How many ounces are in 1.2 liters? There are 40.5768 ounces in 1.2 liters.\n", + "- How many ounces are in 1 liter? There are 33.814 ounces in one liter.\n", + "- How do you measure liquid in ounces? You can use measuring cups and spoons to measure liquid in ounces.\n", + "- How do you measure liquid in liters? You can use measuring jugs or cups to measure liquid in liters.\n", + "- Why is it important to measure accurately? Accurate measurement is crucial to ensure the success of the recipe.\n", + "Convert Units. (n.d.). Liters to US Fluid Ounces Conversion. Retrieved August 03, 2021, from https://www.convertunits.com/from/liters/to/us+fluid+ounces\n", + "========================================================================================================\n" + ] + } + ], + "source": [ + "documents = load_documents(en_documents_path)\n", + "for doc_id in list(doc_ids):\n", + " document = documents[doc_id]\n", + " print(f\"Document ID 1: {doc_id}\")\n", + " print(f\"Document ID 2: {document['document_id']}\")\n", + " print(f\"Scores: {gt_annotations[doc_id]}\")\n", + " print(f\"Text: {document['text']}\")\n", + " print(\"========================================================================================================\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3a289826", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 91, @@ -561,7 +697,7 @@ "outputs": [ { "data": { - "image/png": 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", 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4OPj4+CA2Nhbe3t5F+t4xMTFF+n6m4O/vr3YIZITYWJmH/9tvMq0pW8OGkkz07w84O6sXH5lGTAzQsaN83j4+UsWLv7pEREVDzXPL4oa1RIhKmPR0KRP766/Ahg0564/KlQMGDZLpTvXqqRkhmZq/PxAZCXTqJOW6W7aU0d8GDdSOjIiI8nP58mXs2bMH8fHxSE5ORr9+/RAQEJDvvqtXr8ahQ4cQGhqKpk2barc/fPgQ69atQ0xMDDQaDQIDA9GlSxdYW1sX1beRB+soEZUQ0dHAhAmAt7dMb1q/XpKKtm2BP/8E4uOBH35gUlFS+fgAO3fKmrWbN2Wa1I4dakdFRET5SU9Ph4eHB7o+rcszgOjoaMTFxcHJySnPcxEREbhx4wYGDx6MAQMG4MqVK1i1alVhhVwgTCyIzFhyck7H66Ag6W1w86ZUeXr3XSlwsHWrNJe0s1M7WipsFSrI5922rVSJCg2V0SsiIipeatSogXbt2iEwMPCJ+9y/fx/r1q1Dz549YfFYWdSbN2/i3Llz6N69O7y9veHr64suXbrg5MmTSFKxTCATCyIzoyjAgQPSv8XTE3j5ZWDPHqmMFh4OrFolhQ8++wyoVk3taKmoOTkBa9dKI8O0NKBnT2l2SEREhSspKQn379/X3tLS0gw+lqIoWL58OZo1awZ3d/c8z8fFxcHW1hZeXl7abVWrVoVGo0FcXJzB72ssJhZEZuL2bWDaNKBuXSm3/MsvMmJRvbqUZI6NlZ4Gzz/PTsylna0t8NdfwLBhQGamlPWeOlXtqIiISragoCA4Oztrb1Oy+yUYYPfu3bCwsEBwcHC+zycnJ8PBwUFnm4WFBezs7JCcnGzw+xqLpx9EKsnMBHbtAhISZOShZcu8/ViysmRqy+zZUiY2PV2229rKOorhw4FWrVgmlvKyspIF/K6u0v/nrbckOf34Y/68EBEVhqioKFSqVEn72MbGxqDjxMfHY//+/Rg5ciQ0ZvYHm4kFkQoiIoCxY4Hco5Xe3jIi0bOnbM8uE3vpUs4+9etLmdgBA6TKE9HTWFgAX38tTfPefRf49FNJLn78UbdHEBERGc/JyQlly5Y1+jhXrlxBSkoKvvvuO+02RVGwceNG7Nu3D+PGjYOjoyNSUlJ0XpeVlYWHDx/C0dHR6BgMxcSCqIhFRAC9e+eUgc129SrQq5eUCD16VEYrAOkzMXCgjE6wfCjpS6MBJk6UkYvXXwd++gm4cweYNw9QsSIhERE9QZ06dVC1alWdbfPnz0edOnVQ79/Sjt7e3khNTUV8fLx2ncXFixehKIqqvTSYWBAVocxMGanIry1l9rbDh+Vr69YyOtGrFys6kfFGjpRRrsGDgUWLgLt3gWXLAHt7tSMjIip90tPTkZiYqH18584dXLt2DXZ2dnB2dob9Y3+cLSws4OjoCDc3NwBAhQoVUL16daxatQrPP/88MjMzsXbtWtSqVSvf0rRFhYkFURHatUt3+tOT/PGHNLMjMqV+/SS56NlT+px07AisXg24uKgdGRFR6RIfH4958+ZpH2/cuBEAULduXfTo0aNAx+jZsyfWrl2L33//XadBnpqYWBAVoYSEgu33+CJuIlMJDQU2bwa6dpUyxa1bS4d2T0+1IyMiKj38/PwwefLkAu8/bty4PNvs7OzQq1cvE0ZlPC7fIypCBT1540keFaaQEOnS7ekJnDgBtGgBXLigdlRERGTumFgQFaGWLaX605Oqx2k0gI+P7EdUmGrXBnbvBqpWlaSiRQtJMoiIiAzFxIKoCFlaSknZ/BZvZycbU6dyKhQVjapVJbmoXVum6bVqBezdq3ZURERkrphYEBWxnj3zLxvr7Q0sXSrPExUVT09gxw6gWTOpFNWhg6y5ICIi0hcXbxMVsbNnc0rKzp8vjcqe1HmbqCi4uAAbN0p/lfXrgW7dpDJZv35qR0ZEROaEiQVREZs+Xb527SqN74iKAwcHYOVKYOhQ6XPRv7+MYIwcqXZkRERkLjgViqgIJSUBc+bI/TffVDcWosdZW8so2uuvyzqg114DPv88/zVBREREj2NiQVSEfv8duH8fqFlTmpMRFTeWljKq9v778vi994AJE5hcEBHRszGxICoiWVnAjz/K/TFjZG0FUXGk0QCffAJ89508/vZb4OWXgYwMdeMiIqLijac2REVk82bg9GnAyUnmsRMVd+PGAfPmySjG3LlAnz5AaqraURERUXHFxIKoiPzwg3x96SVJLojMwZAhQEQEYGMDrFghRQfu31c7KiIiKo6YWBAVgfPngTVr5P6oUerGQqSv7t2lDK2TE7BtG9CuHXDzptpRERFRccPEgqgITJ8ui1+7dJGF20Tmpk0bSSrc3IBDh6TvSmys2lEREVFxwsSCqJAlJwO//ir3x4xRNxYiYzRsCOzeDfj4ADExQPPm8pWIiAhgYkFU6P74Q+ak16gBhIaqHQ2Rcfz9gchIICBARixatJARDCIiIiYWRIVIUXIWbY8ezRKzVDL4+AC7dgGNGgG3bgFt2wLbt6sdFRERqY2nOUSFaMsWIDoacHQEhg1TOxoi03FzA7ZulaQiKQno3BlYuVLtqIiISE1MLIgKUfZoxbBhQNmyqoZCZHJOTsDatUCPHkBaGtCrl/S9ICKi0omJBVEhuXABWLVK7o8erW4sRIXF1hb46y/pz5KZKUl0dsduIiIqXZhYEBWSGTNkjUVoqCx4JSqprKyk8tl//iOPx48H3n9ffv6JiKj0YGJBVAhSUnJKzL75prqxEBUFjQb46ivg88/l8WefSTPIzEx14yIioqLDxIKoEMyfD9y9C1SvLotaiUoDjQaYOBGYOVPu//QTMHAgkJ6udmRERFQUmFgQmVjuErOjRrHELJU+I0cCixYBZcoAixcD4eEyikdERCWbldoBEJU027YBp04BDg6yoJWoNOrbF3B2Bnr2BNavBzp1AlavBlxc1I6MiIgAIDU1FVevXkVKSgqUxxbF1a1b16BjMrEgMrHvv5evQ4fKiRVRaRUaCmzeDISFAXv2AK1bAxs2AJ6eakdGRFS6xcTEICIiAunp6bCxsYFGo9F5nokFUTFw8SJLzBLlFhIC7NwpIxYnTgAtWgCbNgFVq6odGRFR6bVx40bUr18f7du3R5kyZUx2XM7+JjKhGTOArCygY0cgMFDtaIiKh1q1gN27gWrVpL9L8+aSZBARkTqSkpIQHBxs0qQC4IgFUYHFxMQ89fm0NGDLFqBmTWDIEOAZuxcJfzbQoGKialVJLkJDgePHgVatgDVrgGbN1I6MiKj0qVatGuLj4+Fi4oVvTCyITGT7dql8U7Ei0LCh2tEQFT8VK8rvSbduQGSkjOxFREiyQURERadGjRrYtGkTbt68CXd3d1haWuo8b+iFSSYWRCagKFLxBpCFqiwxS5Q/Fxdg40agd29g3TpJMv74A+jXT+3IiIhKj1X/LgjdsWNHnuc0Gg0mTZpk0HGZWBCZwMmTwOXLgI0N0KGD2tEQFW/29sCKFcCwYcDChUD//sCdO8Brr6kdGRFR6TB58uRCOa5BicXZs1Kr/8YNWaiam4EJDpFZyx6taNdO+lcQ0dNZW0uHehcXKXrw+utAYqJ07n6s6iEREZkJvROLX36R/wDc3GS+bO7/ADQaJhZU+ty8CezfL/eff17dWIjMiYUF8OOPQPnywCefAO+9B9y+DXz1FacTEhGZ2v79+9GwYUNYWVlhf/aJyxMEBwcb9B56Jxaffgp89hnw9tsGvR9RibN2rYzc1asH+PioHQ2RedFogI8/BlxdgbfeAr79VkYufvkFsOJkXSIik9m3bx9q164NKysr7Nu376n7FllicecO0KePQe9FVOKkpclCVICjFUTGGDdOkouXXwbmzpX/axYtAmxt1Y6MiKhkGDt2bL73TUnvweY+fXJOpIhKux07gKQkwMMDaNRI7WiIzNuQIVJ+1sYGWLkS6NoVuH9f7aiIiEo2RVGgKIpJjqX3iEX16sAHHwD79gG1awOPN+x7802TxEVU7LHELJHpde8ObNggZWi3bZOCCOvWARUqqB0ZEVHJcvjwYezbtw+JiYkAAFdXVzRt2hQNGjQw+Jh6JxY//ww4OsqV2sdL32o0TCyo9Dh1Crh0iSVmiUytdWtppNe5M3DoENCyJbBpE9cwERGZyrZt27B37140adIEPv/+cY2NjcWGDRtw7949tG3b1qDj6p1YXLxo0PsQlTjZoxVt20qyTUSm06ABsGsX0KkTEBMDNG8u03ADAtSOjIjI/B08eBDdunVD7dq1tdv8/f3h4eGBdevWFV1ikVv2dCzWHKfS5uZNmQ4IyDQoIjI9f39g925JLk6flpGL9euBhg3VjoyIyDiXL1/Gnj17EB8fj+TkZPTr1w8B/145yczMxNatW3Hu3DncuXMHNjY2qFq1Kjp06AAnJyftMR4+fIh169YhJiYGGo0GgYGB6NKlC6ytrZ/5/pmZmfDy8sqz3cvLC1mPN6nTg0Gzwn//XdZX2NnJrU4d4I8/DI6ByOysWyclZuvUASpXVjsaopLLx0dGLho1Am7dkhHC7dvVjoqIyDjp6enw8PBA165d8zz36NEjXLt2Da1atcKrr76Kfv364fbt21i4cKHOfhEREbhx4wYGDx6MAQMG4MqVK1i1alWB3r9OnTo4ePBgnu2HDh3SGcXQl94jFt9+K4u3R4+WoWlArii99pr80X/rLYNjITIL6emyuBRgiVmiouDmBmzdCvToIV87dwYWLwbCw9WOjIgoR1JSEu7nKmVnY2MDGxubfPetUaMGatSoke9ztra2GDx4sM62Ll26YPbs2bh37x6cnZ1x8+ZNnDt3DiNGjNCOPHTp0gV//vknOnXqpDOykW1D9skLAI1Gg8OHD+P8+fPw9vYGAFy9ehX37t1DnTp19PvGc9F7xOKHH4CffgK+/FKqd3TvDvzvf8CMGcD33xscB5HZ2LlTSsy6uwNNmqgdDVHp4OQErFkjyUVaGtCrFzBvntpRERHlCAoKgrOzs/Y2ZcoUkx07LS0NgCQdABAXFwdbW1ud6UxVq1aFRqNBXFxcvse4du2a9nbjxg14eXnBwcEBd+7cwZ07d2Bvbw9PT0/cvHnT4Dj1HrFISACaNcu7vVkzeY6oJFMUIHuUsWtXlpglKkq2tsBffwGvvgrMmQMMGyZdujlSTkTFQVRUFCpVqqR9/KTRCn1lZGRg8+bNqF27tvaYycnJcHBw0NnPwsICdnZ2SE5Ozvc4Q4cONUk8T6P3aVH16sCSJXm3L14MPGFEh6jEiI6WymjW1rKglIiKlpUV8OuvwH/+I4/Hjwfefz+nmAgRkVqcnJxQtmxZ7c0UiUVmZib++usvKIqCMDOoFqP3iMVHHwH9+sl0kOw1FpGRwJYt+SccRCVJ9mgFS8wSqUejAb76StZeTJwIfPYZcPs28OOPgKWl2tEREZlGZmYmli5dinv37mHIkCE6iYqjoyNSUlJ09s/KysLDhw/hqOIJit4jFr16Afv3yx/0FSvk5uYGHDgAvPCC6QMkKi5u3QL27pX7XLRNpC6NBnjnHWDWLLk/cyYwcKAUVyAiMnfZScXt27cxePBg2Nvb6zzv7e2N1NRUxMfHa7ddvHgRiqJoF2OrwaA+Fg0bAvPnmzoUouItu8Rs7dosMWuOYmJi1A5BL/7+/mqHYBZefRUoVw4YNEim5N67ByxdCjw29ZiIqFhJT09HYmKi9vGdO3dw7do12NnZwdHREX/99RcSEhLQv39/KIqiXTdhZ2cHS0tLVKhQAdWrV8eqVavw/PPPIzMzE2vXrkWtWrXyrQhVVAqUWNy/D5Qtm3P/abL3IypJHj6UxlwA0K2burEQka6+fQFnZ6BnT/k97dQJWL0acHFROzIiovzFx8djXq7Sdhs3bgQA1K1bF23atNFeDJs1a5bO64YOHQo/Pz8AQM+ePbF27Vr8/vvvOg3yniUzMxOrV69Gq1at4GLiP5QFSixcXKTik7u7XBnKr9O2osj2zEyTxkdULCxaJCVmK1QAGjdWOxoielxoKLB5MxAWBuzZA7RqBWzcCHh6qh0ZEVFefn5+mDx58hOff9pz2ezs7NCrVy+939vS0hLR0dFo1aqV3q99lgIlFlu3Aq6ucn/bNpPHQFSsKYr0bwHkpIWLQ4mKp5AQKSzSqRNw8qQUGNm0CahWTe3IiIiKl4CAAJw+fRohISEmPW6BEovWrXPuV6kC+PjkHbVQFCA21pShERUPkZHAkSNArVpAx45qR0NET1OrlvzOduwInD8PtGgBbNgAGNFIloioxHF1dcXOnTsRGxsLT09PWFtb6zwfHBxs0HH1XrxdpUrOtKjcEhPlOU6FopIme7SiTRvp/ktExVuVKsDu3TI96vhxuTi2Zk3+zV2JiEqjI0eOwNbWFgkJCUjIp8N1kSUW2WspHpecLF1RiUqSuDhg2TK5zxKzROajYkVgxw75vY2MBDp0ACIigM6d1Y6MiEh9Y8eOLZTjFjixGD9evmo0wAcfALnL6WZmSm+LevVMHB2RymbOlJ/v1q2Bf4swEJGZKFdOFnD37i3lort1A/74A3jxRfm93rVLRuA9PYGWLbl+iohKn8zMTNy5cweurq6wsNC7vV0eBU4sjhyRr4oCnDgB5J6KZW0N1K0LTJhgdDxExUZqKvDzz3J/zBh1YyEiw9jbSyPXYcOAhQuBAQOkIMm6dTIimc3bG5g2TUrWEhGVdI8ePcLatWtx7NgxAMCYMWPg4uKCtWvXomzZsmjRooVBxy1wYpFdDeqll+SPL/tVUEm3eDFw86YUKwgPl4WgRGR+rK2lqauLCzBjBvDLL3n3uXpVRjaWLmVyQUQl3+bNm3H9+nUMGzYM83N1va5atSp27NhhcGKh95jHnDlMKqjky11i9o03ACuDetQTUXFhYSEXxZ5UgEFR5Ou4cSxCQkQlX0xMDLp27QpfX19oci2ednd31+kIri+DTpcOHgSWLAGuXAHS03Wfi4gwOBaiYmPvXuDQIcDGBnjlFbWjISJT2L1bGl0+SXbZ9F27pAocEVFJlZKSAgcHhzzb09PTdRINfek9YrFokZTsi44Gli8HHj0CTp2SOavOzgbHQVSsZI9WDBwIuLmpGwsRmUY+FRXztWULRy2IqGTz8vLCmTNn8mw/fPgwvL29DT6u3onF558D330HrFol81anTQNOnwb69gV8fQ2Og6jYiI+XedYAF20TlSSengXb79NPAS8vYORIqSr16FHhxkVEVNTat2+PrVu3YvXq1cjKysL+/fvxxx9/4OjRo2jXrp3Bx9U7sTh/HggLk/vW1kBKipSgfeutnAo6ROZs5kwgI0PKT7KEMlHJ0bKlVH962ii/vb2Uqb1xQ/5PCw0FPDykcMnq1UBaWpGFS0RUaHx9fTFy5EhkZWXB3d0d58+fh4ODA4YPHw4vLy+Dj6v3GgsXl5w5qpUqASdPArVrA3fvAg8eGBwHUbGQlgbMmiX3OVpBVLJYWsooe+/eklxkL9gGcpKNP/6Qfhfbt8vI5fLlUh1u7ly5OTnJ8716SbO93D2diIjMiaurK7p3727SY+o9YtGqFbBpk9zv0wcYOxYYMQLo3x9o396ksREVuSVL5EqltzfQo4fa0RCRqfXsKQlDpUq62729c0rNlikDdOwoFxkSEiTJGDNGpkclJQELFkhiUaGCJCmLFj19UTgRUXGUlZWFqKgo7NixAzt27EBUVBSysrKMOqbeIxY//iiNwwDgvffkD/CePfJH9v33jYqFSFWKAnz/vdx//XX52SaikqdnT+lNU5DO25aWQOvWcps6Fdi/H1i2TG6XLuXct7EBOnWS/wu7d5fRfSKi4urGjRtYtGgRkpOTUb58eQBAZGQkHBwc0L9/f7i7uxt0XI2i5B4MLvni4uLg4+OD2NhYo1a9GyImJqZI388U/P391Q6hyOzbB4SEyAlCbKxcjcyNn595M7fPj59d8aYowOHDOYlF7uIqVlYygt+rl4x8Pv63hIhKFjXPLQ3166+/wt7eHj169ICdnR0A4OHDh1i5ciVSUlIwfPhwg45boKlQ9+/r3n/ajchcZY9W9O/PEwEiejqNBmjYUColnj4NnDgBTJ4M1KolxR82bABefRWoWBFo1w6YPl0qzhERFQfXrl1D+/bttUkFANjZ2aFdu3a4du2awcctUGLh4iLzzgGpluHikveWvV1f06cDfn6ArS0QHAwcOPD0/e/eBUaNkqFrGxugZk1g7Vr935cot/h44K+/5D4XbRORPjQaSSg+/FASjNOngc8+Axo0ALKygG3bgNGjZR1HixZSsv3yZbWjJqLSrHz58khJScmzPSUlBa6urgYft0BrLLZuBbLfY+vWp5fq08fixcD48VLeMzhY5q+GhgIxMUB+U7vS02VBnbt7zuK7y5clqSEyxqxZcpWxeXM5GSAiMpS/P/Duu3K7eBGIiJD/s/btAyIj5TZ+PNCokSz+7tULqF5d7aiJqDRp37491q1bhzZt2minb8XFxWHHjh3o0KED0nLV1raxsSnwcVVdYxEcDDRuLAvCAbmy4+MjV4zfeSfv/jNnAl99JVeDCrqwNi0tTecf5+rVqwgKCuIaiwIqDfO809OlueP165Ls9u2b/378/MybuX1+/OxKnrg4KV+7bBmwc6duuds6dXKSjKAg9WIkIv2Z4xqLjz76SHtf8++IQXZKkPuxRqPBpEmTCnxcvatC1agBDBwotxo19H11jvR04NAhYOLEnG0WFkCHDsDevfm/5u+/ZXHtqFHAypUyD37AAODtt/Ov5gEAU6ZM0fnHI3rcX39JUlGpEvDCC2pHQ0Qllbe3XDgbM0b+5qxYIUnG1q3A8eNymzQJCAiQBKNXL2nSaapZAkRE2YYOHVoox9W7j8UbbwBr1sgfvsaNpdmQIWs8bt0CMjOlo2luHh5PPt6FCzKcnJkp6yo++AD45hvg00+f/D4TJ07EvXv3tLeoqCj9g6USjSVmiaioeXgAI0cCGzdKkvHbb0BYGGBtrbtGo3p14P/+T8rclq4ajkRUmPz8/Ap804feicVbbwH//ANERwNdu8riax8fqd/9++/6Hk0/WVmyvuLnn6UaR79+0ktj5swnv8bGxgZly5bV3pycnAo3SDIr+/dLwQBra2n0SERU1MqXB156CVi9WgqlzJ8vo6e2tnJB7auvgKZNZcrmuHHSfyMzU+2oiYjy0juxyFazJvDRR1K7e9cu4OZN+cNYUG5uMn3p+nXd7devS3m+/Hh6yvvmnvYUGCgjHOnp+n8PRD/8IF/798+/YAARUVFydpapxhERMrL/119yEc3RUdZoTJsGtGolUzffeAPYskUKTxARFQcGJxaAXOkdN06urJw5A/TpU/DXWlvLqMOWLTnbsrLkcUhI/q9p3hw4d072y3bmjCQc1tYGfQtUil27BixZIvdZYpaIihsHB1nQvWiRXLxbuRIYPFiSj+vXgZ9+knWJFSsCw4cD69bxIhsRqUvvxOLMGWkCVLOmnOhHRwNffil/5BYt0u9Y48cDv/wCzJsnx3n9dSAlJWfkY8gQ3cXdr78OJCYCY8dKHGvWSHOiUaP0/S6IpMTso0eSyDZsqHY0RERPZmsLdO8uU45v3JAk4pVXZBrV7duyRqNrVxl5HTxYFoY/fKh21ERU2uhdFSp70faoUcCLL+ZdfK2Pfv3kKsykSXL1uF49YP36nGNeuSKVorL5+Eg307fektJ8lSpJkvH224bHQKVTenrO2pw331Q3FiIifVhbA507y+2nn6R07bJlMn3q2jVZozF/vox4hIVJdamuXWU6FRERADx69AgAUObfqjV3797F6dOnUaFCBVSrVs3g4+rdx+LsWePKzKpNzVrD5lZHHyi5tfQXLJB5zJ6e0mSxINWg+PmZN3P7/PjZkb6ysoA9eyTJWLYMiI3Nec7WVhKRXr2Abt1kOhURmYY59rH4448/EBgYiEaNGiE1NRU//vgjLC0t8eDBA3Tq1AmNGzc26Lh6T4WqUQO4exeYPVumKSUmyvbDh4GrVw2KgajIZS/aZolZIiopLCyAFi2A776TCyb790up2mrVgNRUmR41eLD0gAoLk+lTt2+rHTURqSEhIQG+vr4AgKioKDg6OmLcuHHo0aMHDhw4YPBx9U4sjh+X5OLLL4Gvv5YkA5Ah2NzrIYiKq3/+Afbtk+kEr76qdjRERKan0QBNmsj/1WfPAkePAu+/L5UUHz2SXlDDh8vU4w4dZGqoIT2piMg8PXr0CDY2NgCA8+fPIyAgABqNBt7e3ribfXJvAIP6WLz0kvyhsrXN2d61q8zzJCruskcr+vUzbo0QEZE50GiAunWBTz4BoqLk9sknsi0zU6oxvv464OUlpWy//15K2xJRyeXq6orTp0/j3r17OH/+vHZdRUpKijbhMITeicXBg9It9HGVKvFqBxV/uauXscQsEZVGgYEyenH0qFwk/PJLGd1QFOlLNXasFEtp2lSa8124oHbERGRqrVu3xsaNGzFt2jRUqlQJPj4+AGT0wtPT0+Dj6l0VysYGuH8/7/YzZ2TeJlFx9vPPMg2gaVOpbkZEVJpVry7rMP7v/6QSY0SELPyOjJQ1GtnrNOrXl4XfvXpJdUgiMm9BQUHw9fVFUlISKubqTF21alUEBgYafFy9Ryy6dwc+/lhOzgAZYr1yRUq+9uplcBxEhS49XUozAhytICJ6nK+vNL3dtUuKsUyfDrRrJ4vCjxzJWaNRq5b0szp+XEY5iMj8rFy5EmXKlIGnpyc0Go12e4UKFRAZGWnwcfVOLL75BkhOliY8Dx8CrVvLFQ8nJ+CzzwyOg6jQRUQACQnSpbZ3b7WjISIqvjw9gTfekPUX169LJcjOnaWK3qlTcoGxbl1pljtxokyTZpJBZD6OHTuGjIyMPNszMjJw7Ngxg4+r91QoZ2dg0yZg9265WpGcDDRoIFUliIqz77+Xr6+9JhWhiIjo2dzcpILU8OFSCXLVKpkutX49cO4c8MUXcqtcGejZUy7cNG2q2+CWiIqHtLQ0KIoCRVGQlpYGK6ucVCArKwtnz56Fg4ODwcfXO7HI1qKF3IjMwaFDwN69crUtv+IDRET0bOXKSS+MwYOBpCQpW7tsGbBmjfTO+O47uXl5AS+8IFOkW7YErAw+2yAiU/riiy+g0Wig0Wjw448/5rtPmzZtDD5+gX7Vs6/0FsSbbxoaClHhyS4x27evTIUiIiLjODlJ2e5+/YAHD4ANGyTJWLUKiI+XNRrTp0thlx49JMlo145NSYnUNHToUADAvHnz0LdvX9jZ2Wmfs7S0RLly5eDk5GTw8TWK8uxZkVWq6D6+eVP+iJQrJ4/v3gXs7WXdRXEvS6dm2/WYmJgifT9T8Pf3VzsEo924IaUT09OlwkmTJoYdh5+feTO3z4+fHZmrtDRg82ZJMlauBBITc54rVw4ID5cko2NH3X5YRObKkHPLy5cvY8+ePYiPj0dycjL69euHgFwl1xRFwfbt23H48GGkpqbCx8cHYWFhKF++vHafhw8fYt26dYiJiYFGo0FgYCC6dOkC6wLM97579y6cnZ11Fm6bQoFmQF68mHP77DOgXj0gOlr+WCQmyv0GDaThDlFx88svklQ0aWJ4UkFERAVjYwOEhQG//Sb9rTZtkimo7u5yIXLePKkw6e4ODBggCUhKitpRExWt9PR0eHh4oGvXrvk+HxkZif379yMsLAyvvPIKrK2tMX/+fJ0F1xEREbhx4wYGDx6MAQMG4MqVK1i1alWB3r9cuXJIS0vD+fPncfz4cRw7dkznZii9Zz1+8AGwdCmQ+2Kav7/MqezdGxg40OBYiEzu0SNgxgy5z2l6RERFq0wZKe7SoYNMi4qMlHOIiAgpabtwodzs7IAuXeQ8IiwMKFv2ycfMzJSSuAkJUr2qZUvA0rLovieiJ0lKSsL9XM3ebGxsntjFukaNGqhRo0a+zymKgv3796NVq1baUYwePXrg66+/xunTp1GrVi3cvHkT586dw4gRI+Dl5QUA6NKlC/7880906tTpmdOZYmJiEBERgfT0dNjY2OQZuahbt26Bv+/c9E4sEhKAfKpTITNTStIRFSfLl8tcXw8PoE8ftaMhIiq9LC2BVq3kNnUqcOCAjFYsXQpcuiTJRkSEVO3r1EmmS3XvDri65hwjIkI6g8fF5Wzz9gamTZOKVERqCgoK0nk8efJkfPjhh3of5+7du0hOTkbVqlW122xtbeHt7Y3Y2FjUqlULcXFxsLW11SYVgDS302g0iIuLe2aTu40bN6J+/fpo3749yphw4ZPeiUX79jKkOXu2TH8CpOLO66+z5CwVP9mFB0aOZIlZIqLiwsJCStI2bQr873/SgC87yThzBli9Wm5WVrLgu1cvGf0YPjxvv4yrV2WkY+lSJhekrqioKFSqVEn7+EmjFc+SnJwMAHnKvjo4OCDl33mDycnJeZ63sLCAnZ2d9vVPk5SUhODgYJMmFYABDfJ++02q6jRqJPMobWxk3rqHhyQbRMXF4cMy7G5lJb0riIio+NFo5ELlZ58Bp08DJ04AH34I1K4tMyQ2bpSLQy+/nH8Tvuxt48bJ7AkitTg5OaFs2bLam6GJRVGoVq0a4uPjTX5cvUcsKlSQutVnz8qibQAICJDum0TFSXaJ2T59ZB4uEREVbxoNUKuW3CZPltGLZcuAuXPl/pMoChAbK2svjCjBT1QsODo6AgBSUlJ01kqkpKTAw8NDu0/KY1UPsrKy8PDhQ+3rn6ZGjRrYtGkTbt68CXd3d1g+tlDJ0MqEBresqVFDbkTF0c2bsiAQ4KJtIiJzVbMmMHEi4OcnFaSeJSGh0EMiKnTlypWDo6MjLly4gIr/Nt9KS0tDXFwcGjVqBADw9vZGamoq4uPjtessLl68CEVRClTyNrt61I4dO/I8p9FoMGnSJINiZy9MKpF++UVqqTdqBAQHqx0NEREZo6CjzhydJnORnp6OxFxNXu7cuYNr167Bzs4Ozs7OCA4Oxq5du1C+fHmUK1cO27Ztg5OTk7ZKVIUKFVC9enWsWrUKzz//PDIzM7F27VrUqlWrQA3uJk+eXCjfFxMLKnEePQJ++knuv/mmDK0TEZH5atlSqj9dvZr/OgtAGqG2bFm0cREZKj4+HvPmzdM+3rhxIwAp89qjRw80b94cjx49wqpVq5CamgpfX18MGjQIVlY5p+49e/bE2rVr8fvvv+s0yNNXRkaGznGNwcSCSpwVK6QUobs70Lev2tEQEZGxLC2lpGzv3nKxKL/kYvRo9rMg8+Hn5/fUUQONRoO2bduibdu2T9zHzs4OvXr1Muj9s7KysGvXLhw6dAjJyckYM2YMXFxcsHXrVpQrVw4Nsku/6knvqlBExV32ou2RI6VqGRERmb+ePaWkbK5qngAAW1v5+sMP0umbiJ5t165dOHbsGDp06KCzcNvd3R1Hjhwx+LgFGrE4frzgB6xTx9BQiIx39KhUBWGJWSKikqdnTyA8XLfzdt26QLNmUqq2Vy9g61ZeVCJ6lmPHjuH5559H1apVsWbNGu32ihUr4tatWwYft0CJRb16OUOPz5qvzhrSpKbs0YrevYFczSiJiKiEsLTMW1J25UrpqbVnj0yJ+vlnrq8jepqkpCS45m5r/y9FUZBpxMl8gaZCXbwIXLggX5ctA6pUAWbMkE6ZR47I/WrV5Dkitdy6Bfz5p9wfM0bdWIiIqOjUrAksWiQdvWfPzingQUT5q1ChAq5cuZJne1RUFDyNKK9WoBGLypVz7vfpA3z/PdC1a862OnWkGsMHHwA9ehgcC5FRZs+WErMNGwIhIWpHQ0RERalzZ+CLL4D/+z9g7FggKIjN8oiepFWrVlixYgXu378PRVEQHR2NW7du4fjx4+jfv7/Bx9V78faJEzJi8bgqVYCoKIPjIDJKRoaMnAEyWsEhcCKi0mfCBGmkl5EhF0IvXVI7IqLiKSAgAP3798fFixdRpkwZbNu2Dbdu3UL//v1RrVo1g4+rd7nZwEBgyhS5OmxtLdvS02VbYKDBcRAZZeVKIDYWqFAB6NdP7WiIiEgNGo2cn5w+DRw+LLMoIiMBBwe1IyMqfipXrozBgweb9Jh6JxYzZwLdukmjmuwKUMePyy/zv93BiYpc9qLtV1/NKT1IRESlj52d9DNq1Ag4dgx4+WVZf8GRbKL8paenQ3msOYyNgaXV9E4smjSRhdx//ilXBAC5QjxgAK8IkDqOHwd27JBKIa+/rnY0RESkNh8fKSjTrh2wZIlUt5w4Ue2oiIqPO3fuYN26dbh06RIyMjK02xVFgUajwaRJkww6rl6JxaNHQEAAsHq1XBkmKg6yRyt69crbOImIiEqnFi2A6dPlfOW994DatYHnn1c7KqLiYfny5VAUBd27d4ejo6PJjqtXYlGmDJCaarL3JjLa7dvA/PlynyVmiYgotxEjpHHqjBkys2L/fq4HJQKAa9eu4dVXX4Wbm5tJj6t3VahRo4Avv5SKC0Rq+/VXSXbr1weaN1c7GiIiKm6mTgVatQKSkqRr9927akdEpL5KlSrh/v37Jj+u3mss/vkH2LIF2LhRhhUfX1cREWGq0IieLiNDhrkBlpglIqL8lSkDLF0qi7nPngX695cp3ZaWakdGpJ5u3bphzZo1uH//Ptzd3WH52C+Eh4eHQcfVO7EoV07mshOpbdUq4MoVwM1N/qMgIiLKT4UKUimqeXNg/Xrg3Xdl9gVRafXgwQMkJiZi5cqV2m0ajaZoF28DwJw5Br0Pkcl9/718HTGCJWaJiOjp6teXc5gXXwT+9z+gbl1Zd0FUGq1cuRKenp7o1auXeou3iYqLEyeA7dtZYpaIiAquXz/pbTFlCjB8OODvDzRsqHZUREXv3r176N+/P1xdXU16XIMSi6VLpS70lSvSdTu3w4dNERbR02WXmH3hBalXTkREVBCffCL9j9askc7cBw8CBk4nJzJbVapUwbVr10yeWOhdFer774GXXpJfwiNHpGFe+fLSNK9LF5PGRpSvxMScErNvvqluLEREZF4sLaXJr78/EBcn60Yfv0hKVNLVrFkTGzZswPbt2xEVFYWYmBidm6H0HrGYMQP4+WdZLDt3LvB//wdUrQpMmiQnfESF7ddfgYcPZX5sixZqR0NERObG2RlYuRIIDgYiI6Wy4KxZakdFVHRWr14NANixY0ee54p08faVK0CzZnLfzk7qQgPA4MFA06bAjz8aFAdRgWRm5pSYffNNlpglIiLD+PsDCxcCYWFywbR+feC119SOiqhoTJ48uVCOq/dUqIoVc0YmfH2Bffvk/sWLgKKYMjSivFatAi5flul3LDFLRETG6NIF+OILuT9mDLBzp7rxEJk7vUcs2rUD/v5bMvuXXgLeeksWcx88CPTsWRghEuXIXrQ9YoSMmBERERnjv/8Fjh6V0YvevaURcOXKakdFVLjymwKVW+vWrQ06rt6Jxc8/A1lZcn/UKLlyvGcP0L07MHKkQTEQFcjJk8DWrYCFBUvMEhGRaWg0wOzZQEyMVLbs0UPWXdjbqx0ZUeE5ffq0zuPMzEzcvXsXFhYWcHFxKbrEwsJCbtlefFFuRIUte/3OCy/INDwiIiJTsLcHli8HGjWS0YuXX5YRDK7jo5JqZD6jAWlpaVixYgUCAgIMPm6BEovjxwt+wDp1DA2F6Mnu3AH++EPujxmjbixEVLSMKX2oFn9/f7VDID35+gLLlsmU78WLgXr1gHfeUTsqoqJjY2ODNm3aYOHChahbt65BxyhQYlGvnmTtivLs7D0z06A4iJ7qt9+ABw8kcW3VSu1oiIioJGrZUkbHX3sNePddoHZtqRpFVFqkpaUhLS3N4NcXKLG4eDHn/pEjwIQJstgpJES27d0LfPMN8L//GRwH0RPlLjE7ZgyHpomIqPCMHCnToWbOBAYMAPbvB4yYGUJULO3fv1/nsaIoSE5OxvHjx1G9enWDj1ugxCJ3dYQ+faT7dteuOdvq1AF8fIAPPpBFT0SmtGaNJLeurvJHnoiIqDBNmwacOgXs2gWEh0tyUa6c2lERmc6+7H4R/9JoNLC3t0fdunXRwojuw3ov3j5xAqhSJe/2KlWAqCiD4yB6ouwSs6+8wiodRERU+KytpZR+o0bAmTNyUWvVKsDSUu3IiExj7NixhXJcvRvkBQYCU6YA6ek529LTZVtgoClDI5JkdfNmqUT2xhtqR0NERKWFuzuwYoX0TFq3DnjvPbUjIjKd1NRUPHz4MM/2hw8fGrXGQu/EYuZMYMMGwNsb6NBBbt7esm3mTIPjIMpXdonZ8HA2LCIioqLVoIEUDwGAL7+UErREJcGyZctw8uTJPNtPnTqFpUuXGnxcvROLJk2ACxeATz+VtRV16gCffSbbmjQxOA6iPO7eBebNk/ssMUtERGp48cWcsrPDh0sTPSJzFxcXBz8/vzzb/fz8cPXqVYOPq/caCwBwcABefdXg9yQqkDlzpMRsrVpAmzZqR0NERKXVp59KT6+1a6VIzcGDMlWKyFxlZmYiKysr3+2PHj0y+LgGJRZnzwLbtgE3bgCPxzRpksGxEGllZuZMg2KJWSIiUpOlJbBgARAcDMTEAL17y/o/a2u1IyMyTKVKlXDo0CF0zV3mFcDBgwfh5eVl8HH1Tix++QV4/XXAzQ2oWFH3hE+jYWJBprFunUyvc3EBBg5UOxoiIirtnJ2BlStl2veuXcDYscBPP6kdFZFh2rZtiz/++APXr19HlX/LvV68eBHx8fEYNGiQwcfVO7H49FNZU/H22wa/J9Ezff+9fB0+XKbeERERqc3fX0YuunWTgjV160qXbiJz4+vri+HDhyMyMhJRUVGwsrKCh4cHunfvjvLlyxt8XL0Tizt3pEkeUWGJjgY2bZISs6NGqR0NERFRjrAw4PPPgYkTZaruc88BLVuqHRWR/ipWrIhevXqZ9Jh6V4Xq0wfYuNGkMRDpyF5b0a0bkE/BAiIiIlW9/TbQrx+QkQH06gVcuaJ2RET6y8rKQlRUFHbu3ImdO3ciOjo63wXd+tB7xKJ6deCDD4B9+4DatYEyZXSff/NNo+KhUu7evZwSs/xZIiKi4kijkf4WZ84AR45IpajduwF7e7UjI3OQlZWF7du348SJE0hOToaTkxPq1q2LVq1aQfPv4mVFUbB9+3YcPnwYqamp8PHxQVhYmFHTlHJLTEzEggULcP/+fe0xd+/ejbJly2LAgAFwdXU16Lh6JxY//ww4OgI7dsgtN42GJ4NknDlzgJQUGVpu21btaIiIiPJnby+duRs1kuRi+HBZf8EqhvQskZGROHjwIHr06AF3d3fEx8dj5cqVsLW1RXBwsHaf/fv3o0ePHnBxccG2bdswf/58jBo1ClZWBhV11bFu3Tq4uLhg+PDhsLOzAwA8ePAAy5cvx/r16zFgwACDjqv3VKiLF598u3DBoBiIAEjp4unT5T5LzBIRUXHn6wssXQpYWQGLFgH/+5/aEZE5iI2Nhb+/P2rWrIly5cohKCgI1apV0zamUxQF+/fvR6tWrRAQEAAPDw/06NEDSUlJOH36tEliuHz5Mjp06KBNKgDA3t4e7du3x6VLlww+rt6JBVFhWb8eOHcOKFcOMKLSGRERUZFp1Qr44Qe5P3GiNNGj0ikpKQn379/X3tLS0vLdz8fHBxcvXsTt27cBANeuXcOVK1dQvXp1AMDdu3eRnJyMqlWral9ja2sLb29vxMbGmiRWS0tLpKen59menp4OS0tLg49r0FhKXBzw99+yWOnxmL791uBYqJRjiVkiIjJHr70GHD0KzJoFDBgA7N8vpWmpdAkKCtJ5PHnyZHz44Yd59mvRogXS0tLw448/wsLCAllZWWjXrh3q1KkDAEhOTgYAODx2MuTg4ICUlBSTxFqzZk2sWrUK3bt3R6VKlQAAV69exZo1a+BvxA+v3onFli1A9+5A1arA6dNArVrApUuAogANGhgcB5VyMTHAhg0y/emNN9SOhoiISD/ffw+cOiWLuMPDJblwdlY7KipKUVFR2pN0ALCxscl3v1OnTuHEiRPo1asXKlSogGvXrmHDhg1wcnJCvXr1iiTWLl26YMWKFfj111+1IxRZWVnw9/dH586dDT6u3onFxInAhAnARx8BTk7AsmWAu7t0RzYiDirlcpeYzTXyR0REZBasrWW9RePGcrFs4EDp1G3ErBIyM05OTihbtuwz99u0aROaN2+OWrVqAQA8PDxw79497N69G/Xq1YOjoyMAICUlBU5OTtrXpaSkwMPDwySx2tra4sUXX8Tt27dx69YtAECFChUMrgaVTe81FtHRwJAhct/KCnj4UKpEffwx8OWXRsVCpdT9+8DcuXJ/zBhVQyEiIjKYhwewfDlgawusWSPl+Yke9+jRI21Z2WwajQaKogAAypUrB0dHR1zIVRUpLS0NcXFx8PHxMWks5cuXh7+/P/z9/Y1OKgADRiwcHHLWVXh6AufPS2lQAPg34SHSy9y5QHIyEBgItG+vdjRERESGa9gQ+PVXGbGYMgWoW1ea6RFlq1mzJnbt2gVnZ2e4u7sjISEB+/bt006D0mg0CA4Oxq5du1C+fHmUK1cO27Ztg5OTEwICAgx+3w0bNhR439DQUIPeQ+/EomlTmT8YGAh07Qr85z/AiRNARIQ8R6SPrKycaVAsMUtERCXBgAHAsWNSfvall4CaNYH69dWOioqLLl26YNu2bVi7dq12ulPDhg3RunVr7T7NmzfHo0ePsGrVKqSmpsLX1xeDBg0yqofFtWvXdB4nJCQgKytL2yDv9u3bsLCwgKenp8HvoXd0334rV5cBWWeRnAwsXgzUqMGKUKS/DRuAs2dlgdvgwWpHQ0REZBqffw4cPy6l1Hv0AP75R9akEtnY2KBz585PXSSt0WjQtm1btDVht+ChQ4dq7+/duxfW1tbo0aOHtpfFw4cPsXLlSvj6+hr8HnqvsahaFfi3GhYcHICZM+UXZ9kyoHJlg+OgUiq79vfLL8taHSIiopLA0hJYuFAuvF65AvTunbdEP5Fa9u7di/bt2+s0yLOzs0O7du2wd+9eg49rUGLxbz8PHXfvspoP6efMGWDdOpn+NGqU2tEQERGZVrly0verbFlg1y5g3Di1IyISaWlpePDgQZ7tKSkp+TbOKyi9E4tLl4DMzLzb09KAfzuRExXI9OnyNSwMqFZN3ViIiIgKQ0AA8OefchHtp5+kiR6R2gICArBy5UpER0drO4VHRUXh77//RmBgoMHHLfAai7//zrm/YYNu05fMTGmc5+dncBxUyiQlAXPmyH2WmCUiopLs+eeBzz4D3n0XGD1aqmm2aKF2VFSaPf/889i4cSOWLVuGrKwsAICFhQXq16+Pjh07GnzcAicWPXrIV40GyLX2AwBQpowkFd98Y3AcVMrMmyfJRUAAYMTPLxERkVl45x2pFLV4MdCrF3DwIGDilgREBVamTBmEhYWhY8eOuHPnDgDAxcUF1tbWRh23wInFv8kMqlSRygZubka9L5ViWVk5i7ZHj2aJWSIiKvk0GulvERMDHD0qF2x37QLs7dWOjEoza2trk3XzBgxYY3HxYt6k4u5dE0VDpcKmTbJwu2zZnC7uREREJZ2DA7BihZxHHT4MjBgB/NtsmahE0Dux+PJLGcbL1qcP4OoKVKokQ3xEz/L99/L1pZcAJyd1YyEiIipKlSsDS5cCVlbAggXA11+rHRGR6eidWMycmTMncNMmYPNmaf7SpQvw3/8aFsT06bJGw9YWCA4GDhwo2OsWLZKhxez1H1T8nTuXU2J29Gi1oyEiIip6rVsD06bJ/bfflvMoopJA78Ti2rWcxGL1aqBvX6BTJ+D//k/WXuhr8WJg/Hhg8mQZFqxbFwgNBW7cePrrLl0CJkwAWrbU/z1JPdOny7Bvly5A9epqR0NERKSO11/PmQr14osyRZioMM2aNQsPHz4EAOzYsQOPHj0y+XvonVi4uACxsXJ//XqgQwe5ryj597d4lm+/lV+sl14CgoJkRMTeHvjttye/JjMTGDgQ+OijZzflS0tL09bnvX//PpKSkvQPkkwiOTnnc33zTXVjISIiUpNGA/z4I9C8OXDvHhAeLl+JCsutW7e0ycSOHTuMaoT3JAWuCpWtZ09gwABpUX/7tlx5BoAjR/S/Ap2eDhw6BEycmLPNwkKSlad1E//4Y8DdHRg+XCoqPM2UKVPw0Ucf6RcYFYrffwfu3wdq1mSJWSIiImtrYNkyoFEj4PRpuWi6ciVgaal2ZFQSVaxYEStXroSPjw8URcGePXueWF62devWBr2H3iMW330nc+ODgmSNhaOjbE9IAN54Q79j3bolow+PV7ny8JApV/nZvVvKtf3yS8HeY+LEibh37572FhUVpV+QZBKKklNidswYSSCJiIhKOw8PYPlyWWe6Zg0waZLaEVFJFR4eDjs7O5w9exYajQbnzp3D6dOn870ZSu8RizJlZG3D4956y+AYCiwpCRg8WJKKgvbRsLGxgY2Njfbx/fv3Cyk6eprNm+VqjJNT3gaLREREpVmjRsDs2cCgQcDnnwN16gD9+qkdFZU0bm5u6N27NwDgo48+wpAhQ+Dg4GDS99A7sTAlNzcZ7rt+XXf79etAxYp59z9/XhZtd+uWsy27cZ+VlTSdqVat0MIlI7DELBER0ZMNHChl+7/6Sv6v9PcH6tVTOyoqqSZPnlwox1U1sbC2Bho2BLZsySkZm5Ulj/MrRRoQAJw4obvt/fdlJGPatJxqVVS8nD8vw7sAMGqUurEQEREVV1OmyHnO+vVyXvTPP0CFCmpHRSVVYmIi9u3bh1u3bgEAKlSogODgYLi6uhp8TNVnuo8fL1Ob5s0DoqOl/FpKimTrgHRmzl7cbWsL1KqleytXTq6A16oliQoVP9klZjt3loXbRERElJelpTTNq1EDuHxZmhAXQkVQIpw7dw4zZsxAfHw8PDw84OHhgatXr2LGjBk4f/68wcdVdcQCkDmEN2/KYqVr12TYb/36nAXdV65woa85Y4lZIiKignNxkcpQwcHAjh2yhvXHH9WOikqaLVu2oGnTpuiQ3TfiX5s3b8bmzZtRzcC1BQadst+9K4uMJk4EEhNl2+HDwNWrBsWA0aMlM09LA/bvl1+mbNu3A3PnPvm1c+cCK1YY9r5U+P74Q+py16ghjQ+JiIjo6QIDgT//lF4X06cXvBImUUHdvHkT9evXz7O9fv36uHnzpsHH1TuxOH5cprN8+SXw9deSZABARIRuPwqi3CVmR4/myBMREVFBdesGfPKJ3B81CoiMVDceKlkcHBxwLZ/eDteuXTOqUpTep3rjxwPDhgFnz8qah2xduwI7dxocB5VAW7bIuhlHR/mZISIiooJ7992cdRa9egGxsWpHRCVFgwYNsHr1auzevRuXL1/G5cuXsXv3bqxevRoNGjQw+Lh6r7H45x9g1qy82ytVenJTOyqdskcrhg0DypZVNRQiIiKzo9EAc+ZIOf3jx4EXXgB27QLs7NSOjMxdq1atYG1tjb1792LLli0AACcnJ7Ru3RrBudck6EnvxMLGBsivx9yZMyyJRjkuXABWrZL7+ZUOJiIiomdzcJDF3I0aAYcOASNGyPpFjUbtyMicaTQahISEICQkBGlpaQCg01DaUHpPhereHfj445zyZxqNVG56+20ZpiMCgBkzZI1FaKg0+SEiIiLD+PkBS5dKOdo//wS++UbtiKgksbGxMUlSARiQWHzzjZQQdXcHHj4EWrcGqleXXhKffWaSmMjMpaQAv/4q98eMUTcWIiKikqBNG2kGDMjF3PXrVQ2HKF96T4VydgY2bQJ275b5fsnJQIMGwGNlcKkUmz9fqoVVqwZ06aJ2NERERCXDG28AR49Kyf8XXwQOHGDjWSpeDG6Q16KF3IhyY4lZIiKiwqHRSLO8qChgzx6gRw9g3z4WSKHiQ+/E4vvv89+u0Uj52erVgVatZB4glT7btgGnTslis5deUjsaIiKiksXGBli2TBZzR0cDgwZJo2BeyKOCyszMxJ9//omwsDCUL1/epMfWO7H47jvg5k3gwQNpOw8Ad+4A9vbSr+DGDaBqVTnB9PExaaxkBrJHK4YOlWlzREREZFoVK0oy0bKlVGCcPDmnmR7Rs1haWuL69euFcmy989vPPwcaN5YGebdvy+3MGSA4WBYVXbkiP/BvvVUY4VJxdukS8Pffcp8lZomIiApPo0bAL7/I/U8/Bf76S914yLzUrl0bR44cMflx9R6xeP99GYKrVi1nW/XqwNdfS7nZCxeA//2PpWdLoxkzgKwsoGNHIDBQ7WiIiIhKtkGDZDH3N99IM9qaNYG6ddWOisxBVlYWDh48iAsXLsDT0xPW1tY6z4eGhhp0XL0Ti4QEICMj7/aMjJzO215eQFKSQfGQmXrwQKpUAMCbb6obCxERUWnxxRfAiRPAxo1AeDhw8CDg5qZ2VFTc3bx5E56engCAxMREkx1X78SibVtg5Eg5iaxfX7YdOQK8/jrQrp08PnECqFLFZDGSGfjzT1lrU7UqS8wSEREVFSsrYNEioEkT4Nw5oE8fSTLKlFE7MirOhg4dWijH1XuNxa+/Aq6uQMOGUpnAxkbm+bm65jRFc3RkV8jSRFFyqoWNGsWKYEREREXJxQVYuVLOv7ZvB8aPVzsiMheJiYk4d+4cHj16BABQFMWo4+k9YlGxojTIO31aFm0DgL+/3LK1bWtUTGRmduwATp6UymAvv6x2NERERKVPUJDMHggPl14XdesCr7yidlRUXD148ABLly7FxYsXodFoMGbMGLi4uODvv/+Gra2twWssDK56HBAAdO8ut9xJBZU+2aMVQ4YA5cqpGgoREVGp1b17TtnZN96QJnpE+dmwYQMsLCzw1ltvoUyueXPPPfcczp8/b/BxDeq8HRcnZUWvXAHS03Wf+/Zbg2MhM3T5sgy/AsCYMerGQkREVNq99x5w7BiwdCnQs6cs5vb2VjsqKm7Onz+PQYMGoexjbdvLly+Pu3fvGnxcvROLLVskI65aVaZD1aol/QsUBWjQwOA4yExll5ht316GYYmIiEg9Gg0wZ45MVz9+HHjhBWDnTsDOTu3IqDh59OiRzkhFtocPH8LKyqBxBwAGJBYTJwITJgAffQQ4OUlPC3d3YOBAoHNng+MgM8QSs0RERMWPo6N05m7cWEYsXn0V+P13STqoeLh//z42b96sXTjt6uqK8PBweHl5AZBF1Nu3b8fhw4eRmpoKHx8fhIWFoXz58iZ5f19fXxw7dgztsku6/vuekZGR8PPzM/i4eicW0dHAwoX/vtgKePhQfoA//lgWDL3+usGxkJlZsABITAT8/ICwMLWjISIiomxVqkg37o4dgfnzpUUAq0UVDw8fPsRvv/2GKlWqYODAgbC3t0diYiJsbW21+0RGRmL//v3o0aMHXFxcsG3bNsyfPx+jRo0yakQhW8eOHfH7778jISEBmZmZ2Lx5M27cuIGHDx/iZSMq8ei9eNvBIWddhacnkHt9x61bBsdBZkZRgB9+kPujR7PELBERUXHTti3w3Xdy/7//lf4WpL7IyEg4OzsjPDwclSpVgouLC6pVqwZXV1cAMnKwf/9+tGrVCgEBAfDw8ECPHj2QlJSE06dPmyQGd3d3jB49Gj4+PvD390d6ejoCAwMxcuRIbRyG0DvladoU2L0bCAwEunYF/vMfaYgXESHPUemwc6fM3WSJWSIiouJr9Gjg6FHgt9+Afv2Af/4BqldXO6qSKSkpCffv39c+trGxgY2NTZ79YmJiUK1aNfz111+4dOkSypYti0aNGqFhw4YAgLt37yI5ORlVq1bVvsbW1hbe3t6IjY1FrVq1TBKvra0tWrVqZZJjZdM7sfj2WyA5We5/9JHcX7wYqFGDFaFKk+zRisGDpTEPERERFT8ajRRaiYoC9u2TAjz79gGPFQMiEwh6rIrN5MmT8eGHH+bZ786dOzh48CBCQkLQokULxMfHY/369bC0tES9evWQ/O+JtoODg87rHBwckJKSYrJ4Hz58iCNHjuDmzZsAgAoVKqB+/fqwM2Klv16JRWamlJqtU0ceOzgAM2ca/N5kpq5cAZYvl/ujR6sbCxERET2djY3MLGnUSNbKDh4s/49bGNzNjPITFRWFSpUqaR/nN1oByFQnLy8vtG/fHgDg6emJGzdu4NChQ6hXr15RhIrLly9j4cKFsLGx0S4YP3DgAHbu3In+/fujcuXKBh1Xr8TC0hLo1El+KNkIrfT66ScpMduunZQbJiIiouLN01OSiVatpBfZhx9K4R0yHScnpzx9IZ60X4UKFXS2ubm5ITo6GgDg6OgIAEhJSYGTk5N2n5SUFHh4eJgk1rVr1+K5555DWFgYLP7NMLOysrBmzRqsXbsWrxtYjUnvXLVWLeDCBYPei0qAhw+BX36R+2yIR0REZD6aNAF+/lnuf/KJNNGjoufj44Pbt2/rbLt9+zacnZ0BAOXKlYOjoyMu5DrhTktLQ1xcHHx8fEwSQ2JiIkJCQrRJBQBYWFggJCQEiYmJBh9X78Ti00+lj8Xq1UBCAnD/vu6NSraFC4Hbt4HKlYFu3dSOhoiIiPQxZEhO2dmhQ6UQCxWtpk2bIi4uDrt27UJiYiJOnDiBw4cPo3HjxgAAjUaD4OBg7Nq1CzExMbh+/TqWL18OJycnBAQEmCQGT09P3MqnnOutW7eMGhXRe/F2167ytXt33UYriiKPMzMNjoWKudwlZkeNYolZIiIic/Tll1LRc9Mm6UH2zz+Am5vaUZUelSpVQr9+/bBlyxbs2LEDLi4uCA0NRZ3sRcwAmjdvjkePHmHVqlVITU2Fr68vBg0aZFQPi+vXr2vvN2nSBOvXr0diYiK8vb0BAHFxcfjnn3+0az8MoXd027YZ/F5k5nbvlpJ1dnbA8OFqR0NERESGsLICFi2SqVHnzwN9+wIbNgBlyqgdWelRs2ZN1KxZ84nPazQatG3bFm3btjXZe86cORMajQaKomi3bdq0Kc9+ERERBpe01TuxaN3aoPehEiB7tGLQIMCI3ilERESkMldXYOVK6UG2bZv0Jfv+e7WjosI0duzYQn8Pg8ZTdu0CZs2SRdx//QVUqgT88Ye0j2/RwtQhUnEQGyul6gAu2iYiIioJnnsOmD8f6NFDLh7Wq8emtyVZuSIo6ar34u1ly4DQUJkOc/gwkJYm2+/dAz7/3NThUXExc6asn2nTBqhdW+1oiIiIyBTCw6XhMQC8/jqwd6+68VDRSUpKwqlTp3DgwAHs379f52YovUcsPv1UTjKHDJH5edmaN5fnqORJTc0pT8fRCiIiopLl/feBY8dkZkLPnsDBgzIbhUquo0ePYvXq1bC0tISdnR00uSsyAQgODjbouHonFjEx0lzlcc7OwN27BsVAxdyiRcCtW4Cvr1QDIyIiopLDwgKYNw84cwY4eRJ44QVg507A1lbtyKiwbNu2Da1atULLli3zJBXG0HsqVMWKwLlzebfv3g1UrWqKkKg4UZScxVxvvCGVJIiIiKhkcXSUxdyurlJ+9tVX5RyASqZHjx6hVq1aJk0qAAMSixEjgLFjgf37pW9FfDzw55/SNM/A7t9UjO3ZAxw5IlctXnlF7WiIiIiosFStCixZIn2q/vgDmDpV7YiosNSvXx9RUVEmP67e15/feQfIygLatwcePJBpUTY2klhw/n3Jkz1aMXAgUL68urEQERFR4WrfHvj2W7mIPGECUKsW0LGj2lGRqbVv3x4LFy7EuXPn4O7uDsvHuh6HhoYadFy9EwuNBnjvPeC//5UpUcnJQFCQDKFRyXL7tlQBA5g0EhERlRZjxkhD3DlzgH79gAMHgOrV1Y6KTGn37t04d+4c3NzccOPGDZNNidI7sZg/XyoG2NtLQkEl17p1UmK2VSugbl21oyEiIqKioNEAP/0EREcD+/ZJSdp9+wAnJ7UjI1PZu3cvwsPDUa9ePZMeV+81Fm+9Bbi7AwMGAGvXyoknlTyPHgEbNsj9N99UNxYiIiIqWjY2Un7WywuIigIGD5ap8FQyWFpawsfHx+TH1TuxSEiQ8qMaDdC3L+DpCYwaJYt8qeTYtUuaHvr4yJUKIiIiKl08PYHlyyXJWLkyp5Eemb/g4GAcOHDA5MfVeyqUlRXw/PNye/BAfuAWLADatgW8vYHz500eIxUxRQFWr5b7LDFLRERUejVpIk1yhw4FPv5Ypkb37Kl2VGSs+Ph4XLx4EWfOnIG7uzssLHTHGvr162fQcY06ZbS3B0JDgTt3gMuXZS4emb+YGFmYX6YMS8wSERGVdkOGSOn5qVPlfo0aQO3aakdFxrC1tUVgYKDJj2tQYpE9UvHnn8CWLTJdpn9/YOlSU4dHasgerWjTBnBzUzUUIiIiKga++go4cULO+8LDpYkey9Cbr/BCmueu9xqLF1+UxdtvvSWNVLZvl6vbn3wCBAQUQoRUpBITgchIuf/88+rGQkRERMWDlRWweLGc+128KOtsMzLUjoqKG71HLCwtpStjaKjcz+3kSWmkQuYru8Tsc88BVaqoHQ0REREVF+XLyyLupk2BrVulgR67c5unadOmPfX5sWPHGnRcvROLP//UfZyUBCxcCMyeDRw6xPKz5uzRI2D9ernP0QoiIiJ6XK1awB9/yALuadNkMfdLL6kdFekrODhY53FWVhauXbuGc+fOoVmzZgYf1+DF2zt3Ar/+Kp2ZvbzkB2z6dIPjoGJg924pMevmJlcjiIiIiB73wgvAhx/K7bXXgMBAnjeYm6ZP+MAOHDiAhIQEg4+r1xqLa9eAL76QagB9+gBlywJpacCKFbK9cWOD4yCVKQqwapXc79Il7zQ3IiIiomwffCAJRnq6XFyOj1c7IjKFGjVqICoqyuDXFzix6NYN8PcHjh+X+XTx8cAPPxj8vlTMnDmTU2I2NFTtaIiIiKg4s7AA5s2TqVEJCZJkpKaqHRUZKyoqCnZ2dga/vsBTodatA958E3j9dRmxoJIlu8Rsq1YyEkVERET0NE5Ospi7cWPgwAGZFjVnDqDRqB0ZPcusWbPybEtOTkZKSgrCwsIMPm6BE4vdu2VNRcOGMpdu8GApPUvm784d+XwBLtomIiKigqtaNada6Lx5QL16wLhxakdFz+Lv76/zWKPRwMHBAX5+fnAzoolZgROLpk3lNnWq1DH+7Tdg/HggKwvYtEma5Dk5GRwHqWj9eqnmFRgIVKumdjRERERkTtq3B775RhKKCRNkelSHDmpHRU/Tpk2bQjmu3g3yHByAl1+WK9wnTgD/+Y8s3HZ3B7p3L4wQqTBlZMg0N4CjFURERGSYN98Ehg6VC5V9+wLnz6sdEanB4HKzgCzm/t//gClTpKLQb7+ZKiwqKpGRwN27gKsrYETZYiIiIirFNBpg5kwgOlrWW4SHA3v3cjZLcfPRRx9BU4BFMJMmTTLo+EYlFtksLYEePeRG5iW7xGzXriwxS0RERIaztQWWLwcaNQJOnZIRjKVLpYIUFQ/9+vV74nNxcXHYv38/FEUx+PgmSSzIPJ05IzcrK5aYJSIiIuN5eQEREUDr1pJkfPIJMHmy2lFRtoCAgDzbbt26hS1btiAmJgZ16tQxav0FE4tSLHeJWWdndWMhIiKikqFpU5kW9fLL0p27Th3pc0HFS1JSErZt24Zjx46hevXqeO211+Du7m7UMZlYlFK5S8x266ZuLERERFSyvPQScOwYMG2atCjYuxeoXVvtqAgAUlNTsWvXLhw4cAAVK1bEkCFDULlyZZMcm4lFKbVhg1SECghgiVkiIiIyva+/lgqiW7fKYu5//gHKl1c7qtItMjISkZGRcHR0RK9evfKdGmUMJhalUO4SsxytICIiosJgZSXN8xo3Bi5eBPr1A9askdGLhATA0xNo2ZLFY4rS5s2bUaZMGbi6uuLYsWM4duxYvvs9bZH30zCxKIX27JGpUCwxS0RERIWpfHlg5UogJATYsgVwcwOSk3Oe9/aW6VI9e6oXY2lSt27dApWbNRQTi1Iou8Rsly68SkBERESFq3Zt4I03gK++0k0qAODqVaB3bylLy+Si8PUo5N4QrCxcypw9C8TEsMQsERERFY3MTGDhwvyfy26ZMG6c7EfmjYlFKZNdYrZlS6BcOVVDISIiolJg1y4gLu7JzysKEBsr+5F5Y2JRity9m/NL+/zzqoZCREREpURCgmn3o+KLiUUpkl1i1t8fqFFD7WiIiIioNPD0NO1+VHwxsSglMjNzSsxytIKIiIiKSsuWUv3pScWINBrAx0f2I/PGqlClxJ49QGIi4OICNG+udjRERERUWlhaSknZ3r0lichesA3kJBtTp5beSpW7d+/Gli1bEBwcjM6dOwMAMjIysGHDBpw6dQoZGRmoXr06unbtCkdHR5WjfTqOWJQS2Yu2u3SRilBERERERaVnTykpW6mS7nZv79Jdavbq1as4dOgQPDw8dLavX78eZ86cQZ8+fTBs2DAkJSVhyZIlKkVZcEwsSoHz54HoaJaYJSIiIvX07AlcugRs2wYsWCBfL14sOUlFUlIS7t+/r72lpaU9df/09HRERESgW7dusLW11W5PTU3FkSNHEBoaiipVqsDLywvh4eGIjY1F3NPKaxUDTCxKgeyGeC1ayFQoIiIiIjVYWgJt2gD9+8vXkjT9KSgoCM7OztrblClTnrr/2rVrUaNGDVStWlVne0JCArKysnS2u7m5wdnZGbGxsYUSu6lwUkwJd+8esHOn3OeibSIiIqLCERUVhUq55nrZ2Ng8cd+TJ08iISEBI0aMyPNccnIyLC0tdUYxAMDBwQHJj7cuL2aYWJRw2SVma9aUGxERERGZnpOTE8qWLfvM/e7du4f169dj8ODBsCphC19L1ndDOjIzgbVr5T5HK4iIiIjUl5CQgJSUFMyaNUu7TVEUXL58GQcOHMCgQYOQmZmJ1NRUnVGLlJSUYl8ViolFCbZ3r5SYLVeOJWaJiIiIioMqVarg9ddf19m2cuVKuLm5oXnz5ihbtiwsLCxw4cIFBAUFAQBu3bqFe/fuwcfHR42QC4yJRQmWvWi7c2egTBl1YyEiIiIiWXvh7u6us61MmTKws7PTbq9fvz42btwIOzs72NjYYN26dfD29oa3t7caIRdYsagKNX064OcH2NoCwcHAgQNP3veXX6Qzo4uL3Dp0ePr+pdWFC1Ji1tJSelcQERERkXno3LkzatSogSVLlmDu3LlwdHREv3791A7rmVQfsVi8GBg/Hpg5U5KKqVOl10JMDPBYMgcA2L5dSpQ1ayaJyJdfAp06AadO5W26UpplN8Rr3pwlZomIiIiKs2HDhuk8trKyQlhYGMLCwtQJyECqj1h8+y0wYgTw0ktAUJAkGPb2wG+/5b//n38Cb7wB1KsHBAQAs2cDWVnAli1FGnaxdv8+sGOH3O/WTd1YiIiIiKh0UDWxSE8HDh2S6UzZLCzk8d69BTvGgwfAo0eAq2v+z6elpel0QUxKSjI+8GJu40b5N6lenSVmiYiIiKhoqJpY3LolJVE9PHS3e3gA164V7Bhvvw14eekmJ7lNmTJFpwti9ur6kip3idlu3QCNRt14iIiIiKh0UH0qlDG++AJYtAhYvlzWW+Rn4sSJuHfvnvYWFRVVtEEWsf37JWFzdgZatFA7GiIiIiIqLVRdvO3mJlWLrl/X3X79OlCx4tNf+/XXklhs3gzUqfPk/WxsbHRaqt+/f9+IiIs/lpglIiIiIjWoOmJhbQ00bKi78Dp7IXZIyJNf97//AZ98AqxfDzRqVPhxmouLF6U6lqWlJBZEREREREVF9XKz48cDQ4dKgtCkiZSbTUmRKlEAMGSIlJGdMkUef/klMGkSsGCB9L7IXovh6Ci30iy7xGyzZkD58urGQkRERESli+qJRb9+wM2bkixcuyZlZNevz1nQfeWKVIrK9tNPUk2qd2/d40yeDHz4YVFFXfywxCwRERERqUn1xAIARo+WW362b9d9fOlSYUdjXrKyZPrT+vWScFWtCvj7qx0VEREREZU2xSKxIMPs3Qv88otUgcp24wawb9/T16gQEREREZmaWZebLc327pWqWLmTCkDWp3zxRcEbDBIRERERmQITCzOUlSUjFYqS97nsbb/8IvsRERERERUFJhZm6NSpvCMVuSmKPH/qVNHFRERERESlGxMLM3Tnjmn3IyIiIiIyFhMLM+TiYtr9iIiIiIiMxcTCDD33HODmBmg0+T+v0cjzzz1XtHERERERUenFxMIMWVgAI0bI/ceTi+zHI0boNhYkIiIiIipMPPU0UyEhwDvvAOXL624vX162s48FERERERUlNsgzYyEhQHCwVH+6c0fWVDz3HEcqiIiIiKjoMbEwcxYWQO3aakdBRERERKUdr20TEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRrNQOgIiIiIiotNi1axdOnz6NW7duwcrKCj4+PujQoQPc3Ny0+2RkZGDDhg04deoUMjIyUL16dXTt2hWOjo4qRv5sHLEgIiIiIioily9fRuPGjTF8+HAMHjwYWVlZmD9/PtLT07X7rF+/HmfOnEGfPn0wbNgwJCUlYcmSJSpGXTBMLIiIiIiIjJSUlIT79+9rb2lpafnuN2jQINSrVw/u7u6oWLEiwsPDce/ePSQkJAAAUlNTceTIEYSGhqJKlSrw8vJCeHg4YmNjERcXV5Tfkt6YWBARERERGSkoKAjOzs7a25QpUwr0uuwExM7ODgCQkJCArKwsVK1aVbuPm5sbnJ2dERsba/rATYhrLIiIiIiIjBQVFYVKlSppH9vY2DzzNYqiYP369fDx8YG7uzsAIDk5GZaWlrC1tdXZ18HBAcnJyaYN2sSYWBARERERGcnJyQlly5bV6zVr1qzBjRs38PLLLxdSVEWLU6GIiIiIiIrY2rVrcfbsWQwdOlQnIXF0dERmZiZSU1N19k9JSWFVKCIiIiIiEoqiYO3atTh9+jSGDBkCFxcXnec9PT1hYWGBCxcuaLfdunUL9+7dg4+PT1GHqxdOhSIiIiIiKiJr167FiRMn8OKLL8LGxka7bsLGxgZlypSBra0t6tevj40bN8LOzg42NjZYt24dvL294e3trXL0T8fEgoiIiIioiBw8eBAAMG/ePJ3t4eHhqFevHgCgc+fO2LBhA5YsWYLMzExUq1YNYWFhRR2q3phYEBEREREVkcmTJz9zHysrK4SFhZlFMpEb11gQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRrNQOgIiIiEqumJgYtUPQi7+/v9ohEJktjlgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRrNQOgIiIiIiKn5iYGLVD0Ju/v7/aIZRqxWLEYvp0wM8PsLUFgoOBAweevv9ffwEBAbJ/7drA2rVFEiYRERERkUkcOHAAU6dOxaefforZs2fj6tWraodkNNUTi8WLgfHjgcmTgcOHgbp1gdBQ4MaN/Pffswfo3x8YPhw4cgTo0UNuJ08WZdRERERERIY5efIkNm7ciNatW2PkyJHw8PDA/PnzkZKSonZoRlE9sfj2W2DECOCll4CgIGDmTMDeHvjtt/z3nzYN6NwZ+O9/gcBA4JNPgAYNgB9/LNq4iYiIiIgMsW/fPjRo0AD169dHhQoV8Pzzz6NMmTI4cuSI2qEZRdU1FunpwKFDwMSJOdssLIAOHYC9e/N/zd69MsKRW2gosGJF/vunpaUhLS1N+/jevXsAgISEBCMiN8yNJw3DFGMODg5qh1Bs8PMzb+b2+fGzy2Funx3Azy83c/v8+NnlMLfPDlDn88s+p7x37x7Kli2r3W5jYwMbG5s8+2dmZiI+Ph4tWrTQbtNoNKhatSri4uIKP+BCpGpicesWkJkJeHjobvfwAE6fzv81167lv/+1a/nvP2XKFHz00Ud5tjdp0sSAiImIiIiI8qpVq5bO48mTJ+PDDz/Ms9+DBw+gKEqeJMjBwQG3bt0qzBALXYmvCjVx4kSMzzXEkZGRgejoaPj4+MDCQvWZYCaRlJSEoKAgREVFwcnJSe1wSA/87MwbPz/zxs/PfPGzM28l7fPLysrClStXEBQUBCurnFPr/EYrSjpVEws3N8DSErh+XXf79etAxYr5v6ZiRf32z28Yqnnz5gZGXDzdv38fAFCpUiWdITgq/vjZmTd+fuaNn5/54mdn3kri5+fr61vgfe3t7aHRaPIs1E5JSYGjo6OpQytSql6yt7YGGjYEtmzJ2ZaVJY9DQvJ/TUiI7v4AsGnTk/cnIiIiIiouLC0t4eXlhQsXLmi3KYqCCxcuwNvbW8XIjKf6VKjx44GhQ4FGjYAmTYCpU4GUFKkSBQBDhgCVKgFTpsjjsWOB1q2Bb74BwsKARYuAgweBn39W7VsgIiIiIiqwpk2bYsWKFfDy8kKlSpWwb98+PHr0CPXq1VM7NKOonlj06wfcvAlMmiQLsOvVA9avz1mgfeWKVIrK1qwZsGAB8P77wLvvAjVqSEWox9bLlCo2NjaYPHlyqZzLZ+742Zk3fn7mjZ+f+eJnZ974+clC7wcPHmD79u1ITk5GxYoVMXDgQLOfCqVRFEVROwgiIiIiIjJvJaMsEhERERERqYqJBRERERERGY2JBRERERERGY2JBRERERERGY2JhZmbPn06/Pz8YGtri+DgYBw4cEDtkKgAdu7ciW7dusHLywsajQYrVqxQOyTSw5QpU9C4cWM4OTnB3d0dPXr0QExMjNphUQH89NNPqFOnDsqWLYuyZcsiJCQE69atUzssMsAXX3wBjUaDcePGqR0KFcCHH34IjUajcwsICFA7LDIxJhZmbPHixRg/fjwmT56Mw4cPo27duggNDcWNGzfUDo2eISUlBXXr1sX06dPVDoUMsGPHDowaNQr79u3Dpk2b8OjRI3Tq1ClPF1Uqfry9vfHFF1/g0KFDOHjwINq1a4fw8HCcOnVK7dBID//88w9mzZqFOnXqqB0K6eG5555DQkKC9rZ79261QyITY7lZMxYcHIzGjRvjxx9/BABkZWXBx8cHY8aMwTvvvKNydFRQGo0Gy5cvR48ePdQOhQx08+ZNuLu7Y8eOHWjVqpXa4ZCeXF1d8dVXX2H48OFqh0IFkJycjAYNGmDGjBn49NNPUa9ePUydOlXtsOgZPvzwQ6xYsQJHjx5VOxQqRByxMFPp6ek4dOgQOnTooN1mYWGBDh06YO/evSpGRlT63Lt3D4CcoJL5yMzMxKJFi5CSkoKQkBC1w6ECGjVqFMLCwnT+/yPzcPbsWXh5eaFq1aoYOHAgrly5onZIZGKqd94mw9y6dQuZmZnwyG5R/i8PDw+cPn1apaiISp+srCyMGzcOzZs3R61atdQOhwrgxIkTCAkJQWpqKhwdHbF8+XIEBQWpHRYVwKJFi3D48GH8888/aodCegoODsbcuXPh7++PhIQEfPTRR2jZsiVOnjwJJycntcMjE2FiQURkhFGjRuHkyZOcK2xG/P39cfToUdy7dw9Lly7F0KFDsWPHDiYXxVxsbCzGjh2LTZs2wdbWVu1wSE9dunTR3q9Tpw6Cg4NRuXJlLFmyhNMQSxAmFmbKzc0NlpaWuH79us7269evo2LFiipFRVS6jB49GqtXr8bOnTvh7e2tdjhUQNbW1qhevToAoGHDhvjnn38wbdo0zJo1S+XI6GkOHTqEGzduoEGDBtptmZmZ2LlzJ3788UekpaXB0tJSxQhJH+XKlUPNmjVx7tw5tUMhE+IaCzNlbW2Nhg0bYsuWLdptWVlZ2LJlC+cKExUyRVEwevRoLF++HFu3bkWVKlXUDomMkJWVhbS0NLXDoGdo3749Tpw4gaNHj2pvjRo1wsCBA3H06FEmFWYmOTkZ58+fh6enp9qhkAlxxMKMjR8/HkOHDkWjRo3QpEkTTJ06FSkpKXjppZfUDo2eITk5WecqzcWLF3H06FG4urrC19dXxcioIEaNGoUFCxZg5cqVcHJywrVr1wAAzs7OsLOzUzk6epqJEyeiS5cu8PX1RVJSEhYsWIDt27djw4YNaodGz+Dk5JRnHZODgwPKly/P9U1mYMKECejWrRsqV66M+Ph4TJ48GZaWlujfv7/aoZEJMbEwY/369cPNmzcxadIkXLt2DfXq1cP69evzLOim4ufgwYNo27at9vH48eMBAEOHDsXcuXNViooK6qeffgIAtGnTRmf7nDlzMGzYsKIPiArsxo0bGDJkCBISEuDs7Iw6depgw4YN6Nixo9qhEZVocXFx6N+/P27fvo0KFSqgRYsW2LdvHypUqKB2aGRC7GNBRERERERG4xoLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhMLIiJS3ZYtWxAYGIjMzEy1Q9HSaDRYsWKF2mGoJj09HX5+fjh48KDaoRCRmWBiQUQ6hg0bBo1Gg9deey3Pc6NGjYJGo8GwYcOKPrBizM/PD1OnTtX7dW3atMG4ceNMHo85+r//+z+8//77sLS0VDuUUunDDz9EvXr1dLZZW1tjwoQJePvtt9UJiojMDhMLIsrDx8cHixYtwsOHD7XbUlNTsWDBAvj6+qoYGeUnPT1d7RCQmZmJrKwsg167e/dunD9/Hr169TJxVHk9evSo0N+jJBk4cCB2796NU6dOqR0KEZkBJhZElEeDBg3g4+ODiIgI7baIiAj4+vqifv36OvtmZWVhypQpqFKlCuzs7FC3bl0sXbpU+3xmZiaGDx+ufd7f3x/Tpk3TOcawYcPQo0cPfP311/D09ET58uUxatSop54Enj9/HuHh4fDw8ICjoyMaN26MzZs36+zj5+eHzz//HC+//DKcnJzg6+uLn3/+Wfv8pUuXoNFoEBERgbZt28Le3h5169bF3r17dY6zbNkyPPfcc7CxsYGfnx+++eYb7XNt2rTB5cuX8dZbb0Gj0UCj0QAAbt++jf79+6NSpUqwt7dH7dq1sXDhQp3veceOHZg2bZr2dZcuXQIA7NixA02aNIGNjQ08PT3xzjvvICMjQ+c9R48ejXHjxsHNzQ2hoaH5/htt374dTZo0gYODA8qVK4fmzZvj8uXL2udXrVqFxo0bw9bWFm5ubnjhhRe0z925cwdDhgyBi4sL7O3t0aVLF5w9e1b7/Ny5c1GuXDn8/fffCAoKgo2NDa5cuYK0tDRMmDABlSpVgoODA4KDg7F9+/Ynfo4AsGjRInTs2BG2trbabdlX0GfNmgUfHx/Y29ujb9++uHfvns5rZ8+ejcDAQNja2iIgIAAzZszQPpf9+S5evBitW7eGra0t/vzzz3xjOHv2LFq1agVbW1sEBQVh06ZNefY5ceIE2rVrBzs7O5QvXx6vvvoqkpOTdfb57bfftD8rnp6eGD16tE4sR48e1e579+5daDQa7b/P9u3bodFosGHDBtSvXx92dnZo164dbty4gXXr1iEwMBBly5bFgAED8ODBA+1xnvU7mH3cLVu2oFGjRrC3t0ezZs0QExMDQD7Ljz76CMeOHdP+LM6dOxcA4OLigubNm2PRokVP+viIiHIoRES5DB06VAkPD1e+/fZbpX379trt7du3V7777jslPDxcGTp0qHb7p59+qgQEBCjr169Xzp8/r8yZM0exsbFRtm/friiKoqSnpyuTJk1S/vnnH+XChQvK/PnzFXt7e2Xx4sU671m2bFnltddeU6Kjo5VVq1Yp9vb2ys8///zEOI8eParMnDlTOXHihHLmzBnl/fffV2xtbZXLly9r96lcubLi6uqqTJ8+XTl79qwyZcoUxcLCQjl9+rSiKIpy8eJFBYASEBCgrF69WomJiVF69+6tVK5cWXn06JGiKIpy8OBBxcLCQvn444+VmJgYZc6cOYqdnZ0yZ84cRVEU5fbt24q3t7fy8ccfKwkJCUpCQoKiKIoSFxenfPXVV8qRI0eU8+fPK99//71iaWmp7N+/X1EURbl7964SEhKijBgxQvu6jIwMJS4uTrG3t1feeOMNJTo6Wlm+fLni5uamTJ48Wft9tW7dWnF0dFT++9//KqdPn9Z+P7k9evRIcXZ2ViZMmKCcO3dOiYqKUubOnav991m9erViaWmpTJo0SYmKilKOHj2qfP7559rXd+/eXQkMDFR27typHD16VAkNDVWqV6+upKenK4qiKHPmzFHKlCmjNGvWTImMjFROnz6tpKSkKK+88orSrFkzZefOncq5c+eUr776SrGxsVHOnDnzxM+yTp06yhdffKGzbfLkyYqDg4PSrl075ciRI8qOHTuU6tWrKwMGDNDuM3/+fMXT01NZtmyZcuHCBWXZsmWKq6urMnfuXJ3P18/PT7tPfHx8nvfPzMxUatWqpbRv3145evSosmPHDqV+/foKAGX58uWKoihKcnKy4unpqfTs2VM5ceKEsmXLFqVKlSo6vwszZsxQbG1tlalTpyoxMTHKgQMHlO+++04nliNHjmj3v3PnjgJA2bZtm6IoirJt2zYFgNK0aVNl9+7dyuHDh5Xq1asrrVu3Vjp16qQcPnxY2blzp1K+fHmdf69n/Q5mHzc4OFjZvn27curUKaVly5ZKs2bNFEVRlAcPHij/+c9/lOeee077s/jgwQPt8d9++22ldevWT/z8iIiyMbEgIh3ZicWNGzcUGxsb5dKlS8qlS5cUW1tb5ebNmzqJRWpqqmJvb6/s2bNH5xjDhw9X+vfv/8T3GDVqlNKrVy+d96xcubKSkZGh3danTx+lX79+esX+3HPPKT/88IP2ceXKlZVBgwZpH2dlZSnu7u7KTz/9pChKzsne7NmztfucOnVKAaBER0criqIoAwYMUDp27KjzPv/973+VoKAgnffJPoF8mrCwMOU///mP9nHr1q2VsWPH6uzz7rvvKv7+/kpWVpZ22/Tp0xVHR0clMzNT+7r69es/9b1u376tANCeXD4uJCREGThwYL7PnTlzRgGgREZGarfdunVLsbOzU5YsWaIoiiQWAJSjR49q97l8+bJiaWmpXL16Ved47du3VyZOnPjEWJ2dnZXff/9dZ9vkyZMVS0tLJS4uTrtt3bp1ioWFhTZ5q1atmrJgwQKd133yySdKSEiIoig5n+/UqVOf+N6KoigbNmxQrKysdOJet26dTmLx888/Ky4uLkpycrJ2nzVr1igWFhbKtWvXFEVRFC8vL+W9997L9z30SSw2b96s3WfKlCkKAOX8+fPabSNHjlRCQ0MVRSnY72B+x12zZo0CQHn48KGiKPLvXbdu3XxjnzZtmuLn55fvc0REuVkV7fgIEZmLChUqICwsDHPnzoWiKAgLC4Obm5vOPufOncODBw/QsWNHne3p6ek6U6amT5+O3377DVeuXMHDhw+Rnp6eZ6Hoc889p7Nw19PTEydOnHhifMnJyfjwww+xZs0aJCQkICMjAw8fPsSVK1d09qtTp472vkajQcWKFXHjxo0n7uPp6QkAuHHjBgICAhAdHY3w8HCd/Zs3b46pU6ciMzPziYuNMzMz8fnnn2PJkiW4evUq0tPTkZaWBnt7+yd+TwAQHR2NkJAQ7ZSq7PdLTk5GXFycdo1Lw4YNn3ocV1dXDBs2DKGhoejYsSM6dOiAvn37ar+/o0ePYsSIEU+MwcrKCsHBwdpt5cuXh7+/P6Kjo7XbrK2tdf7tTpw4gczMTNSsWVPneGlpaShfvvwTY3348KHONKhsvr6+qFSpkvZxSEgIsrKyEBMTAycnJ5w/fx7Dhw/X+T4yMjLg7Oysc5xGjRo98b2zv18fHx94eXnpvNfj+9StWxcODg7abc2bN9fGo9FoEB8fj/bt2z/1vQoi97+ph4cH7O3tUbVqVZ1tBw4cAFDw38HHj5v75/xZ66bs7Ox0pl4RET0JEwsieqKXX35ZO0d8+vTpeZ7Pnl++Zs0anRNAALCxsQEg8+cnTJiAb775BiEhIXBycsJXX32F/fv36+xfpkwZnccajeapi4EnTJiATZs24euvv0b16tVhZ2eH3r1751nIXJDj5t4n+4Te0IXI2b766itMmzYNU6dORe3ateHg4IBx48aZbKF17hPcJ5kzZw7efPNNrF+/HosXL8b777+PTZs2oWnTprCzszM6Bjs7O50EKDk5GZaWljh06FCehMvR0fGJx3Fzc8OdO3f0eu/sn71ffvlFJwECkOe9C/JvZaxn/XtaWMiSRkVRtNuetIbo8Z/Hp/0MF+R38EnHBQr2c56YmIgKFSo8cz8iIiYWRPREnTt3Rnp6OjQaTb4LhHMv2m3dunW+x4iMjESzZs3wxhtvaLedP3/e6NgiIyMxbNgw7YLj5ORk7eJnUwoMDERkZGSe965Zs6b2BNba2jpP/4XIyEiEh4dj0KBBAOQE7syZMwgKCtLuk9/rAgMDsWzZMiiKoj35i4yMhJOTE7y9vfWOv379+qhfvz4mTpyIkJAQLFiwAE2bNkWdOnWwZcsWvPTSS/l+zxkZGdi/fz+aNWsGQBajx8TE6MSf33tlZmbixo0baNmypV4xRkVF5dl+5coVxMfHa0cS9u3bBwsLC/j7+8PDwwNeXl64cOECBg4cWOD3yk9gYCBiY2ORkJCgvZK/b9++PPvMnTsXKSkp2kQlMjJSG4+TkxP8/PywZcsWtG3bNs97ZJ+YJyQkaEcSci/kNlRBfgcLIr+fxWwnT57MM/pBRJQfVoUioieytLREdHQ0oqKi8p3y4+TkhAkTJuCtt97CvHnzcP78eRw+fBg//PAD5s2bBwCoUaMGDh48iA0bNuDMmTP44IMP8M8//xgdW40aNRAREYGjR4/i2LFjGDBggNGjDPn5z3/+gy1btuCTTz7BmTNnMG/ePPz444+YMGGCdh8/Pz/s3LkTV69exa1bt7Txbdq0CXv27EF0dDRGjhyJ69ev6xzbz88P+/fvx6VLl3Dr1i1kZWXhjTfeQGxsLMaMGYPTp09j5cqVmDx5MsaPH6+96l0QFy9exMSJE7F3715cvnwZGzduxNmzZxEYGAgAmDx5MhYuXIjJkycjOjoaJ06cwJdffqmNPTw8HCNGjMDu3btx7NgxDBo0CJUqVcozLSy3mjVrYuDAgRgyZAgiIiJw8eJFHDhwAFOmTMGaNWue+LrQ0FDs3r07z3ZbW1sMHToUx44dw65du/Dmm2+ib9++qFixIgDgo48+wpQpU/D999/jzJkzOHHiBObMmYNvv/22wP9OANChQwfUrFlT573ee+89nX0GDhyojefkyZPYtm0bxowZg8GDB8PDwwOAVLL65ptv8P333+Ps2bPa3wVARjSaNm2KL774AtHR0dixYwfef/99veLMT0F+BwvCz88PFy9exNGjR3Hr1i2kpaVpn9u1axc6depkdKxEVAqovMaDiIqZ7MXbT/J4VaisrCxl6tSpir+/v1KmTBmlQoUKSmhoqLJjxw5FUWRx6bBhwxRnZ2elXLlyyuuvv6688847OgtF83vPsWPHPrUSzcWLF5W2bdsqdnZ2io+Pj/Ljjz/mWQyd36LqunXraissFWRBraIoytKlS5WgoCClTJkyiq+vr/LVV1/pHHPv3r1KnTp1FBsbGyX7z+rt27eV8PBwxdHRUXF3d1fef/99ZciQITrfZ0xMjNK0aVPFzs5OAaBcvHhRURRF2b59u9K4cWPF2tpaqVixovL2229rq1QpSv6Lvh937do1pUePHoqnp6dibW2tVK5cWZk0aZJ2AbiiKMqyZcuUevXqKdbW1oqbm5vSs2dP7XOJiYnK4MGDFWdnZ8XOzk4JDQ3Vqew0Z84cxdnZOc/7ZlcB8/PzU8qUKaN4enoqL7zwgnL8+PEnxnr79m3F1tZWp7pV9mLiGTNmKF5eXoqtra3Su3dvJTExUee1f/75p/Z7cHFxUVq1aqVEREQoipL/5/skMTExSosWLRRra2ulZs2ayvr163UWbyuKohw/flxp27atYmtrq7i6uiojRoxQkpKSdI4zc+ZM7e+Cp6enMmbMGO1zUVFRSkhIiGJnZ6fUq1dP2bhxY76Lt+/cuaN9TX7/zo8vtH7W72B+xz1y5IjOz1xqaqrSq1cvpVy5cgoAbdWzPXv2KOXKldOpEkVE9CQaRck14ZOIiEgF//3vf3H//n3MmjULgFz9X7FihUmmC5Hh+vXrh7p16+Ldd99VOxQiMgOcCkVERKp77733ULly5UKZzkaGSU9PR+3atfHWW2+pHQoRmQmOWBARUbHDEQsiIvPDxIKIiIiIiIzGqVBERERERGQ0JhZERERERGQ0JhZERERERGQ0JhZERERERGQ0JhZERERERGQ0JhZERERERGQ0JhZERERERGQ0JhZERERERGS0/wfuev7jEgUougAAAABJRU5ErkJggg==", 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" ] @@ -601,23 +737,37 @@ "\n", "# Line plot for average std dev\n", "ax1.plot(bin_centers, avg_stds_per_bin, color='blue', marker='o', label='Avg Std Dev')\n", - "ax1.set_xlabel('Mean Annotator Score (per Document)')\n", - "ax1.set_ylabel('Average Standard Deviation', color='blue')\n", + "ax1.set_xlabel('Mean annotator score (per document)')\n", + "ax1.set_ylabel('Average standard deviation', color='blue')\n", "ax1.tick_params(axis='y', labelcolor='blue')\n", "ax1.set_ylim(0, max(avg_stds_per_bin) + 0.1)\n", "\n", "# Bar plot for support on secondary y-axis\n", "ax2 = ax1.twinx()\n", "ax2.bar(bin_centers, support_per_bin, width=0.4, alpha=0.3, color='gray', label='Support (Count)')\n", - "ax2.set_ylabel('Number of Documents per Bin', color='gray')\n", + "ax2.set_ylabel('Number of documents per bin', color='gray')\n", "ax2.tick_params(axis='y', labelcolor='gray')\n", "\n", "# Title and layout\n", - "plt.title('Disagreement vs. Mean Score with Support per Bin')\n", + "# plt.title('Disagreement vs. Mean Score with Support per Bin')\n", "fig.tight_layout()\n", + "plt.savefig(plot_path / f\"human_annotation_score_std_hist.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", + "\n", "plt.show()\n" ] }, + { + "cell_type": "code", + "execution_count": 92, + "id": "ff3b4355", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO\n", + "# * Add plot where x_axis is ground truth and the y_axis the standard deviation of the predictions\n", + "# * Could also plot the confusion matrix instead\n" + ] + }, { "cell_type": "markdown", "id": "197531d3", @@ -628,14 +778,61 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 93, "id": "c944d423", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'bg': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.16588711569468226,\n", + "{'bg': {'phi-4': {'metrics': {'Fleiss': 0.2502797242524014,\n", + " 'Cohen': 0.2581460372083022,\n", + " 'Spearman': 0.6311440245975249,\n", + " 'Kendall': 0.524629373412667,\n", + " 'Krippendorff': 0.5890210059887584,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.735812133072407,\n", + " 'TA-4.0': 0.8825831702544031,\n", + " 'Acc': 0.4187866927592955,\n", + " 'MAE': 0.8405088062622307,\n", + " 'MSE': 1.4927701674277016,\n", + " 'CA-0': 0.489247311827957,\n", + " 'CA-1': 0.32,\n", + " 'CA-2': 0.3113207547169811,\n", + " 'CA-3': 0.5288461538461539,\n", + " 'CA-4': 0.23076923076923078,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.3007767238307655,\n", + " 'Micro-F1': 0.4187866927592955,\n", + " 'F1-0_vs_rest': 0.6190476190476191,\n", + " 'F1-1_vs_rest': 0.2831858407079646,\n", + " 'F1-2_vs_rest': 0.32195121951219513,\n", + " 'F1-3_vs_rest': 0.48672566371681414,\n", + " 'F1-4_vs_rest': 0.09375,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8461538461538461,\n", + " 'Recall-0.5': 0.9476923076923077,\n", + " 'Precision-0.5': 0.7642679900744417,\n", + " 'F1-1.5': 0.749003984063745,\n", + " 'Recall-1.5': 0.8355555555555556,\n", + " 'Precision-1.5': 0.6787003610108303,\n", + " 'F1-2.5': 0.6060606060606061,\n", + " 'Recall-2.5': 0.7563025210084033,\n", + " 'Precision-2.5': 0.5056179775280899,\n", + " 'F1-3.5': 0.14084507042253522,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.08928571428571429,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8800594751862555},\n", + " 'CM': {'0': {'-1': 0, '0': 91, '1': 60, '2': 19, '3': 12, '4': 3, '5': 1},\n", + " '1': {'-1': 0, '0': 14, '1': 32, '2': 29, '3': 14, '4': 9, '5': 2},\n", + " '2': {'-1': 0, '0': 3, '1': 23, '2': 33, '3': 31, '4': 15, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 11, '2': 18, '3': 55, '4': 19, '5': 1},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 10, '4': 3, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.16588711569468226,\n", " 'Cohen': 0.19228036253776437,\n", " 'Spearman': 0.5866735918259259,\n", " 'Kendall': 0.4939727977473699,\n", @@ -654,12 +851,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.27892558085476743,\n", " 'Micro-F1': 0.36007827788649704,\n", - " 'F1-0': 0.401673640167364,\n", - " 'F1-1': 0.3125,\n", - " 'F1-2': 0.32,\n", - " 'F1-3': 0.4533333333333333,\n", - " 'F1-4': 0.18604651162790697,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.401673640167364,\n", + " 'F1-1_vs_rest': 0.3125,\n", + " 'F1-2_vs_rest': 0.32,\n", + " 'F1-3_vs_rest': 0.4533333333333333,\n", + " 'F1-4_vs_rest': 0.18604651162790697,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8173690932311622,\n", + " 'Recall-0.5': 0.9846153846153847,\n", + " 'Precision-0.5': 0.6986899563318777,\n", + " 'F1-1.5': 0.7393939393939394,\n", + " 'Recall-1.5': 0.8133333333333334,\n", + " 'Precision-1.5': 0.6777777777777778,\n", + " 'F1-2.5': 0.5259259259259259,\n", + " 'Recall-2.5': 0.5966386554621849,\n", + " 'Precision-2.5': 0.47019867549668876,\n", + " 'F1-3.5': 0.26666666666666666,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8871652140653743},\n", " 'CM': {'0': {'-1': 0, '0': 48, '1': 102, '2': 25, '3': 7, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 45, '2': 26, '3': 18, '4': 7, '5': 0},\n", @@ -686,12 +898,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.28429684004747086,\n", " 'Micro-F1': 0.36007827788649704,\n", - " 'F1-0': 0.6344827586206897,\n", - " 'F1-1': 0.32142857142857145,\n", - " 'F1-2': 0.3076923076923077,\n", - " 'F1-3': 0.23170731707317074,\n", - " 'F1-4': 0.08547008547008547,\n", - " 'F1-5': 0.125,\n", + " 'F1-0_vs_rest': 0.6344827586206897,\n", + " 'F1-1_vs_rest': 0.32142857142857145,\n", + " 'F1-2_vs_rest': 0.3076923076923077,\n", + " 'F1-3_vs_rest': 0.23170731707317074,\n", + " 'F1-4_vs_rest': 0.08547008547008547,\n", + " 'F1-5_vs_rest': 0.125,\n", + " 'F1-0.5': 0.855191256830601,\n", + " 'Recall-0.5': 0.963076923076923,\n", + " 'Precision-0.5': 0.769041769041769,\n", + " 'F1-1.5': 0.7913385826771654,\n", + " 'Recall-1.5': 0.8933333333333333,\n", + " 'Precision-1.5': 0.7102473498233216,\n", + " 'F1-2.5': 0.6198083067092651,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.5,\n", + " 'F1-3.5': 0.1342281879194631,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07462686567164178,\n", + " 'F1-4.5': 0.125,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.06666666666666667,\n", " 'NDCG@all': 0.8962455778836316},\n", " 'CM': {'0': {'-1': 0, '0': 92, '1': 66, '2': 15, '3': 5, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 10, '1': 36, '2': 24, '3': 9, '4': 14, '5': 7},\n", @@ -718,12 +945,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.19655877639811004,\n", " 'Micro-F1': 0.2632612966601179,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.22018348623853212,\n", - " 'F1-2': 0.3453815261044177,\n", - " 'F1-3': 0.4608294930875576,\n", - " 'F1-4': 0.12121212121212122,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.22018348623853212,\n", + " 'F1-2_vs_rest': 0.3453815261044177,\n", + " 'F1-3_vs_rest': 0.4608294930875576,\n", + " 'F1-4_vs_rest': 0.12121212121212122,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7792521109770808,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6383399209486166,\n", + " 'F1-1.5': 0.7649402390438247,\n", + " 'Recall-1.5': 0.8609865470852018,\n", + " 'Precision-1.5': 0.6881720430107527,\n", + " 'F1-2.5': 0.5454545454545454,\n", + " 'Recall-2.5': 0.5897435897435898,\n", + " 'Precision-2.5': 0.5073529411764706,\n", + " 'F1-3.5': 0.16666666666666666,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.900996853510188},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 160, '2': 17, '3': 4, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 36, '2': 44, '3': 18, '4': 2, '5': 0},\n", @@ -750,12 +992,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.3737258417905565,\n", " 'Micro-F1': 0.3796477495107632,\n", - " 'F1-0': 0.5522388059701493,\n", - " 'F1-1': 0.3089430894308943,\n", - " 'F1-2': 0.30845771144278605,\n", - " 'F1-3': 0.4077669902912621,\n", - " 'F1-4': 0.16494845360824742,\n", - " 'F1-5': 0.5,\n", + " 'F1-0_vs_rest': 0.5522388059701493,\n", + " 'F1-1_vs_rest': 0.3089430894308943,\n", + " 'F1-2_vs_rest': 0.30845771144278605,\n", + " 'F1-3_vs_rest': 0.4077669902912621,\n", + " 'F1-4_vs_rest': 0.16494845360824742,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8408488063660478,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7389277389277389,\n", + " 'F1-1.5': 0.7480314960629921,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.6713780918727915,\n", + " 'F1-2.5': 0.6123778501628665,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.5,\n", + " 'F1-3.5': 0.19801980198019803,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.11627906976744186,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", " 'NDCG@all': 0.904476063808766},\n", " 'CM': {'0': {'-1': 0, '0': 74, '1': 76, '2': 23, '3': 9, '4': 3, '5': 1},\n", " '1': {'-1': 0, '0': 5, '1': 38, '2': 27, '3': 17, '4': 13, '5': 0},\n", @@ -782,12 +1039,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11355093565748602,\n", " 'Micro-F1': 0.14285714285714285,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.10582010582010581,\n", - " 'F1-2': 0.17670682730923695,\n", - " 'F1-3': 0.27522935779816515,\n", - " 'F1-4': 0.10227272727272728,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.10582010582010581,\n", + " 'F1-2_vs_rest': 0.17670682730923695,\n", + " 'F1-3_vs_rest': 0.27522935779816515,\n", + " 'F1-4_vs_rest': 0.10227272727272728,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6759689922480621,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5190476190476191,\n", + " 'F1-2.5': 0.5303030303030303,\n", + " 'Recall-2.5': 0.8823529411764706,\n", + " 'Precision-2.5': 0.37906137184115524,\n", + " 'F1-3.5': 0.12359550561797752,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.06748466257668712,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8854668923293021},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 72, '2': 77, '3': 23, '4': 12, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 10, '2': 33, '3': 24, '4': 33, '5': 0},\n", @@ -814,12 +1086,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.1314626366852865,\n", " 'Micro-F1': 0.13307240704500978,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.058823529411764705,\n", - " 'F1-2': 0.14953271028037382,\n", - " 'F1-3': 0.2727272727272727,\n", - " 'F1-4': 0.1258741258741259,\n", - " 'F1-5': 0.18181818181818182,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.058823529411764705,\n", + " 'F1-2_vs_rest': 0.14953271028037382,\n", + " 'F1-3_vs_rest': 0.2727272727272727,\n", + " 'F1-4_vs_rest': 0.1258741258741259,\n", + " 'F1-5_vs_rest': 0.18181818181818182,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7056962025316456,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.547911547911548,\n", + " 'F1-2.5': 0.5550239234449761,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.3879598662207358,\n", + " 'F1-3.5': 0.14285714285714285,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07913669064748201,\n", + " 'F1-4.5': 0.18181818181818182,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.1111111111111111,\n", " 'NDCG@all': 0.9006209147328194},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 96, '2': 63, '3': 20, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 27, '3': 48, '4': 16, '5': 3},\n", @@ -846,12 +1133,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2767890378705405,\n", " 'Micro-F1': 0.37573385518590996,\n", - " 'F1-0': 0.3826086956521739,\n", - " 'F1-1': 0.2734375,\n", - " 'F1-2': 0.427536231884058,\n", - " 'F1-3': 0.48826291079812206,\n", - " 'F1-4': 0.08888888888888889,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3826086956521739,\n", + " 'F1-1_vs_rest': 0.2734375,\n", + " 'F1-2_vs_rest': 0.427536231884058,\n", + " 'F1-3_vs_rest': 0.48826291079812206,\n", + " 'F1-4_vs_rest': 0.08888888888888889,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8207070707070707,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.69593147751606,\n", + " 'F1-1.5': 0.7985074626865671,\n", + " 'Recall-1.5': 0.9511111111111111,\n", + " 'Precision-1.5': 0.6881028938906752,\n", + " 'F1-2.5': 0.5923076923076923,\n", + " 'Recall-2.5': 0.6470588235294118,\n", + " 'Precision-2.5': 0.5460992907801419,\n", + " 'F1-3.5': 0.1276595744680851,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.09375,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9051863977133235},\n", " 'CM': {'0': {'-1': 0, '0': 44, '1': 110, '2': 25, '3': 5, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 35, '2': 45, '3': 15, '4': 5, '5': 0},\n", @@ -878,12 +1180,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08788561489818225,\n", " 'Micro-F1': 0.10543130990415335,\n", - " 'F1-0': 0.16071428571428573,\n", - " 'F1-1': 0.021505376344086023,\n", - " 'F1-2': 0.11475409836065574,\n", - " 'F1-3': 0.14814814814814814,\n", - " 'F1-4': 0.0821917808219178,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.16071428571428573,\n", + " 'F1-1_vs_rest': 0.021505376344086023,\n", + " 'F1-2_vs_rest': 0.11475409836065574,\n", + " 'F1-3_vs_rest': 0.14814814814814814,\n", + " 'F1-4_vs_rest': 0.0821917808219178,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8171206225680934,\n", + " 'Recall-0.5': 0.9905660377358491,\n", + " 'Precision-0.5': 0.695364238410596,\n", + " 'F1-1.5': 0.6508313539192399,\n", + " 'Recall-1.5': 0.9716312056737588,\n", + " 'Precision-1.5': 0.48928571428571427,\n", + " 'F1-2.5': 0.46153846153846156,\n", + " 'Recall-2.5': 0.9078947368421053,\n", + " 'Precision-2.5': 0.3094170403587444,\n", + " 'F1-3.5': 0.08536585365853659,\n", + " 'Recall-3.5': 0.6363636363636364,\n", + " 'Precision-3.5': 0.0457516339869281,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8618141740127587},\n", " 'CM': {'0': {'-1': 85, '0': 9, '1': 18, '2': 32, '3': 23, '4': 16, '5': 3},\n", " '1': {'-1': 29, '0': 1, '1': 1, '2': 12, '3': 19, '4': 37, '5': 1},\n", @@ -891,6 +1208,53 @@ " '3': {'-1': 39, '0': 1, '1': 0, '2': 5, '3': 10, '4': 44, '5': 5},\n", " '4': {'-1': 3, '0': 0, '1': 0, '2': 1, '3': 2, '4': 6, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13297603241902303,\n", + " 'Cohen': 0.1734400094010733,\n", + " 'Spearman': 0.6911600163966094,\n", + " 'Kendall': 0.5934610549123195,\n", + " 'Krippendorff': 0.5907768825035782,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7549019607843137,\n", + " 'TA-4.0': 0.9666666666666667,\n", + " 'Acc': 0.3509803921568627,\n", + " 'MAE': 0.7774509803921567,\n", + " 'MSE': 1.014433551198257,\n", + " 'CA-0': 0.22043010752688172,\n", + " 'CA-1': 0.3,\n", + " 'CA-2': 0.660377358490566,\n", + " 'CA-3': 0.3592233009708738,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2543133455470617,\n", + " 'Micro-F1': 0.3509803921568627,\n", + " 'F1-0_vs_rest': 0.35807860262008734,\n", + " 'F1-1_vs_rest': 0.23715415019762845,\n", + " 'F1-2_vs_rest': 0.42168674698795183,\n", + " 'F1-3_vs_rest': 0.3978494623655914,\n", + " 'F1-4_vs_rest': 0.1111111111111111,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8141592920353983,\n", + " 'Recall-0.5': 0.9938271604938271,\n", + " 'Precision-0.5': 0.6895074946466809,\n", + " 'F1-1.5': 0.7881040892193308,\n", + " 'Recall-1.5': 0.9464285714285714,\n", + " 'Precision-1.5': 0.6751592356687898,\n", + " 'F1-2.5': 0.4563106796116505,\n", + " 'Recall-2.5': 0.3983050847457627,\n", + " 'Precision-2.5': 0.5340909090909091,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9111846181499187},\n", + " 'CM': {'0': {'-1': 0, '0': 41, '1': 111, '2': 31, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 30, '2': 56, '3': 12, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 10, '2': 70, '3': 24, '4': 2, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 2, '2': 62, '3': 37, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 5, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.09640031331237015,\n", " 'Cohen': 0.12505495954977142,\n", " 'Spearman': 0.6716945975644261,\n", @@ -910,12 +1274,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.25640917913565986,\n", " 'Micro-F1': 0.2823779193205945,\n", - " 'F1-0': 0.484304932735426,\n", - " 'F1-1': 0.15384615384615385,\n", - " 'F1-2': 0.2928870292887029,\n", - " 'F1-3': 0.2810810810810811,\n", - " 'F1-4': 0.07633587786259542,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.484304932735426,\n", + " 'F1-1_vs_rest': 0.15384615384615385,\n", + " 'F1-2_vs_rest': 0.2928870292887029,\n", + " 'F1-3_vs_rest': 0.2810810810810811,\n", + " 'F1-4_vs_rest': 0.07633587786259542,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8400556328233658,\n", + " 'Recall-0.5': 0.9741935483870968,\n", + " 'Precision-0.5': 0.7383863080684596,\n", + " 'F1-1.5': 0.7566607460035524,\n", + " 'Recall-1.5': 0.9638009049773756,\n", + " 'Precision-1.5': 0.6228070175438597,\n", + " 'F1-2.5': 0.6111111111111112,\n", + " 'Recall-2.5': 0.8319327731092437,\n", + " 'Precision-2.5': 0.48292682926829267,\n", + " 'F1-3.5': 0.10071942446043165,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.056451612903225805,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.9132807727945667},\n", " 'CM': {'0': {'-1': 25, '0': 54, '1': 49, '2': 43, '3': 10, '4': 5, '5': 0},\n", " '1': {'-1': 11, '0': 6, '1': 12, '2': 39, '3': 14, '4': 18, '5': 0},\n", @@ -942,12 +1321,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12917755405681397,\n", " 'Micro-F1': 0.162426614481409,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.1092896174863388,\n", - " 'F1-2': 0.15444015444015444,\n", - " 'F1-3': 0.29045643153526973,\n", - " 'F1-4': 0.12857142857142856,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.1092896174863388,\n", + " 'F1-2_vs_rest': 0.15444015444015444,\n", + " 'F1-3_vs_rest': 0.29045643153526973,\n", + " 'F1-4_vs_rest': 0.12857142857142856,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6708074534161491,\n", + " 'Recall-1.5': 0.96,\n", + " 'Precision-1.5': 0.5155131264916468,\n", + " 'F1-2.5': 0.5402597402597402,\n", + " 'Recall-2.5': 0.8739495798319328,\n", + " 'Precision-2.5': 0.39097744360902253,\n", + " 'F1-3.5': 0.1527777777777778,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08527131782945736,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8864212752405546},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 64, '2': 81, '3': 24, '4': 7, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 10, '2': 39, '3': 31, '4': 20, '5': 0},\n", @@ -955,647 +1349,1182 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 13, '3': 35, '4': 53, '5': 1},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, 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'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7559808612440191,\n", + " 'F1-1.5': 0.7490774907749077,\n", + " 'Recall-1.5': 0.9022222222222223,\n", + " 'Precision-1.5': 0.6403785488958991,\n", + " 'F1-2.5': 0.591715976331361,\n", + " 'Recall-2.5': 0.8403361344537815,\n", + " 'Precision-2.5': 0.45662100456621,\n", + " 'F1-3.5': 0.15,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.09230769230769231,\n", + " 'F1-4.5': 0.2222222222222222,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.14285714285714285,\n", + " 'NDCG@all': 0.8878281403189244},\n", + " 'CM': {'0': {'-1': 0, '0': 84, '1': 52, '2': 32, '3': 13, '4': 4, '5': 1},\n", + " '1': {'-1': 0, '0': 8, '1': 28, '2': 25, '3': 30, '4': 6, '5': 3},\n", + " '2': {'-1': 0, '0': 1, '1': 17, '2': 26, '3': 47, '4': 15, '5': 0},\n", + " '3': {'-1': 0, '0': 0, '1': 4, '2': 15, '3': 55, '4': 28, '5': 2},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 8, '4': 5, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0760532145238589,\n", " 'Cohen': 0.11510918701714945,\n", " 'Spearman': 0.5946333886099705,\n", " 'Kendall': 0.5041168968431521,\n", @@ -1614,12 +2543,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2177940467738537,\n", " 'Micro-F1': 0.29158512720156554,\n", - " 'F1-0': 0.22641509433962265,\n", - " 'F1-1': 0.24305555555555555,\n", - " 'F1-2': 0.2834008097165992,\n", - " 'F1-3': 0.4608695652173913,\n", - " 'F1-4': 0.09302325581395349,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.22641509433962265,\n", + " 'F1-1_vs_rest': 0.24305555555555555,\n", + " 'F1-2_vs_rest': 0.2834008097165992,\n", + " 'F1-3_vs_rest': 0.4608695652173913,\n", + " 'F1-4_vs_rest': 0.09302325581395349,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7975308641975308,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6659793814432989,\n", + " 'F1-1.5': 0.7241379310344828,\n", + " 'Recall-1.5': 0.84,\n", + " 'Precision-1.5': 0.6363636363636364,\n", + " 'F1-2.5': 0.5527272727272727,\n", + " 'Recall-2.5': 0.6386554621848739,\n", + " 'Precision-2.5': 0.48717948717948717,\n", + " 'F1-3.5': 0.13333333333333333,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8869302180716039},\n", " 'CM': {'0': {'-1': 0, '0': 24, '1': 117, '2': 37, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 35, '2': 40, '3': 16, '4': 7, '5': 0},\n", @@ -1646,12 +2590,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.32033743244669327,\n", " 'Micro-F1': 0.4050880626223092,\n", - " 'F1-0': 0.6801346801346801,\n", - " 'F1-1': 0.36363636363636365,\n", - " 'F1-2': 0.3673469387755102,\n", - " 'F1-3': 0.2331288343558282,\n", - " 'F1-4': 0.12962962962962962,\n", - " 'F1-5': 0.14814814814814814,\n", + " 'F1-0_vs_rest': 0.6801346801346801,\n", + " 'F1-1_vs_rest': 0.36363636363636365,\n", + " 'F1-2_vs_rest': 0.3673469387755102,\n", + " 'F1-3_vs_rest': 0.2331288343558282,\n", + " 'F1-4_vs_rest': 0.12962962962962962,\n", + " 'F1-5_vs_rest': 0.14814814814814814,\n", + " 'F1-0.5': 0.8689655172413793,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7875,\n", + " 'F1-1.5': 0.7894736842105263,\n", + " 'Recall-1.5': 0.8666666666666667,\n", + " 'Precision-1.5': 0.724907063197026,\n", + " 'F1-2.5': 0.6040268456375839,\n", + " 'Recall-2.5': 0.7563025210084033,\n", + " 'Precision-2.5': 0.5027932960893855,\n", + " 'F1-3.5': 0.16296296296296298,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.09166666666666666,\n", + " 'F1-4.5': 0.14814814814814814,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.08,\n", " 'NDCG@all': 0.8964037523983026},\n", " 'CM': {'0': {'-1': 0, '0': 101, '1': 60, '2': 10, '3': 9, '4': 2, '5': 4},\n", " '1': {'-1': 0, '0': 9, '1': 42, '2': 20, '3': 10, '4': 14, '5': 5},\n", @@ -1678,12 +2637,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2084528463001225,\n", " 'Micro-F1': 0.29411764705882354,\n", - " 'F1-0': 0.042105263157894736,\n", - " 'F1-1': 0.29444444444444445,\n", - " 'F1-2': 0.3565217391304348,\n", - " 'F1-3': 0.49514563106796117,\n", - " 'F1-4': 0.0625,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.042105263157894736,\n", + " 'F1-1_vs_rest': 0.29444444444444445,\n", + " 'F1-2_vs_rest': 0.3565217391304348,\n", + " 'F1-3_vs_rest': 0.49514563106796117,\n", + " 'F1-4_vs_rest': 0.0625,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7807228915662651,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6403162055335968,\n", + " 'F1-1.5': 0.7489361702127659,\n", + " 'Recall-1.5': 0.7857142857142857,\n", + " 'Precision-1.5': 0.7154471544715447,\n", + " 'F1-2.5': 0.5583333333333333,\n", + " 'Recall-2.5': 0.5630252100840336,\n", + " 'Precision-2.5': 0.5537190082644629,\n", + " 'F1-3.5': 0.11764705882352941,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.10526315789473684,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8885064368778701},\n", " 'CM': {'0': {'-1': 0, '0': 4, '1': 159, '2': 16, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 53, '2': 32, '3': 12, '4': 3, '5': 0},\n", @@ -1710,12 +2684,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.25119909014876957,\n", " 'Micro-F1': 0.33268101761252444,\n", - " 'F1-0': 0.5220588235294118,\n", - " 'F1-1': 0.3333333333333333,\n", - " 'F1-2': 0.18181818181818182,\n", - " 'F1-3': 0.3033175355450237,\n", - " 'F1-4': 0.16666666666666666,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5220588235294118,\n", + " 'F1-1_vs_rest': 0.3333333333333333,\n", + " 'F1-2_vs_rest': 0.18181818181818182,\n", + " 'F1-3_vs_rest': 0.3033175355450237,\n", + " 'F1-4_vs_rest': 0.16666666666666666,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8266666666666667,\n", + " 'Recall-0.5': 0.9538461538461539,\n", + " 'Precision-0.5': 0.7294117647058823,\n", + " 'F1-1.5': 0.7469879518072289,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6813186813186813,\n", + " 'F1-2.5': 0.6186186186186187,\n", + " 'Recall-2.5': 0.865546218487395,\n", + " 'Precision-2.5': 0.48130841121495327,\n", + " 'F1-3.5': 0.19672131147540983,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.11214953271028037,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9124451754206458},\n", " 'CM': {'0': {'-1': 0, '0': 71, '1': 80, '2': 20, '3': 11, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 6, '1': 42, '2': 20, '3': 19, '4': 13, '5': 0},\n", @@ -1742,12 +2731,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.0787009578241681,\n", " 'Micro-F1': 0.09784735812133072,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.0784313725490196,\n", - " 'F1-2': 0.17721518987341772,\n", - " 'F1-3': 0.13043478260869565,\n", - " 'F1-4': 0.0861244019138756,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.0784313725490196,\n", + " 'F1-2_vs_rest': 0.17721518987341772,\n", + " 'F1-3_vs_rest': 0.13043478260869565,\n", + " 'F1-4_vs_rest': 0.0861244019138756,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6930379746835443,\n", + " 'Recall-1.5': 0.9733333333333334,\n", + " 'Precision-1.5': 0.538083538083538,\n", + " 'F1-2.5': 0.5316455696202531,\n", + " 'Recall-2.5': 0.8823529411764706,\n", + " 'Precision-2.5': 0.3804347826086957,\n", + " 'F1-3.5': 0.10426540284360189,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.05612244897959184,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8888230445200241},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 59, '3': 20, '4': 17, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 39, '3': 22, '4': 31, '5': 0},\n", @@ -1774,12 +2778,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09964342920565251,\n", " 'Micro-F1': 0.12915851272015655,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.07692307692307693,\n", - " 'F1-2': 0.1588785046728972,\n", - " 'F1-3': 0.24175824175824176,\n", - " 'F1-4': 0.12030075187969924,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.07692307692307693,\n", + " 'F1-2_vs_rest': 0.1588785046728972,\n", + " 'F1-3_vs_rest': 0.24175824175824176,\n", + " 'F1-4_vs_rest': 0.12030075187969924,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7101910828025477,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5533498759305211,\n", + " 'F1-2.5': 0.5458937198067633,\n", + " 'Recall-2.5': 0.9495798319327731,\n", + " 'Precision-2.5': 0.38305084745762713,\n", + " 'F1-3.5': 0.14184397163120568,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07936507936507936,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8966455180175203},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 98, '2': 58, '3': 24, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 28, '3': 46, '4': 17, '5': 1},\n", @@ -1806,12 +2825,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2961800950226636,\n", " 'Micro-F1': 0.40117416829745595,\n", - " 'F1-0': 0.4034334763948498,\n", - " 'F1-1': 0.2943396226415094,\n", - " 'F1-2': 0.4280155642023346,\n", - " 'F1-3': 0.5560538116591929,\n", - " 'F1-4': 0.09523809523809523,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4034334763948498,\n", + " 'F1-1_vs_rest': 0.2943396226415094,\n", + " 'F1-2_vs_rest': 0.4280155642023346,\n", + " 'F1-3_vs_rest': 0.5560538116591929,\n", + " 'F1-4_vs_rest': 0.09523809523809523,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8238276299112801,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.7004310344827587,\n", + " 'F1-1.5': 0.7748091603053435,\n", + " 'Recall-1.5': 0.9022222222222223,\n", + " 'Precision-1.5': 0.6789297658862876,\n", + " 'F1-2.5': 0.6367041198501873,\n", + " 'Recall-2.5': 0.7142857142857143,\n", + " 'Precision-2.5': 0.5743243243243243,\n", + " 'F1-3.5': 0.13636363636363635,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.10344827586206896,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8981506220609349},\n", " 'CM': {'0': {'-1': 0, '0': 47, '1': 104, '2': 25, '3': 6, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 39, '2': 42, '3': 16, '4': 3, '5': 0},\n", @@ -1838,12 +2872,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1311417004880069,\n", " 'Micro-F1': 0.1564245810055866,\n", - " 'F1-0': 0.12658227848101267,\n", - " 'F1-1': 0.15873015873015872,\n", - " 'F1-2': 0.16666666666666666,\n", - " 'F1-3': 0.29850746268656714,\n", - " 'F1-4': 0.03636363636363636,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.12658227848101267,\n", + " 'F1-1_vs_rest': 0.15873015873015872,\n", + " 'F1-2_vs_rest': 0.16666666666666666,\n", + " 'F1-3_vs_rest': 0.29850746268656714,\n", + " 'F1-4_vs_rest': 0.03636363636363636,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7526881720430108,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.603448275862069,\n", + " 'F1-1.5': 0.6018518518518519,\n", + " 'Recall-1.5': 0.9558823529411765,\n", + " 'Precision-1.5': 0.4391891891891892,\n", + " 'F1-2.5': 0.48484848484848486,\n", + " 'Recall-2.5': 0.8648648648648649,\n", + " 'Precision-2.5': 0.3368421052631579,\n", + " 'F1-3.5': 0.12307692307692308,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.06779661016949153,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8358097549745576},\n", " 'CM': {'0': {'-1': 112, '0': 5, '1': 18, '2': 29, '3': 11, '4': 9, '5': 2},\n", " '1': {'-1': 63, '0': 0, '1': 5, '2': 13, '3': 9, '4': 8, '5': 2},\n", @@ -1851,6 +2900,53 @@ " '3': {'-1': 73, '0': 0, '1': 0, '2': 3, '3': 10, '4': 15, '5': 3},\n", " '4': {'-1': 8, '0': 0, '1': 1, '2': 1, '3': 0, '4': 1, '5': 2},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1438858309727244,\n", + " 'Cohen': 0.17958979489744875,\n", + " 'Spearman': 0.6947722013864978,\n", + " 'Kendall': 0.5974775270838849,\n", + " 'Krippendorff': 0.6088878412396672,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7647058823529411,\n", + " 'TA-4.0': 0.9627450980392157,\n", + " 'Acc': 0.3568627450980392,\n", + " 'MAE': 0.7617647058823527,\n", + " 'MSE': 0.983061002178649,\n", + " 'CA-0': 0.24193548387096775,\n", + " 'CA-1': 0.33,\n", + " 'CA-2': 0.6226415094339622,\n", + " 'CA-3': 0.36893203883495146,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.24314481552569087,\n", + " 'Micro-F1': 0.3568627450980392,\n", + " 'F1-0_vs_rest': 0.38461538461538464,\n", + " 'F1-1_vs_rest': 0.2509505703422053,\n", + " 'F1-2_vs_rest': 0.41904761904761906,\n", + " 'F1-3_vs_rest': 0.40425531914893614,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.816793893129771,\n", + " 'Recall-0.5': 0.9907407407407407,\n", + " 'Precision-0.5': 0.6948051948051948,\n", + " 'F1-1.5': 0.7915869980879541,\n", + " 'Recall-1.5': 0.9241071428571429,\n", + " 'Precision-1.5': 0.6923076923076923,\n", + " 'F1-2.5': 0.4807692307692308,\n", + " 'Recall-2.5': 0.423728813559322,\n", + " 'Precision-2.5': 0.5555555555555556,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.904681007323939},\n", + " 'CM': {'0': {'-1': 0, '0': 45, '1': 113, '2': 24, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 3, '1': 33, '2': 55, '3': 8, '4': 1, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 13, '2': 66, '3': 26, '4': 1, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 4, '2': 58, '3': 38, '4': 3, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 7, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.2020930818199387,\n", " 'Cohen': 0.21798948480117553,\n", " 'Spearman': 0.6308886758496952,\n", @@ -1870,12 +2966,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.28032607803103093,\n", " 'Micro-F1': 0.36989247311827955,\n", - " 'F1-0': 0.5761316872427984,\n", - " 'F1-1': 0.2681564245810056,\n", - " 'F1-2': 0.37668161434977576,\n", - " 'F1-3': 0.3488372093023256,\n", - " 'F1-4': 0.11214953271028037,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5761316872427984,\n", + " 'F1-1_vs_rest': 0.2681564245810056,\n", + " 'F1-2_vs_rest': 0.37668161434977576,\n", + " 'F1-3_vs_rest': 0.3488372093023256,\n", + " 'F1-4_vs_rest': 0.11214953271028037,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8500727802037845,\n", + " 'Recall-0.5': 0.954248366013072,\n", + " 'Precision-0.5': 0.7664041994750657,\n", + " 'F1-1.5': 0.7677165354330708,\n", + " 'Recall-1.5': 0.8944954128440367,\n", + " 'Precision-1.5': 0.6724137931034483,\n", + " 'F1-2.5': 0.6035087719298246,\n", + " 'Recall-2.5': 0.7288135593220338,\n", + " 'Precision-2.5': 0.5149700598802395,\n", + " 'F1-3.5': 0.12389380530973451,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.07142857142857142,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8818882556649317},\n", " 'CM': {'0': {'-1': 27, '0': 70, '1': 50, '2': 28, '3': 4, '4': 6, '5': 1},\n", " '1': {'-1': 12, '0': 8, '1': 24, '2': 26, '3': 16, '4': 13, '5': 1},\n", @@ -1902,12 +3013,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12875257958222047,\n", " 'Micro-F1': 0.15851272015655576,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.1218274111675127,\n", - " 'F1-2': 0.1640625,\n", - " 'F1-3': 0.2600896860986547,\n", - " 'F1-4': 0.1342281879194631,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.1218274111675127,\n", + " 'F1-2_vs_rest': 0.1640625,\n", + " 'F1-3_vs_rest': 0.2600896860986547,\n", + " 'F1-4_vs_rest': 0.1342281879194631,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6857142857142857,\n", + " 'Recall-1.5': 0.96,\n", + " 'Precision-1.5': 0.5333333333333333,\n", + " 'F1-2.5': 0.5401069518716578,\n", + " 'Recall-2.5': 0.8487394957983193,\n", + " 'Precision-2.5': 0.396078431372549,\n", + " 'F1-3.5': 0.15894039735099338,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08823529411764706,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8973069383958757},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 76, '2': 72, '3': 21, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 12, '2': 41, '3': 27, '4': 20, '5': 0},\n", @@ -1915,7 +3041,54 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 16, '3': 29, '4': 57, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'et': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0895834113111502,\n", + " 'et': {'phi-4': {'metrics': {'Fleiss': 0.16558092638361183,\n", + " 'Cohen': 0.18244334035304144,\n", + " 'Spearman': 0.649066914283782,\n", + " 'Kendall': 0.5389754356719453,\n", + " 'Krippendorff': 0.5261555326699758,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7064579256360078,\n", + " 'TA-4.0': 0.8767123287671232,\n", + " 'Acc': 0.350293542074364,\n", + " 'MAE': 0.9399869536855838,\n", + " 'MSE': 1.671450315285932,\n", + " 'CA-0': 0.4032258064516129,\n", + " 'CA-1': 0.24,\n", + " 'CA-2': 0.1792452830188679,\n", + " 'CA-3': 0.5480769230769231,\n", + " 'CA-4': 0.23076923076923078,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3147512127127717,\n", + " 'Micro-F1': 0.350293542074364,\n", + " 'F1-0_vs_rest': 0.5576208178438662,\n", + " 'F1-1_vs_rest': 0.23880597014925373,\n", + " 'F1-2_vs_rest': 0.18719211822660098,\n", + " 'F1-3_vs_rest': 0.42696629213483145,\n", + " 'F1-4_vs_rest': 0.07792207792207792,\n", + " 'F1-5_vs_rest': 0.4,\n", + " 'F1-0.5': 0.8419654714475432,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7406542056074766,\n", + " 'F1-1.5': 0.75,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.6330275229357798,\n", + " 'F1-2.5': 0.5673352435530086,\n", + " 'Recall-2.5': 0.8319327731092437,\n", + " 'Precision-2.5': 0.43043478260869567,\n", + " 'F1-3.5': 0.12195121951219512,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.07462686567164178,\n", + " 'F1-4.5': 0.4,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.3333333333333333,\n", + " 'NDCG@all': 0.9010819148560122},\n", + " 'CM': {'0': {'-1': 0, '0': 75, '1': 62, '2': 30, '3': 14, '4': 5, '5': 0},\n", + " '1': {'-1': 0, '0': 5, '1': 24, '2': 32, '3': 30, '4': 9, '5': 0},\n", + " '2': {'-1': 0, '0': 3, '1': 11, '2': 19, '3': 54, '4': 17, '5': 2},\n", + " '3': {'-1': 0, '0': 0, '1': 4, '2': 14, '3': 57, '4': 29, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 2, '3': 8, '4': 3, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0895834113111502,\n", " 'Cohen': 0.12669226203013995,\n", " 'Spearman': 0.5886573583101743,\n", " 'Kendall': 0.49874009555449356,\n", @@ -1934,12 +3107,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23190438310001307,\n", " 'Micro-F1': 0.3013698630136986,\n", - " 'F1-0': 0.23963133640552994,\n", - " 'F1-1': 0.22916666666666666,\n", - " 'F1-2': 0.35294117647058826,\n", - " 'F1-3': 0.4392523364485981,\n", - " 'F1-4': 0.13043478260869565,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.23963133640552994,\n", + " 'F1-1_vs_rest': 0.22916666666666666,\n", + " 'F1-2_vs_rest': 0.35294117647058826,\n", + " 'F1-3_vs_rest': 0.4392523364485981,\n", + " 'F1-4_vs_rest': 0.13043478260869565,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7950310559006211,\n", + " 'Recall-0.5': 0.9846153846153847,\n", + " 'Precision-0.5': 0.6666666666666666,\n", + " 'F1-1.5': 0.7350096711798839,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.6506849315068494,\n", + " 'F1-2.5': 0.549618320610687,\n", + " 'Recall-2.5': 0.6050420168067226,\n", + " 'Precision-2.5': 0.5034965034965035,\n", + " 'F1-3.5': 0.16666666666666666,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.12121212121212122,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8868261112040604},\n", " 'CM': {'0': {'-1': 0, '0': 26, '1': 120, '2': 31, '3': 4, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 33, '2': 41, '3': 15, '4': 6, '5': 0},\n", @@ -1966,12 +3154,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.3117286433927741,\n", " 'Micro-F1': 0.40313111545988256,\n", - " 'F1-0': 0.6597938144329897,\n", - " 'F1-1': 0.37130801687763715,\n", - " 'F1-2': 0.36363636363636365,\n", - " 'F1-3': 0.2822085889570552,\n", - " 'F1-4': 0.11009174311926606,\n", - " 'F1-5': 0.08333333333333333,\n", + " 'F1-0_vs_rest': 0.6597938144329897,\n", + " 'F1-1_vs_rest': 0.37130801687763715,\n", + " 'F1-2_vs_rest': 0.36363636363636365,\n", + " 'F1-3_vs_rest': 0.2822085889570552,\n", + " 'F1-4_vs_rest': 0.11009174311926606,\n", + " 'F1-5_vs_rest': 0.08333333333333333,\n", + " 'F1-0.5': 0.8645690834473324,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7783251231527094,\n", + " 'F1-1.5': 0.8016194331983806,\n", + " 'Recall-1.5': 0.88,\n", + " 'Precision-1.5': 0.7360594795539034,\n", + " 'F1-2.5': 0.6283783783783784,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.5254237288135594,\n", + " 'F1-3.5': 0.15037593984962405,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.0847457627118644,\n", + " 'F1-4.5': 0.08333333333333333,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.045454545454545456,\n", " 'NDCG@all': 0.8896079879101745},\n", " 'CM': {'0': {'-1': 0, '0': 96, '1': 69, '2': 10, '3': 4, '4': 3, '5': 4},\n", " '1': {'-1': 0, '0': 6, '1': 44, '2': 24, '3': 8, '4': 13, '5': 5},\n", @@ -1998,12 +3201,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.18341003615458226,\n", " 'Micro-F1': 0.275049115913556,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.26822157434402333,\n", - " 'F1-2': 0.33620689655172414,\n", - " 'F1-3': 0.4642857142857143,\n", - " 'F1-4': 0.0,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.26822157434402333,\n", + " 'F1-2_vs_rest': 0.33620689655172414,\n", + " 'F1-3_vs_rest': 0.4642857142857143,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7792521109770808,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6383399209486166,\n", + " 'F1-1.5': 0.7654320987654321,\n", + " 'Recall-1.5': 0.8340807174887892,\n", + " 'Precision-1.5': 0.7072243346007605,\n", + " 'F1-2.5': 0.5590551181102362,\n", + " 'Recall-2.5': 0.6068376068376068,\n", + " 'Precision-2.5': 0.5182481751824818,\n", + " 'F1-3.5': 0.06666666666666667,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.06666666666666667,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9070218054859662},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 160, '2': 18, '3': 5, '4': 0, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 46, '2': 33, '3': 19, '4': 2, '5': 0},\n", @@ -2030,12 +3248,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22248246053786316,\n", " 'Micro-F1': 0.29158512720156554,\n", - " 'F1-0': 0.5019607843137255,\n", - " 'F1-1': 0.28448275862068967,\n", - " 'F1-2': 0.16080402010050251,\n", - " 'F1-3': 0.2648401826484018,\n", - " 'F1-4': 0.12280701754385964,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5019607843137255,\n", + " 'F1-1_vs_rest': 0.28448275862068967,\n", + " 'F1-2_vs_rest': 0.16080402010050251,\n", + " 'F1-3_vs_rest': 0.2648401826484018,\n", + " 'F1-4_vs_rest': 0.12280701754385964,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.834419817470665,\n", + " 'Recall-0.5': 0.9846153846153847,\n", + " 'Precision-0.5': 0.7239819004524887,\n", + " 'F1-1.5': 0.7327102803738318,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.632258064516129,\n", + " 'F1-2.5': 0.5595238095238095,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.43317972350230416,\n", + " 'F1-3.5': 0.15384615384615385,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.08823529411764706,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8944168140548879},\n", " 'CM': {'0': {'-1': 0, '0': 64, '1': 72, '2': 34, '3': 11, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 33, '2': 27, '3': 22, '4': 14, '5': 1},\n", @@ -2062,12 +3295,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.06830586376405796,\n", " 'Micro-F1': 0.08414872798434442,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07954545454545454,\n", - " 'F1-2': 0.11353711790393013,\n", - " 'F1-3': 0.10784313725490197,\n", - " 'F1-4': 0.09821428571428571,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07954545454545454,\n", + " 'F1-2_vs_rest': 0.11353711790393013,\n", + " 'F1-3_vs_rest': 0.10784313725490197,\n", + " 'F1-4_vs_rest': 0.09821428571428571,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6707132018209409,\n", + " 'Recall-1.5': 0.9822222222222222,\n", + " 'Precision-1.5': 0.5092165898617511,\n", + " 'F1-2.5': 0.5255813953488372,\n", + " 'Recall-2.5': 0.9495798319327731,\n", + " 'Precision-2.5': 0.3633440514469453,\n", + " 'F1-3.5': 0.11504424778761062,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.061611374407582936,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8951297972913057},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 65, '2': 76, '3': 31, '4': 13, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 30, '3': 30, '4': 33, '5': 0},\n", @@ -2094,12 +3342,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09024573310282308,\n", " 'Micro-F1': 0.11937377690802348,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.05853658536585366,\n", - " 'F1-2': 0.1188118811881188,\n", - " 'F1-3': 0.24647887323943662,\n", - " 'F1-4': 0.11764705882352941,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.05853658536585366,\n", + " 'F1-2_vs_rest': 0.1188118811881188,\n", + " 'F1-3_vs_rest': 0.24647887323943662,\n", + " 'F1-4_vs_rest': 0.11764705882352941,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7068145800316957,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5492610837438424,\n", + " 'F1-2.5': 0.5314685314685315,\n", + " 'Recall-2.5': 0.957983193277311,\n", + " 'Precision-2.5': 0.36774193548387096,\n", + " 'F1-3.5': 0.13793103448275862,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07692307692307693,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.900840405136827},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 97, '2': 55, '3': 30, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 25, '3': 50, '4': 18, '5': 1},\n", @@ -2126,12 +3389,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2554860618213582,\n", " 'Micro-F1': 0.33268101761252444,\n", - " 'F1-0': 0.3013698630136986,\n", - " 'F1-1': 0.23826714801444043,\n", - " 'F1-2': 0.3944636678200692,\n", - " 'F1-3': 0.45595854922279794,\n", - " 'F1-4': 0.14285714285714285,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3013698630136986,\n", + " 'F1-1_vs_rest': 0.23826714801444043,\n", + " 'F1-2_vs_rest': 0.3944636678200692,\n", + " 'F1-3_vs_rest': 0.45595854922279794,\n", + " 'F1-4_vs_rest': 0.14285714285714285,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8094645080946451,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6799163179916318,\n", + " 'F1-1.5': 0.7604562737642585,\n", + " 'Recall-1.5': 0.8888888888888888,\n", + " 'Precision-1.5': 0.6644518272425249,\n", + " 'F1-2.5': 0.5654008438818565,\n", + " 'Recall-2.5': 0.5630252100840336,\n", + " 'Precision-2.5': 0.5677966101694916,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.13793103448275862,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9002040119744911},\n", " 'CM': {'0': {'-1': 0, '0': 33, '1': 119, '2': 27, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 33, '2': 51, '3': 10, '4': 6, '5': 0},\n", @@ -2158,12 +3436,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.11925675181253274,\n", " 'Micro-F1': 0.12437810945273632,\n", - " 'F1-0': 0.07142857142857142,\n", - " 'F1-1': 0.0392156862745098,\n", - " 'F1-2': 0.12987012987012986,\n", - " 'F1-3': 0.2727272727272727,\n", - " 'F1-4': 0.06896551724137931,\n", - " 'F1-5': 0.13333333333333333,\n", + " 'F1-0_vs_rest': 0.07142857142857142,\n", + " 'F1-1_vs_rest': 0.0392156862745098,\n", + " 'F1-2_vs_rest': 0.12987012987012986,\n", + " 'F1-3_vs_rest': 0.2727272727272727,\n", + " 'F1-4_vs_rest': 0.06896551724137931,\n", + " 'F1-5_vs_rest': 0.13333333333333333,\n", + " 'F1-0.5': 0.7547169811320755,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6060606060606061,\n", + " 'F1-1.5': 0.6217228464419475,\n", + " 'Recall-1.5': 0.9764705882352941,\n", + " 'Precision-1.5': 0.45604395604395603,\n", + " 'F1-2.5': 0.4421052631578947,\n", + " 'Recall-2.5': 0.9130434782608695,\n", + " 'Precision-2.5': 0.2916666666666667,\n", + " 'F1-3.5': 0.0784313725490196,\n", + " 'Recall-3.5': 0.5714285714285714,\n", + " 'Precision-3.5': 0.042105263157894736,\n", + " 'F1-4.5': 0.13333333333333333,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.07142857142857142,\n", " 'NDCG@all': 0.810221510285519},\n", " 'CM': {'0': {'-1': 105, '0': 3, '1': 13, '2': 22, '3': 19, '4': 19, '5': 5},\n", " '1': {'-1': 65, '0': 0, '1': 1, '2': 8, '3': 7, '4': 19, '5': 0},\n", @@ -2171,6 +3464,53 @@ " '3': {'-1': 65, '0': 0, '1': 1, '2': 2, '3': 12, '4': 20, '5': 4},\n", " '4': {'-1': 7, '0': 0, '1': 0, '2': 1, '3': 2, '4': 3, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.11180771628168028,\n", + " 'Cohen': 0.15448403553349477,\n", + " 'Spearman': 0.6913342173111973,\n", + " 'Kendall': 0.5944550436574051,\n", + " 'Krippendorff': 0.5741091963068756,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7440944881889764,\n", + " 'TA-4.0': 0.9645669291338582,\n", + " 'Acc': 0.3346456692913386,\n", + " 'MAE': 0.7979002624671914,\n", + " 'MSE': 1.0468066491688535,\n", + " 'CA-0': 0.1935483870967742,\n", + " 'CA-1': 0.27,\n", + " 'CA-2': 0.6509433962264151,\n", + " 'CA-3': 0.37623762376237624,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2252702862488842,\n", + " 'Micro-F1': 0.3346456692913386,\n", + " 'F1-0_vs_rest': 0.32286995515695066,\n", + " 'F1-1_vs_rest': 0.216,\n", + " 'F1-2_vs_rest': 0.4169184290030212,\n", + " 'F1-3_vs_rest': 0.3958333333333333,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8095838587641866,\n", + " 'Recall-0.5': 0.9968944099378882,\n", + " 'Precision-0.5': 0.6815286624203821,\n", + " 'F1-1.5': 0.7845303867403315,\n", + " 'Recall-1.5': 0.9594594594594594,\n", + " 'Precision-1.5': 0.6635514018691588,\n", + " 'F1-2.5': 0.4716981132075472,\n", + " 'Recall-2.5': 0.43103448275862066,\n", + " 'Precision-2.5': 0.5208333333333334,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9088057990711205},\n", + " 'CM': {'0': {'-1': 0, '0': 36, '1': 114, '2': 32, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 27, '2': 58, '3': 14, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 9, '2': 69, '3': 25, '4': 3, '5': 0},\n", + " '3': {'-1': 3, '0': 0, '1': 0, '2': 62, '3': 38, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 4, '3': 9, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.10729452617254405,\n", " 'Cohen': 0.12806939144981844,\n", " 'Spearman': 0.6300324475976044,\n", @@ -2190,12 +3530,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2227745574018922,\n", " 'Micro-F1': 0.29310344827586204,\n", - " 'F1-0': 0.48623853211009177,\n", - " 'F1-1': 0.1761006289308176,\n", - " 'F1-2': 0.2966101694915254,\n", - " 'F1-3': 0.3015075376884422,\n", - " 'F1-4': 0.0761904761904762,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.48623853211009177,\n", + " 'F1-1_vs_rest': 0.1761006289308176,\n", + " 'F1-2_vs_rest': 0.2966101694915254,\n", + " 'F1-3_vs_rest': 0.3015075376884422,\n", + " 'F1-4_vs_rest': 0.0761904761904762,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8422535211267606,\n", + " 'Recall-0.5': 0.9583333333333334,\n", + " 'Precision-0.5': 0.7512562814070352,\n", + " 'F1-1.5': 0.7477313974591652,\n", + " 'Recall-1.5': 0.944954128440367,\n", + " 'Precision-1.5': 0.6186186186186187,\n", + " 'F1-2.5': 0.5968253968253968,\n", + " 'Recall-2.5': 0.8103448275862069,\n", + " 'Precision-2.5': 0.4723618090452261,\n", + " 'F1-3.5': 0.10344827586206896,\n", + " 'Recall-3.5': 0.46153846153846156,\n", + " 'Precision-3.5': 0.05825242718446602,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.884117460215676},\n", " 'CM': {'0': {'-1': 34, '0': 53, '1': 45, '2': 40, '3': 9, '4': 3, '5': 2},\n", " '1': {'-1': 6, '0': 7, '1': 14, '2': 38, '3': 24, '4': 9, '5': 2},\n", @@ -2222,12 +3577,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12772994050372277,\n", " 'Micro-F1': 0.1643835616438356,\n", - " 'F1-0': 0.042105263157894736,\n", - " 'F1-1': 0.08791208791208792,\n", - " 'F1-2': 0.1893939393939394,\n", - " 'F1-3': 0.3020408163265306,\n", - " 'F1-4': 0.14492753623188406,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.042105263157894736,\n", + " 'F1-1_vs_rest': 0.08791208791208792,\n", + " 'F1-2_vs_rest': 0.1893939393939394,\n", + " 'F1-3_vs_rest': 0.3020408163265306,\n", + " 'F1-4_vs_rest': 0.14492753623188406,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78125,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6410256410256411,\n", + " 'F1-1.5': 0.676923076923077,\n", + " 'Recall-1.5': 0.9777777777777777,\n", + " 'Precision-1.5': 0.5176470588235295,\n", + " 'F1-2.5': 0.5492227979274611,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.3970037453183521,\n", + " 'F1-3.5': 0.1702127659574468,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.09523809523809523,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8816973338953877},\n", " 'CM': {'0': {'-1': 0, '0': 4, '1': 69, '2': 76, '3': 30, '4': 6, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 44, '3': 29, '4': 19, '5': 0},\n", @@ -2235,7 +3605,54 @@ " '3': {'-1': 0, '0': 0, '1': 0, '2': 13, '3': 37, '4': 54, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'fi': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0799419224278231,\n", + " 'fi': {'phi-4': {'metrics': {'Fleiss': 0.17799737596005955,\n", + " 'Cohen': 0.19335705812574144,\n", + " 'Spearman': 0.6342030573922413,\n", + " 'Kendall': 0.527903153069031,\n", + " 'Krippendorff': 0.5198763506255754,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7137254901960784,\n", + " 'TA-4.0': 0.8549019607843137,\n", + " 'Acc': 0.3568627450980392,\n", + " 'MAE': 0.9522875816993464,\n", + " 'MSE': 1.767320261437909,\n", + " 'CA-0': 0.41397849462365593,\n", + " 'CA-1': 0.25,\n", + " 'CA-2': 0.22857142857142856,\n", + " 'CA-3': 0.4807692307692308,\n", + " 'CA-4': 0.38461538461538464,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.30837214672726865,\n", + " 'Micro-F1': 0.3568627450980392,\n", + " 'F1-0_vs_rest': 0.5641025641025641,\n", + " 'F1-1_vs_rest': 0.25125628140703515,\n", + " 'F1-2_vs_rest': 0.2376237623762376,\n", + " 'F1-3_vs_rest': 0.3952569169960474,\n", + " 'F1-4_vs_rest': 0.11627906976744186,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.8406961178045516,\n", + " 'Recall-0.5': 0.9691358024691358,\n", + " 'Precision-0.5': 0.7423167848699763,\n", + " 'F1-1.5': 0.7518248175182481,\n", + " 'Recall-1.5': 0.9196428571428571,\n", + " 'Precision-1.5': 0.6358024691358025,\n", + " 'F1-2.5': 0.5722543352601156,\n", + " 'Recall-2.5': 0.8319327731092437,\n", + " 'Precision-2.5': 0.43612334801762115,\n", + " 'F1-3.5': 0.15053763440860216,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.08974358974358974,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", + " 'NDCG@all': 0.8894419543470243},\n", + " 'CM': {'0': {'-1': 0, '0': 77, '1': 59, '2': 28, '3': 16, '4': 4, '5': 2},\n", + " '1': {'-1': 0, '0': 7, '1': 25, '2': 30, '3': 25, '4': 13, '5': 0},\n", + " '2': {'-1': 1, '0': 3, '1': 10, '2': 24, '3': 50, '4': 17, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 5, '2': 15, '3': 50, '4': 33, '5': 1},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 8, '4': 5, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0799419224278231,\n", " 'Cohen': 0.12044397564366882,\n", " 'Spearman': 0.5693590267173353,\n", " 'Kendall': 0.48002557414113606,\n", @@ -2254,12 +3671,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.21649127412220284,\n", " 'Micro-F1': 0.2974559686888454,\n", - " 'F1-0': 0.25688073394495414,\n", - " 'F1-1': 0.2709677419354839,\n", - " 'F1-2': 0.3291139240506329,\n", - " 'F1-3': 0.39436619718309857,\n", - " 'F1-4': 0.047619047619047616,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.25688073394495414,\n", + " 'F1-1_vs_rest': 0.2709677419354839,\n", + " 'F1-2_vs_rest': 0.3291139240506329,\n", + " 'F1-3_vs_rest': 0.39436619718309857,\n", + " 'F1-4_vs_rest': 0.047619047619047616,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7985074626865671,\n", + " 'Recall-0.5': 0.9876923076923076,\n", + " 'Precision-0.5': 0.6701461377870563,\n", + " 'F1-1.5': 0.7368421052631579,\n", + " 'Recall-1.5': 0.8088888888888889,\n", + " 'Precision-1.5': 0.6765799256505576,\n", + " 'F1-2.5': 0.4980544747081712,\n", + " 'Recall-2.5': 0.5378151260504201,\n", + " 'Precision-2.5': 0.463768115942029,\n", + " 'F1-3.5': 0.13636363636363635,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.10344827586206896,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8868469034419542},\n", " 'CM': {'0': {'-1': 0, '0': 28, '1': 125, '2': 19, '3': 11, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 42, '2': 33, '3': 15, '4': 6, '5': 0},\n", @@ -2286,12 +3718,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.308828917505067,\n", " 'Micro-F1': 0.3933463796477495,\n", - " 'F1-0': 0.6482758620689655,\n", - " 'F1-1': 0.3605150214592275,\n", - " 'F1-2': 0.32989690721649484,\n", - " 'F1-3': 0.26285714285714284,\n", - " 'F1-4': 0.17142857142857143,\n", - " 'F1-5': 0.08,\n", + " 'F1-0_vs_rest': 0.6482758620689655,\n", + " 'F1-1_vs_rest': 0.3605150214592275,\n", + " 'F1-2_vs_rest': 0.32989690721649484,\n", + " 'F1-3_vs_rest': 0.26285714285714284,\n", + " 'F1-4_vs_rest': 0.17142857142857143,\n", + " 'F1-5_vs_rest': 0.08,\n", + " 'F1-0.5': 0.860655737704918,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.773955773955774,\n", + " 'F1-1.5': 0.7895791583166333,\n", + " 'Recall-1.5': 0.8755555555555555,\n", + " 'Precision-1.5': 0.718978102189781,\n", + " 'F1-2.5': 0.6163934426229508,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.5053763440860215,\n", + " 'F1-3.5': 0.16923076923076924,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.09565217391304348,\n", + " 'F1-4.5': 0.08,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.043478260869565216,\n", " 'NDCG@all': 0.8822406658180483},\n", " 'CM': {'0': {'-1': 0, '0': 94, '1': 67, '2': 13, '3': 5, '4': 3, '5': 4},\n", " '1': {'-1': 0, '0': 6, '1': 42, '2': 23, '3': 14, '4': 8, '5': 7},\n", @@ -2318,12 +3765,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.20850150035118534,\n", " 'Micro-F1': 0.2896281800391389,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.24778761061946902,\n", - " 'F1-2': 0.3904382470119522,\n", - " 'F1-3': 0.47572815533980584,\n", - " 'F1-4': 0.06451612903225806,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.24778761061946902,\n", + " 'F1-2_vs_rest': 0.3904382470119522,\n", + " 'F1-3_vs_rest': 0.47572815533980584,\n", + " 'F1-4_vs_rest': 0.06451612903225806,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7428571428571429,\n", + " 'Recall-1.5': 0.8088888888888889,\n", + " 'Precision-1.5': 0.6867924528301886,\n", + " 'F1-2.5': 0.5523012552301255,\n", + " 'Recall-2.5': 0.5546218487394958,\n", + " 'Precision-2.5': 0.55,\n", + " 'F1-3.5': 0.12121212121212122,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.1111111111111111,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8924107902654057},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 154, '2': 19, '3': 4, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 42, '2': 39, '3': 15, '4': 4, '5': 0},\n", @@ -2350,12 +3812,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.24081231461994299,\n", " 'Micro-F1': 0.3131115459882583,\n", - " 'F1-0': 0.5075757575757576,\n", - " 'F1-1': 0.2845528455284553,\n", - " 'F1-2': 0.21761658031088082,\n", - " 'F1-3': 0.27860696517412936,\n", - " 'F1-4': 0.1565217391304348,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5075757575757576,\n", + " 'F1-1_vs_rest': 0.2845528455284553,\n", + " 'F1-2_vs_rest': 0.21761658031088082,\n", + " 'F1-3_vs_rest': 0.27860696517412936,\n", + " 'F1-4_vs_rest': 0.1565217391304348,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8284960422163589,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7251732101616628,\n", + " 'F1-1.5': 0.7265625,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6480836236933798,\n", + " 'F1-2.5': 0.5893416927899686,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.47,\n", + " 'F1-3.5': 0.1864406779661017,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.10679611650485436,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9113634731999892},\n", " 'CM': {'0': {'-1': 0, '0': 67, '1': 78, '2': 30, '3': 7, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 35, '2': 26, '3': 20, '4': 14, '5': 0},\n", @@ -2382,12 +3859,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08338001255758522,\n", " 'Micro-F1': 0.10371819960861056,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07650273224043716,\n", - " 'F1-2': 0.16326530612244897,\n", - " 'F1-3': 0.1641025641025641,\n", - " 'F1-4': 0.08571428571428572,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07650273224043716,\n", + " 'F1-2_vs_rest': 0.16326530612244897,\n", + " 'F1-3_vs_rest': 0.1641025641025641,\n", + " 'F1-4_vs_rest': 0.08571428571428572,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6748466257668712,\n", + " 'Recall-1.5': 0.9777777777777777,\n", + " 'Precision-1.5': 0.5152224824355972,\n", + " 'F1-2.5': 0.5503685503685504,\n", + " 'Recall-2.5': 0.9411764705882353,\n", + " 'Precision-2.5': 0.3888888888888889,\n", + " 'F1-3.5': 0.10377358490566038,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.05583756345177665,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.89194524734931},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 71, '2': 84, '3': 19, '4': 11, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 28, '3': 23, '4': 42, '5': 0},\n", @@ -2414,12 +3906,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.14622383113860796,\n", " 'Micro-F1': 0.14145383104125736,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.05102040816326531,\n", - " 'F1-2': 0.17674418604651163,\n", - " 'F1-3': 0.28363636363636363,\n", - " 'F1-4': 0.11594202898550725,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.05102040816326531,\n", + " 'F1-2_vs_rest': 0.17674418604651163,\n", + " 'F1-3_vs_rest': 0.28363636363636363,\n", + " 'F1-4_vs_rest': 0.11594202898550725,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.7764423076923077,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6345776031434185,\n", + " 'F1-1.5': 0.7012578616352201,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.5399515738498789,\n", + " 'F1-2.5': 0.5463182897862233,\n", + " 'Recall-2.5': 0.9745762711864406,\n", + " 'Precision-2.5': 0.3795379537953795,\n", + " 'F1-3.5': 0.136986301369863,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07633587786259542,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.901604515831509},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 91, '2': 61, '3': 28, '4': 5, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 27, '3': 50, '4': 18, '5': 0},\n", @@ -2446,12 +3953,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.26503023089241634,\n", " 'Micro-F1': 0.3659491193737769,\n", - " 'F1-0': 0.3466666666666667,\n", - " 'F1-1': 0.2857142857142857,\n", - " 'F1-2': 0.45161290322580644,\n", - " 'F1-3': 0.4607329842931937,\n", - " 'F1-4': 0.045454545454545456,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3466666666666667,\n", + " 'F1-1_vs_rest': 0.2857142857142857,\n", + " 'F1-2_vs_rest': 0.45161290322580644,\n", + " 'F1-3_vs_rest': 0.4607329842931937,\n", + " 'F1-4_vs_rest': 0.045454545454545456,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8155583437892095,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6885593220338984,\n", + " 'F1-1.5': 0.7775628626692457,\n", + " 'Recall-1.5': 0.8933333333333333,\n", + " 'Precision-1.5': 0.6883561643835616,\n", + " 'F1-2.5': 0.6050420168067226,\n", + " 'Recall-2.5': 0.6050420168067226,\n", + " 'Precision-2.5': 0.6050420168067226,\n", + " 'F1-3.5': 0.0851063829787234,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.0625,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8987635078006797},\n", " 'CM': {'0': {'-1': 0, '0': 39, '1': 116, '2': 26, '3': 1, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 40, '2': 43, '3': 12, '4': 5, '5': 0},\n", @@ -2478,12 +4000,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08028613223589871,\n", " 'Micro-F1': 0.10666666666666667,\n", - " 'F1-0': 0.07058823529411765,\n", - " 'F1-1': 0.034482758620689655,\n", - " 'F1-2': 0.0594059405940594,\n", - " 'F1-3': 0.26785714285714285,\n", - " 'F1-4': 0.04938271604938271,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07058823529411765,\n", + " 'F1-1_vs_rest': 0.034482758620689655,\n", + " 'F1-2_vs_rest': 0.0594059405940594,\n", + " 'F1-3_vs_rest': 0.26785714285714285,\n", + " 'F1-4_vs_rest': 0.04938271604938271,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7835616438356164,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6441441441441441,\n", + " 'F1-1.5': 0.6319218241042345,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.46190476190476193,\n", + " 'F1-2.5': 0.47572815533980584,\n", + " 'Recall-2.5': 0.8596491228070176,\n", + " 'Precision-2.5': 0.3288590604026846,\n", + " 'F1-3.5': 0.06382978723404255,\n", + " 'Recall-3.5': 0.3,\n", + " 'Precision-3.5': 0.03571428571428571,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8257871100756643},\n", " 'CM': {'0': {'-1': 104, '0': 3, '1': 11, '2': 38, '3': 14, '4': 13, '5': 3},\n", " '1': {'-1': 54, '0': 0, '1': 1, '2': 12, '3': 12, '4': 18, '5': 3},\n", @@ -2491,6 +4028,53 @@ " '3': {'-1': 57, '0': 0, '1': 0, '2': 6, '3': 15, '4': 24, '5': 2},\n", " '4': {'-1': 3, '0': 0, '1': 0, '2': 2, '3': 5, '4': 2, '5': 1},\n", " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.08210228519360778,\n", + " 'Cohen': 0.1288029124834017,\n", + " 'Spearman': 0.6791722611224639,\n", + " 'Kendall': 0.582352940026658,\n", + " 'Krippendorff': 0.5755812159992642,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7519685039370079,\n", + " 'TA-4.0': 0.9547244094488189,\n", + " 'Acc': 0.3110236220472441,\n", + " 'MAE': 0.8149606299212596,\n", + " 'MSE': 1.0625546806649167,\n", + " 'CA-0': 0.17204301075268819,\n", + " 'CA-1': 0.32,\n", + " 'CA-2': 0.5754716981132075,\n", + " 'CA-3': 0.31683168316831684,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.22490900891205304,\n", + " 'Micro-F1': 0.3110236220472441,\n", + " 'F1-0_vs_rest': 0.2922374429223744,\n", + " 'F1-1_vs_rest': 0.23703703703703705,\n", + " 'F1-2_vs_rest': 0.3765432098765432,\n", + " 'F1-3_vs_rest': 0.36363636363636365,\n", + " 'F1-4_vs_rest': 0.08,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8055207026348808,\n", + " 'Recall-0.5': 0.9968944099378882,\n", + " 'Precision-0.5': 0.6757894736842105,\n", + " 'F1-1.5': 0.7741935483870968,\n", + " 'Recall-1.5': 0.918918918918919,\n", + " 'Precision-1.5': 0.6688524590163935,\n", + " 'F1-2.5': 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0.5,\n", " 'Macro-F1': 0.2635109597458267,\n", " 'Micro-F1': 0.29336188436830835,\n", - " 'F1-0': 0.40707964601769914,\n", - " 'F1-1': 0.16666666666666666,\n", - " 'F1-2': 0.32653061224489793,\n", - " 'F1-3': 0.34831460674157305,\n", - " 'F1-4': 0.08247422680412371,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.40707964601769914,\n", + " 'F1-1_vs_rest': 0.16666666666666666,\n", + " 'F1-2_vs_rest': 0.32653061224489793,\n", + " 'F1-3_vs_rest': 0.34831460674157305,\n", + " 'F1-4_vs_rest': 0.08247422680412371,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8107344632768362,\n", + " 'Recall-0.5': 0.9534883720930233,\n", + " 'Precision-0.5': 0.7051597051597052,\n", + " 'F1-1.5': 0.7537878787878788,\n", + " 'Recall-1.5': 0.9386792452830188,\n", + " 'Precision-1.5': 0.629746835443038,\n", + " 'F1-2.5': 0.6148409893992933,\n", + " 'Recall-2.5': 0.75,\n", + " 'Precision-2.5': 0.5209580838323353,\n", + " 'F1-3.5': 0.11428571428571428,\n", + " 'Recall-3.5': 0.46153846153846156,\n", + " 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0.4262295081967213,\n", - " 'F1-1': 0.3120567375886525,\n", - " 'F1-2': 0.37751004016064255,\n", - " 'F1-3': 0.4292682926829268,\n", - " 'F1-4': 0.10526315789473684,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4262295081967213,\n", + " 'F1-1_vs_rest': 0.3120567375886525,\n", + " 'F1-2_vs_rest': 0.37751004016064255,\n", + " 'F1-3_vs_rest': 0.4292682926829268,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8195876288659794,\n", + " 'Recall-0.5': 0.9814814814814815,\n", + " 'Precision-0.5': 0.7035398230088495,\n", + " 'F1-1.5': 0.7368421052631579,\n", + " 'Recall-1.5': 0.8125,\n", + " 'Precision-1.5': 0.674074074074074,\n", + " 'F1-2.5': 0.5224489795918368,\n", + " 'Recall-2.5': 0.5423728813559322,\n", + " 'Precision-2.5': 0.5039370078740157,\n", + " 'F1-3.5': 0.15,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.12,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 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0.696969696969697,\n", + " 'F1-2.5': 0.6012269938650306,\n", + " 'Recall-2.5': 0.8235294117647058,\n", + " 'Precision-2.5': 0.47342995169082125,\n", + " 'F1-3.5': 0.13836477987421383,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.0763888888888889,\n", + " 'F1-4.5': 0.11428571428571428,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.06060606060606061,\n", " 'NDCG@all': 0.8917784896472812},\n", " 'CM': {'0': {'-1': 0, '0': 80, '1': 76, '2': 13, '3': 6, '4': 7, '5': 4},\n", " '1': {'-1': 0, '0': 6, '1': 34, '2': 26, '3': 13, '4': 14, '5': 7},\n", @@ -3598,12 +6021,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.19820262856913248,\n", " 'Micro-F1': 0.27897838899803534,\n", - " 'F1-0': 0.05235602094240838,\n", - " 'F1-1': 0.2345679012345679,\n", - " 'F1-2': 0.3474576271186441,\n", - " 'F1-3': 0.5022026431718062,\n", - " 'F1-4': 0.05263157894736842,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.05235602094240838,\n", + " 'F1-1_vs_rest': 0.2345679012345679,\n", + " 'F1-2_vs_rest': 0.3474576271186441,\n", + " 'F1-3_vs_rest': 0.5022026431718062,\n", + " 'F1-4_vs_rest': 0.05263157894736842,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.781136638452237,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6408730158730159,\n", + " 'F1-1.5': 0.7554671968190855,\n", + " 'Recall-1.5': 0.852017937219731,\n", + " 'Precision-1.5': 0.6785714285714286,\n", + " 'F1-2.5': 0.599250936329588,\n", + " 'Recall-2.5': 0.6779661016949152,\n", + " 'Precision-2.5': 0.5369127516778524,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.08,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8975557679616587},\n", " 'CM': {'0': {'-1': 0, '0': 5, '1': 153, '2': 21, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 38, '2': 42, '3': 17, '4': 3, '5': 0},\n", @@ -3630,12 +6068,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.34525112736467684,\n", " 'Micro-F1': 0.34705882352941175,\n", - " 'F1-0': 0.5512367491166078,\n", - " 'F1-1': 0.28448275862068967,\n", - " 'F1-2': 0.21800947867298578,\n", - " 'F1-3': 0.34,\n", - " 'F1-4': 0.17777777777777778,\n", - " 'F1-5': 0.5,\n", + " 'F1-0_vs_rest': 0.5512367491166078,\n", + " 'F1-1_vs_rest': 0.28448275862068967,\n", + " 'F1-2_vs_rest': 0.21800947867298578,\n", + " 'F1-3_vs_rest': 0.34,\n", + " 'F1-4_vs_rest': 0.17777777777777778,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8276797829036635,\n", + " 'Recall-0.5': 0.941358024691358,\n", + " 'Precision-0.5': 0.738498789346247,\n", + " 'F1-1.5': 0.7326732673267327,\n", + " 'Recall-1.5': 0.8258928571428571,\n", + " 'Precision-1.5': 0.6583629893238434,\n", + " 'F1-2.5': 0.5850340136054422,\n", + " 'Recall-2.5': 0.7288135593220338,\n", + " 'Precision-2.5': 0.48863636363636365,\n", + " 'F1-3.5': 0.2127659574468085,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.12658227848101267,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", " 'NDCG@all': 0.9145076761966459},\n", " 'CM': {'0': {'-1': 0, '0': 78, '1': 69, '2': 26, '3': 9, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 10, '1': 33, '2': 33, '3': 14, '4': 10, '5': 0},\n", @@ -3662,12 +6115,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.055904766994553705,\n", " 'Micro-F1': 0.06862745098039216,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.03225806451612903,\n", - " 'F1-2': 0.06808510638297872,\n", - " 'F1-3': 0.14634146341463414,\n", - " 'F1-4': 0.07804878048780488,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.03225806451612903,\n", + " 'F1-2_vs_rest': 0.06808510638297872,\n", + " 'F1-3_vs_rest': 0.14634146341463414,\n", + " 'F1-4_vs_rest': 0.07804878048780488,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7779111644657863,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6365422396856582,\n", + " 'F1-1.5': 0.6707882534775889,\n", + " 'Recall-1.5': 0.96875,\n", + " 'Precision-1.5': 0.5130023640661938,\n", + " 'F1-2.5': 0.5048543689320388,\n", + " 'Recall-2.5': 0.8813559322033898,\n", + " 'Precision-2.5': 0.35374149659863946,\n", + " 'F1-3.5': 0.0966183574879227,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.052083333333333336,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8884000858698269},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 76, '2': 78, '3': 17, '4': 14, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 3, '2': 32, '3': 28, '4': 37, '5': 0},\n", @@ -3694,12 +6162,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.11878465200975445,\n", " 'Micro-F1': 0.10371819960861056,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.06030150753768844,\n", - " 'F1-2': 0.06,\n", - " 'F1-3': 0.22627737226277372,\n", - " 'F1-4': 0.11612903225806452,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.06030150753768844,\n", + " 'F1-2_vs_rest': 0.06,\n", + " 'F1-3_vs_rest': 0.22627737226277372,\n", + " 'F1-4_vs_rest': 0.11612903225806452,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6970172684458399,\n", + " 'Recall-1.5': 0.9866666666666667,\n", + " 'Precision-1.5': 0.5388349514563107,\n", + " 'F1-2.5': 0.5217391304347826,\n", + " 'Recall-2.5': 0.957983193277311,\n", + " 'Precision-2.5': 0.3584905660377358,\n", + " 'F1-3.5': 0.13496932515337423,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07432432432432433,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.9090243751659209},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 61, '3': 29, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 23, '3': 48, '4': 22, '5': 1},\n", @@ -3726,12 +6209,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.26116990944677254,\n", " 'Micro-F1': 0.3522504892367906,\n", - " 'F1-0': 0.33183856502242154,\n", - " 'F1-1': 0.27611940298507465,\n", - " 'F1-2': 0.4,\n", - " 'F1-3': 0.47572815533980584,\n", - " 'F1-4': 0.08333333333333333,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.33183856502242154,\n", + " 'F1-1_vs_rest': 0.27611940298507465,\n", + " 'F1-2_vs_rest': 0.4,\n", + " 'F1-3_vs_rest': 0.47572815533980584,\n", + " 'F1-4_vs_rest': 0.08333333333333333,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8135168961201502,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6856540084388185,\n", + " 'F1-1.5': 0.7909604519774012,\n", + " 'Recall-1.5': 0.9333333333333333,\n", + " 'Precision-1.5': 0.6862745098039216,\n", + " 'F1-2.5': 0.6015625,\n", + " 'Recall-2.5': 0.6470588235294118,\n", + " 'Precision-2.5': 0.5620437956204379,\n", + " 'F1-3.5': 0.12,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.08571428571428572,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9027732523608726},\n", " 'CM': {'0': {'-1': 0, '0': 37, '1': 116, '2': 26, '3': 3, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 37, '2': 48, '3': 11, '4': 4, '5': 0},\n", @@ -3758,12 +6256,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10242940245764282,\n", " 'Micro-F1': 0.11983471074380166,\n", - " 'F1-0': 0.08080808080808081,\n", - " 'F1-1': 0.08450704225352113,\n", - " 'F1-2': 0.2,\n", - " 'F1-3': 0.15217391304347827,\n", - " 'F1-4': 0.0970873786407767,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.08080808080808081,\n", + " 'F1-1_vs_rest': 0.08450704225352113,\n", + " 'F1-2_vs_rest': 0.2,\n", + " 'F1-3_vs_rest': 0.15217391304347827,\n", + " 'F1-4_vs_rest': 0.0970873786407767,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7636363636363637,\n", + " 'Recall-0.5': 0.9932432432432432,\n", + " 'Precision-0.5': 0.620253164556962,\n", + " 'F1-1.5': 0.643312101910828,\n", + " 'Recall-1.5': 0.9805825242718447,\n", + " 'Precision-1.5': 0.4786729857819905,\n", + " 'F1-2.5': 0.4953271028037383,\n", + " 'Recall-2.5': 0.9464285714285714,\n", + " 'Precision-2.5': 0.33544303797468356,\n", + " 'F1-3.5': 0.11475409836065574,\n", + " 'Recall-3.5': 0.6363636363636364,\n", + " 'Precision-3.5': 0.06306306306306306,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8384485864026487},\n", " 'CM': {'0': {'-1': 92, '0': 4, '1': 22, '2': 33, '3': 15, '4': 16, '5': 4},\n", " '1': {'-1': 55, '0': 0, '1': 3, '2': 9, '3': 10, '4': 20, '5': 3},\n", @@ -3771,6 +6284,53 @@ " '3': {'-1': 59, '0': 1, '1': 1, '2': 1, '3': 7, '4': 29, '5': 6},\n", " '4': {'-1': 3, '0': 0, '1': 0, '2': 0, '3': 3, '4': 5, '5': 2},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.12044377684393867,\n", + " 'Cohen': 0.15942500036934715,\n", + " 'Spearman': 0.6901680704518787,\n", + " 'Kendall': 0.5928388865688672,\n", + " 'Krippendorff': 0.5843584348092454,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7440944881889764,\n", + " 'TA-4.0': 0.9586614173228346,\n", + " 'Acc': 0.33858267716535434,\n", + " 'MAE': 0.7926509186351705,\n", + " 'MSE': 1.054680664916885,\n", + " 'CA-0': 0.20967741935483872,\n", + " 'CA-1': 0.26,\n", + " 'CA-2': 0.6037735849056604,\n", + " 'CA-3': 0.42574257425742573,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.23322815229152175,\n", + " 'Micro-F1': 0.33858267716535434,\n", + " 'F1-0_vs_rest': 0.3436123348017621,\n", + " 'F1-1_vs_rest': 0.203125,\n", + " 'F1-2_vs_rest': 0.4,\n", + " 'F1-3_vs_rest': 0.45263157894736844,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8111533586818758,\n", + " 'Recall-0.5': 0.9937888198757764,\n", + " 'Precision-0.5': 0.6852248394004282,\n", + " 'F1-1.5': 0.7729831144465291,\n", + " 'Recall-1.5': 0.9279279279279279,\n", + " 'Precision-1.5': 0.662379421221865,\n", + " 'F1-2.5': 0.5070422535211268,\n", + " 'Recall-2.5': 0.46551724137931033,\n", + " 'Precision-2.5': 0.5567010309278351,\n", + " 'F1-3.5': 0.08695652173913043,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.125,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.897331117844216},\n", + " 'CM': {'0': {'-1': 0, '0': 39, '1': 115, '2': 28, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 26, '2': 61, '3': 9, '4': 3, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 14, '2': 64, '3': 24, '4': 3, '5': 0},\n", + " '3': {'-1': 3, '0': 0, '1': 1, '2': 56, '3': 43, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08195292066259803,\n", " 'Cohen': 0.11068636548003341,\n", " 'Spearman': 0.6517214272250328,\n", @@ -3790,12 +6350,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2062197415218214,\n", " 'Micro-F1': 0.2692307692307692,\n", - " 'F1-0': 0.48,\n", - " 'F1-1': 0.16568047337278108,\n", - " 'F1-2': 0.30042918454935624,\n", - " 'F1-3': 0.21428571428571427,\n", - " 'F1-4': 0.07692307692307693,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.48,\n", + " 'F1-1_vs_rest': 0.16568047337278108,\n", + " 'F1-2_vs_rest': 0.30042918454935624,\n", + " 'F1-3_vs_rest': 0.21428571428571427,\n", + " 'F1-4_vs_rest': 0.07692307692307693,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8354430379746836,\n", + " 'Recall-0.5': 0.9642857142857143,\n", + " 'Precision-0.5': 0.7369727047146402,\n", + " 'F1-1.5': 0.7527675276752768,\n", + " 'Recall-1.5': 0.9444444444444444,\n", + " 'Precision-1.5': 0.6257668711656442,\n", + " 'F1-2.5': 0.6084142394822006,\n", + " 'Recall-2.5': 0.8103448275862069,\n", + " 'Precision-2.5': 0.48704663212435234,\n", + " 'F1-3.5': 0.09929078014184398,\n", + " 'Recall-3.5': 0.5,\n", + " 'Precision-3.5': 0.05511811023622047,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9027368881716582},\n", " 'CM': {'0': {'-1': 26, '0': 54, '1': 53, '2': 37, '3': 7, '4': 8, '5': 1},\n", " '1': {'-1': 8, '0': 9, '1': 14, '2': 40, '3': 13, '4': 15, '5': 1},\n", @@ -3822,12 +6397,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1295871688620951,\n", " 'Micro-F1': 0.1627450980392157,\n", - " 'F1-0': 0.0625,\n", - " 'F1-1': 0.07954545454545454,\n", - " 'F1-2': 0.16,\n", - " 'F1-3': 0.3148936170212766,\n", - " 'F1-4': 0.16058394160583941,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0625,\n", + " 'F1-1_vs_rest': 0.07954545454545454,\n", + " 'F1-2_vs_rest': 0.16,\n", + " 'F1-3_vs_rest': 0.3148936170212766,\n", + " 'F1-4_vs_rest': 0.16058394160583941,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.782608695652174,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6428571428571429,\n", + " 'F1-1.5': 0.6717791411042945,\n", + " 'Recall-1.5': 0.9776785714285714,\n", + " 'Precision-1.5': 0.5116822429906542,\n", + " 'F1-2.5': 0.5464190981432361,\n", + " 'Recall-2.5': 0.8728813559322034,\n", + " 'Precision-2.5': 0.39768339768339767,\n", + " 'F1-3.5': 0.18309859154929578,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.10236220472440945,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.876186125820189},\n", " 'CM': {'0': {'-1': 0, '0': 6, '1': 64, '2': 85, '3': 22, '4': 8, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 47, '3': 25, '4': 20, '5': 1},\n", @@ -3835,647 +6425,1182 @@ " '3': {'-1': 1, '0': 0, '1': 0, '2': 15, '3': 37, '4': 51, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 11, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'mt': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08897789049454477,\n", - " 'Cohen': 0.1288782816229117,\n", - " 'Spearman': 0.5451741762114075,\n", - " 'Kendall': 0.460578042092817,\n", - " 'Krippendorff': 0.4477467367736032,\n", - " 'Invalid': 0,\n", - " 'TA-2.0': 0.6888454011741683,\n", - " 'TA-4.0': 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0.09264381499247225,\n", " 'Cohen': 0.1336004737842562,\n", " 'Spearman': 0.5901238831650634,\n", " 'Kendall': 0.49887871329901307,\n", @@ -4494,12 +7619,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2329918916584107,\n", " 'Micro-F1': 0.30528375733855184,\n", - " 'F1-0': 0.19138755980861244,\n", - " 'F1-1': 0.27303754266211605,\n", - " 'F1-2': 0.33204633204633205,\n", - " 'F1-3': 0.46511627906976744,\n", - " 'F1-4': 0.13636363636363635,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.19138755980861244,\n", + " 'F1-1_vs_rest': 0.27303754266211605,\n", + " 'F1-2_vs_rest': 0.33204633204633205,\n", + " 'F1-3_vs_rest': 0.46511627906976744,\n", + " 'F1-4_vs_rest': 0.13636363636363635,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7921279212792128,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.6598360655737705,\n", + " 'F1-1.5': 0.7384615384615385,\n", + " 'Recall-1.5': 0.8533333333333334,\n", + " 'Precision-1.5': 0.6508474576271186,\n", + " 'F1-2.5': 0.5517241379310345,\n", + " 'Recall-2.5': 0.6050420168067226,\n", + " 'Precision-2.5': 0.5070422535211268,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.12903225806451613,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8866148012660774},\n", " 'CM': {'0': {'-1': 0, '0': 20, '1': 120, '2': 38, '3': 5, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 40, '2': 38, '3': 11, '4': 8, '5': 0},\n", @@ -4526,12 +7666,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.3432992621756135,\n", " 'Micro-F1': 0.4207436399217221,\n", - " 'F1-0': 0.6552901023890785,\n", - " 'F1-1': 0.35807860262008734,\n", - " 'F1-2': 0.4117647058823529,\n", - " 'F1-3': 0.3125,\n", - " 'F1-4': 0.16216216216216217,\n", - " 'F1-5': 0.16,\n", + " 'F1-0_vs_rest': 0.6552901023890785,\n", + " 'F1-1_vs_rest': 0.35807860262008734,\n", + " 'F1-2_vs_rest': 0.4117647058823529,\n", + " 'F1-3_vs_rest': 0.3125,\n", + " 'F1-4_vs_rest': 0.16216216216216217,\n", + " 'F1-5_vs_rest': 0.16,\n", + " 'F1-0.5': 0.8614540466392319,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7772277227722773,\n", + " 'F1-1.5': 0.792,\n", + " 'Recall-1.5': 0.88,\n", + " 'Precision-1.5': 0.72,\n", + " 'F1-2.5': 0.6351351351351351,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.5310734463276836,\n", + " 'F1-3.5': 0.16176470588235295,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.09090909090909091,\n", + " 'F1-4.5': 0.16,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.08695652173913043,\n", " 'NDCG@all': 0.8878365114993971},\n", " 'CM': {'0': {'-1': 0, '0': 96, '1': 64, '2': 12, '3': 6, '4': 5, '5': 3},\n", " '1': {'-1': 0, '0': 8, '1': 41, '2': 24, '3': 9, '4': 11, '5': 7},\n", @@ -4558,12 +7713,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.209938145817518,\n", " 'Micro-F1': 0.30724070450097846,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.29608938547486036,\n", - " 'F1-2': 0.4052863436123348,\n", - " 'F1-3': 0.4857142857142857,\n", - " 'F1-4': 0.0,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.29608938547486036,\n", + " 'F1-2_vs_rest': 0.4052863436123348,\n", + " 'F1-3_vs_rest': 0.4857142857142857,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7515923566878981,\n", + " 'Recall-1.5': 0.7866666666666666,\n", + " 'Precision-1.5': 0.7195121951219512,\n", + " 'F1-2.5': 0.5819672131147541,\n", + " 'Recall-2.5': 0.5966386554621849,\n", + " 'Precision-2.5': 0.568,\n", + " 'F1-3.5': 0.058823529411764705,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.05263157894736842,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8938653525989312},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 157, '2': 15, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 53, '2': 28, '3': 17, '4': 2, '5': 0},\n", @@ -4590,12 +7760,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2520687641256895,\n", " 'Micro-F1': 0.3268101761252446,\n", - " 'F1-0': 0.5263157894736842,\n", - " 'F1-1': 0.29535864978902954,\n", - " 'F1-2': 0.25870646766169153,\n", - " 'F1-3': 0.2694300518134715,\n", - " 'F1-4': 0.16260162601626016,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5263157894736842,\n", + " 'F1-1_vs_rest': 0.29535864978902954,\n", + " 'F1-2_vs_rest': 0.25870646766169153,\n", + " 'F1-3_vs_rest': 0.2694300518134715,\n", + " 'F1-4_vs_rest': 0.16260162601626016,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8333333333333334,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7308584686774942,\n", + " 'F1-1.5': 0.7552986512524085,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.6666666666666666,\n", + " 'F1-2.5': 0.5911949685534591,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.4723618090452261,\n", + " 'F1-3.5': 0.192,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.10909090909090909,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9076025346217166},\n", " 'CM': {'0': {'-1': 0, '0': 70, '1': 78, '2': 24, '3': 8, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 35, '2': 28, '3': 18, '4': 14, '5': 0},\n", @@ -4622,12 +7807,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07678393552730602,\n", " 'Micro-F1': 0.09393346379647749,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.09278350515463918,\n", - " 'F1-2': 0.12173913043478261,\n", - " 'F1-3': 0.15228426395939088,\n", - " 'F1-4': 0.09389671361502347,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.09278350515463918,\n", + " 'F1-2_vs_rest': 0.12173913043478261,\n", + " 'F1-3_vs_rest': 0.15228426395939088,\n", + " 'F1-4_vs_rest': 0.09389671361502347,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6853582554517134,\n", + " 'Recall-1.5': 0.9777777777777777,\n", + " 'Precision-1.5': 0.5275779376498801,\n", + " 'F1-2.5': 0.5436893203883495,\n", + " 'Recall-2.5': 0.9411764705882353,\n", + " 'Precision-2.5': 0.3822525597269625,\n", + " 'F1-3.5': 0.11162790697674418,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.06,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8918955183734459},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 80, '2': 74, '3': 16, '4': 16, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 31, '3': 26, '4': 34, '5': 0},\n", @@ -4654,12 +7854,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.14453821186992102,\n", " 'Micro-F1': 0.12770137524557956,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.047619047619047616,\n", - " 'F1-2': 0.13270142180094788,\n", - " 'F1-3': 0.27169811320754716,\n", - " 'F1-4': 0.12949640287769784,\n", - " 'F1-5': 0.2857142857142857,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.047619047619047616,\n", + " 'F1-2_vs_rest': 0.13270142180094788,\n", + " 'F1-3_vs_rest': 0.27169811320754716,\n", + " 'F1-4_vs_rest': 0.12949640287769784,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.7764423076923077,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6345776031434185,\n", + " 'F1-1.5': 0.7106109324758842,\n", + " 'Recall-1.5': 0.9866071428571429,\n", + " 'Precision-1.5': 0.5552763819095478,\n", + " 'F1-2.5': 0.5547445255474452,\n", + " 'Recall-2.5': 0.957983193277311,\n", + " 'Precision-2.5': 0.3904109589041096,\n", + " 'F1-3.5': 0.1506849315068493,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08396946564885496,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", " 'NDCG@all': 0.9083473712991376},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 103, '2': 55, '3': 23, '4': 5, '5': 0},\n", " '1': {'-1': 1, '0': 0, '1': 5, '2': 34, '3': 38, '4': 21, '5': 1},\n", @@ -4686,12 +7901,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.28406014749821173,\n", " 'Micro-F1': 0.37573385518590996,\n", - " 'F1-0': 0.4034334763948498,\n", - " 'F1-1': 0.28679245283018867,\n", - " 'F1-2': 0.39543726235741444,\n", - " 'F1-3': 0.48826291079812206,\n", - " 'F1-4': 0.13043478260869565,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4034334763948498,\n", + " 'F1-1_vs_rest': 0.28679245283018867,\n", + " 'F1-2_vs_rest': 0.39543726235741444,\n", + " 'F1-3_vs_rest': 0.48826291079812206,\n", + " 'F1-4_vs_rest': 0.13043478260869565,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8238276299112801,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.7004310344827587,\n", + " 'F1-1.5': 0.7862595419847328,\n", + " 'Recall-1.5': 0.9155555555555556,\n", + " 'Precision-1.5': 0.6889632107023411,\n", + " 'F1-2.5': 0.5823754789272031,\n", + " 'Recall-2.5': 0.6386554621848739,\n", + " 'Precision-2.5': 0.5352112676056338,\n", + " 'F1-3.5': 0.16666666666666666,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.12121212121212122,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8926975976009004},\n", " 'CM': {'0': {'-1': 0, '0': 47, '1': 108, '2': 21, '3': 5, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 38, '2': 44, '3': 12, '4': 6, '5': 0},\n", @@ -4718,12 +7948,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.23121198461203488,\n", " 'Micro-F1': 0.23737373737373738,\n", - " 'F1-0': 0.2,\n", - " 'F1-1': 0.16129032258064516,\n", - " 'F1-2': 0.2553191489361702,\n", - " 'F1-3': 0.3516483516483517,\n", - " 'F1-4': 0.16901408450704225,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.2,\n", + " 'F1-1_vs_rest': 0.16129032258064516,\n", + " 'F1-2_vs_rest': 0.2553191489361702,\n", + " 'F1-3_vs_rest': 0.3516483516483517,\n", + " 'F1-4_vs_rest': 0.16901408450704225,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8282208588957055,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.7068062827225131,\n", + " 'F1-1.5': 0.7348484848484849,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.5808383233532934,\n", + " 'F1-2.5': 0.5764705882352941,\n", + " 'Recall-2.5': 0.8448275862068966,\n", + " 'Precision-2.5': 0.4375,\n", + " 'F1-3.5': 0.17721518987341772,\n", + " 'Recall-3.5': 0.7777777777777778,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.14285714285714285,\n", " 'NDCG@all': 0.87948982617392},\n", " 'CM': {'0': {'-1': 123, '0': 7, '1': 19, '2': 21, '3': 7, '4': 9, '5': 0},\n", " '1': {'-1': 62, '0': 0, '1': 5, '2': 13, '3': 10, '4': 9, '5': 1},\n", @@ -4731,6 +7976,53 @@ " '3': {'-1': 55, '0': 0, '1': 0, '2': 7, '3': 16, '4': 24, '5': 2},\n", " '4': {'-1': 5, '0': 0, '1': 0, '2': 2, '3': 0, '4': 6, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13116213395543003,\n", + " 'Cohen': 0.1662575602859162,\n", + " 'Spearman': 0.6774188380645677,\n", + " 'Kendall': 0.5804370428335067,\n", + " 'Krippendorff': 0.5871734481408813,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7392156862745098,\n", + " 'TA-4.0': 0.9647058823529412,\n", + " 'Acc': 0.34705882352941175,\n", + " 'MAE': 0.7843137254901957,\n", + " 'MSE': 1.0348583877995639,\n", + " 'CA-0': 0.25268817204301075,\n", + " 'CA-1': 0.26,\n", + " 'CA-2': 0.5943396226415094,\n", + " 'CA-3': 0.3883495145631068,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.25450561451111653,\n", + " 'Micro-F1': 0.34705882352941175,\n", + " 'F1-0_vs_rest': 0.3983050847457627,\n", + " 'F1-1_vs_rest': 0.2047244094488189,\n", + " 'F1-2_vs_rest': 0.39622641509433965,\n", + " 'F1-3_vs_rest': 0.4166666666666667,\n", + " 'F1-4_vs_rest': 0.1111111111111111,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8188775510204082,\n", + " 'Recall-0.5': 0.9907407407407407,\n", + " 'Precision-0.5': 0.6978260869565217,\n", + " 'F1-1.5': 0.769811320754717,\n", + " 'Recall-1.5': 0.9107142857142857,\n", + " 'Precision-1.5': 0.6666666666666666,\n", + " 'F1-2.5': 0.4716981132075472,\n", + " 'Recall-2.5': 0.423728813559322,\n", + " 'Precision-2.5': 0.5319148936170213,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9049197837525359},\n", + " 'CM': {'0': {'-1': 0, '0': 47, '1': 109, '2': 26, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 26, '2': 59, '3': 13, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 15, '2': 63, '3': 24, '4': 3, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 4, '2': 58, '3': 40, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 6, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1633776573219277,\n", " 'Cohen': 0.18360137869391402,\n", " 'Spearman': 0.6383587604624152,\n", @@ -4750,12 +8042,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.29901603641894925,\n", " 'Micro-F1': 0.33853006681514475,\n", - " 'F1-0': 0.5110132158590308,\n", - " 'F1-1': 0.25,\n", - " 'F1-2': 0.36123348017621143,\n", - " 'F1-3': 0.30864197530864196,\n", - " 'F1-4': 0.11320754716981132,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.5110132158590308,\n", + " 'F1-1_vs_rest': 0.25,\n", + " 'F1-2_vs_rest': 0.36123348017621143,\n", + " 'F1-3_vs_rest': 0.30864197530864196,\n", + " 'F1-4_vs_rest': 0.11320754716981132,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.834575260804769,\n", + " 'Recall-0.5': 0.9459459459459459,\n", + " 'Precision-0.5': 0.7466666666666667,\n", + " 'F1-1.5': 0.7634194831013916,\n", + " 'Recall-1.5': 0.9142857142857143,\n", + " 'Precision-1.5': 0.6552901023890785,\n", + " 'F1-2.5': 0.6376811594202898,\n", + " 'Recall-2.5': 0.7586206896551724,\n", + " 'Precision-2.5': 0.55,\n", + " 'F1-3.5': 0.14035087719298245,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.08080808080808081,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.910262404250484},\n", " 'CM': {'0': {'-1': 33, '0': 58, '1': 53, '2': 30, '3': 6, '4': 6, '5': 0},\n", " '1': {'-1': 14, '0': 6, '1': 21, '2': 38, '3': 9, '4': 11, '5': 1},\n", @@ -4782,12 +8089,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.13297289457508324,\n", " 'Micro-F1': 0.16634050880626222,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.10204081632653061,\n", - " 'F1-2': 0.20392156862745098,\n", - " 'F1-3': 0.2794759825327511,\n", - " 'F1-4': 0.13986013986013987,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.10204081632653061,\n", + " 'F1-2_vs_rest': 0.20392156862745098,\n", + " 'F1-3_vs_rest': 0.2794759825327511,\n", + " 'F1-4_vs_rest': 0.13986013986013987,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.6856240126382307,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5318627450980392,\n", + " 'F1-2.5': 0.5608465608465608,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.4092664092664093,\n", + " 'F1-3.5': 0.1610738255033557,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08955223880597014,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.876696521829403},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 78, '2': 73, '3': 20, '4': 7, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 10, '2': 39, '3': 30, '4': 19, '5': 2},\n", @@ -4795,327 +8117,618 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 11, '3': 32, '4': 59, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'mk': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09469032527669412,\n", - " 'Cohen': 0.12589213663401744,\n", - " 'Spearman': 0.5816396163701059,\n", - " 'Kendall': 0.4908832375324907,\n", - " 'Krippendorff': 0.5029280236862802,\n", + " 'mk': {'phi-4': {'metrics': {'Fleiss': 0.1999462797482112,\n", + " 'Cohen': 0.20991850829407743,\n", + " 'Spearman': 0.6127020778469268,\n", + " 'Kendall': 0.5109324902946139,\n", + " 'Krippendorff': 0.55607580063667,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7151277013752456,\n", + " 'TA-4.0': 0.888015717092338,\n", + " 'Acc': 0.3791748526522593,\n", + " 'MAE': 0.8732809430255403,\n", + " 'MSE': 1.5060576293385721,\n", + " 'CA-0': 0.46774193548387094,\n", + " 'CA-1': 0.28,\n", + " 'CA-2': 0.29523809523809524,\n", + " 'CA-3': 0.4174757281553398,\n", + " 'CA-4': 0.23076923076923078,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.35430055077942396,\n", + " 'Micro-F1': 0.3791748526522593,\n", + " 'F1-0_vs_rest': 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'5': 0}}}},\n", - " 'sv': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0953309728140191,\n", + " 'sv': {'phi-4': {'metrics': {'Fleiss': 0.22190244554852706,\n", + " 'Cohen': 0.23316881709406723,\n", + " 'Spearman': 0.6409972792070059,\n", + " 'Kendall': 0.5364517240781522,\n", + " 'Krippendorff': 0.5507744996003143,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7254901960784313,\n", + " 'TA-4.0': 0.8823529411764706,\n", + " 'Acc': 0.396078431372549,\n", + " 'MAE': 0.89281045751634,\n", + " 'MSE': 1.6542483660130722,\n", + " 'CA-0': 0.4731182795698925,\n", + " 'CA-1': 0.24,\n", + " 'CA-2': 0.2641509433962264,\n", + " 'CA-3': 0.5436893203883495,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2892500564813452,\n", + " 'Micro-F1': 0.396078431372549,\n", + " 'F1-0_vs_rest': 0.6068965517241379,\n", + " 'F1-1_vs_rest': 0.24870466321243523,\n", + " 'F1-2_vs_rest': 0.2814070351758794,\n", + " 'F1-3_vs_rest': 0.43410852713178294,\n", + " 'F1-4_vs_rest': 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'1': 0, '2': 0, '3': 7, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0953309728140191,\n", " 'Cohen': 0.13102335121944186,\n", " 'Spearman': 0.5844193624778261,\n", " 'Kendall': 0.492311755374174,\n", @@ -5134,12 +8747,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22982093575208573,\n", " 'Micro-F1': 0.30724070450097846,\n", - " 'F1-0': 0.28054298642533937,\n", - " 'F1-1': 0.2653061224489796,\n", - " 'F1-2': 0.3037974683544304,\n", - " 'F1-3': 0.43171806167400884,\n", - " 'F1-4': 0.0975609756097561,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.28054298642533937,\n", + " 'F1-1_vs_rest': 0.2653061224489796,\n", + " 'F1-2_vs_rest': 0.3037974683544304,\n", + " 'F1-3_vs_rest': 0.43171806167400884,\n", + " 'F1-4_vs_rest': 0.0975609756097561,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8014981273408239,\n", + " 'Recall-0.5': 0.9876923076923076,\n", + " 'Precision-0.5': 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'F1-0_vs_rest': 0.6508474576271186,\n", + " 'F1-1_vs_rest': 0.3211009174311927,\n", + " 'F1-2_vs_rest': 0.39195979899497485,\n", + " 'F1-3_vs_rest': 0.29411764705882354,\n", + " 'F1-4_vs_rest': 0.1651376146788991,\n", + " 'F1-5_vs_rest': 0.06451612903225806,\n", + " 'F1-0.5': 0.8583218707015131,\n", + " 'Recall-0.5': 0.96,\n", + " 'Precision-0.5': 0.7761194029850746,\n", + " 'F1-1.5': 0.793713163064833,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.7112676056338029,\n", + " 'F1-2.5': 0.6258064516129033,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.5078534031413613,\n", + " 'F1-3.5': 0.17142857142857143,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.096,\n", + " 'F1-4.5': 0.06451612903225806,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.034482758620689655,\n", " 'NDCG@all': 0.8879430038363442},\n", " 'CM': {'0': {'-1': 0, '0': 96, '1': 62, '2': 13, '3': 9, '4': 2, '5': 4},\n", " '1': {'-1': 0, '0': 11, '1': 35, '2': 22, '3': 12, '4': 13, '5': 7},\n", @@ -5198,12 +8841,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2360211031384666,\n", " 'Micro-F1': 0.33072407045009783,\n", - " 'F1-0': 0.1306532663316583,\n", - " 'F1-1': 0.3170028818443804,\n", - " 'F1-2': 0.37668161434977576,\n", - " 'F1-3': 0.5272727272727272,\n", - " 'F1-4': 0.06451612903225806,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.1306532663316583,\n", + " 'F1-1_vs_rest': 0.3170028818443804,\n", + " 'F1-2_vs_rest': 0.37668161434977576,\n", + " 'F1-3_vs_rest': 0.5272727272727272,\n", + " 'F1-4_vs_rest': 0.06451612903225806,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7897934386391251,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6526104417670683,\n", + " 'F1-1.5': 0.7815126050420168,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.7410358565737052,\n", + " 'F1-2.5': 0.5928853754940712,\n", + " 'Recall-2.5': 0.6302521008403361,\n", + " 'Precision-2.5': 0.5597014925373134,\n", + " 'F1-3.5': 0.12121212121212122,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.1111111111111111,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.895974309785504},\n", " 'CM': {'0': {'-1': 0, '0': 13, '1': 153, '2': 13, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 55, '2': 29, '3': 14, '4': 2, '5': 0},\n", @@ -5230,12 +8888,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2500912083595594,\n", " 'Micro-F1': 0.3287671232876712,\n", - " 'F1-0': 0.5056603773584906,\n", - " 'F1-1': 0.30952380952380953,\n", - " 'F1-2': 0.19672131147540983,\n", - " 'F1-3': 0.3444976076555024,\n", - " 'F1-4': 0.14414414414414414,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5056603773584906,\n", + " 'F1-1_vs_rest': 0.30952380952380953,\n", + " 'F1-2_vs_rest': 0.19672131147540983,\n", + " 'F1-3_vs_rest': 0.3444976076555024,\n", + " 'F1-4_vs_rest': 0.14414414414414414,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8269484808454426,\n", + " 'Recall-0.5': 0.963076923076923,\n", + " 'Precision-0.5': 0.7245370370370371,\n", + " 'F1-1.5': 0.7564356435643564,\n", + " 'Recall-1.5': 0.8488888888888889,\n", + " 'Precision-1.5': 0.6821428571428572,\n", + " 'F1-2.5': 0.6149068322981367,\n", + " 'Recall-2.5': 0.8319327731092437,\n", + " 'Precision-2.5': 0.4876847290640394,\n", + " 'F1-3.5': 0.17699115044247787,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.10204081632653061,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9068802351548026},\n", " 'CM': {'0': {'-1': 0, '0': 67, '1': 84, '2': 21, '3': 8, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 7, '1': 39, '2': 27, '3': 15, '4': 12, '5': 0},\n", @@ -5262,12 +8935,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08431521103171968,\n", " 'Micro-F1': 0.10371819960861056,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07142857142857142,\n", - " 'F1-2': 0.1643835616438356,\n", - " 'F1-3': 0.15609756097560976,\n", - " 'F1-4': 0.10328638497652583,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07142857142857142,\n", + " 'F1-2_vs_rest': 0.1643835616438356,\n", + " 'F1-3_vs_rest': 0.15609756097560976,\n", + " 'F1-4_vs_rest': 0.10328638497652583,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6917057902973396,\n", + " 'Recall-1.5': 0.9822222222222222,\n", + " 'Precision-1.5': 0.533816425120773,\n", + " 'F1-2.5': 0.5333333333333333,\n", + " 'Recall-2.5': 0.9411764705882353,\n", + " 'Precision-2.5': 0.37209302325581395,\n", + " 'F1-3.5': 0.12093023255813953,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.065,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8924085658101588},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 85, '2': 59, '3': 25, '4': 16, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 31, '3': 29, '4': 33, '5': 0},\n", @@ -5294,12 +8982,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10720819208284883,\n", " 'Micro-F1': 0.1411764705882353,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.0660377358490566,\n", - " 'F1-2': 0.18779342723004694,\n", - " 'F1-3': 0.2857142857142857,\n", - " 'F1-4': 0.1037037037037037,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.0660377358490566,\n", + " 'F1-2_vs_rest': 0.18779342723004694,\n", + " 'F1-3_vs_rest': 0.2857142857142857,\n", + " 'F1-4_vs_rest': 0.1037037037037037,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.7138263665594855,\n", + " 'Recall-1.5': 0.9910714285714286,\n", + " 'Precision-1.5': 0.5577889447236181,\n", + " 'F1-2.5': 0.5672371638141809,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.4,\n", + " 'F1-3.5': 0.13986013986013987,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.078125,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9045519607350617},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 103, '2': 56, '3': 22, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 30, '3': 45, '4': 17, '5': 1},\n", @@ -5326,12 +9029,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.27130397419715363,\n", " 'Micro-F1': 0.37377690802348335,\n", - " 'F1-0': 0.37554585152838427,\n", - " 'F1-1': 0.28044280442804426,\n", - " 'F1-2': 0.3968253968253968,\n", - " 'F1-3': 0.5315315315315315,\n", - " 'F1-4': 0.043478260869565216,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.37554585152838427,\n", + " 'F1-1_vs_rest': 0.28044280442804426,\n", + " 'F1-2_vs_rest': 0.3968253968253968,\n", + " 'F1-3_vs_rest': 0.5315315315315315,\n", + " 'F1-4_vs_rest': 0.043478260869565216,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.819672131147541,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6944444444444444,\n", + " 'F1-1.5': 0.7739463601532567,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.6801346801346801,\n", + " 'F1-2.5': 0.6444444444444445,\n", + " 'Recall-2.5': 0.7310924369747899,\n", + " 'Precision-2.5': 0.5761589403973509,\n", + " 'F1-3.5': 0.08333333333333333,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.06060606060606061,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8975530038634952},\n", " 'CM': {'0': {'-1': 0, '0': 43, '1': 110, '2': 26, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 38, '2': 42, '3': 12, '4': 8, '5': 0},\n", @@ -5358,12 +9076,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09070374070374071,\n", " 'Micro-F1': 0.11170212765957446,\n", - " 'F1-0': 0.07792207792207792,\n", - " 'F1-1': 0.08333333333333333,\n", - " 'F1-2': 0.17582417582417584,\n", - " 'F1-3': 0.17142857142857143,\n", - " 'F1-4': 0.03571428571428571,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07792207792207792,\n", + " 'F1-1_vs_rest': 0.08333333333333333,\n", + " 'F1-2_vs_rest': 0.17582417582417584,\n", + " 'F1-3_vs_rest': 0.17142857142857143,\n", + " 'F1-4_vs_rest': 0.03571428571428571,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7625418060200669,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6162162162162163,\n", + " 'F1-1.5': 0.6696035242290749,\n", + " 'Recall-1.5': 0.9743589743589743,\n", + " 'Precision-1.5': 0.5100671140939598,\n", + " 'F1-2.5': 0.4117647058823529,\n", + " 'Recall-2.5': 0.7368421052631579,\n", + " 'Precision-2.5': 0.2857142857142857,\n", + " 'F1-3.5': 0.06060606060606061,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.03278688524590164,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8562739565927192},\n", " 'CM': {'0': {'-1': 112, '0': 3, '1': 31, '2': 26, '3': 8, '4': 5, '5': 1},\n", " '1': {'-1': 64, '0': 0, '1': 3, '2': 8, '3': 9, '4': 14, '5': 2},\n", @@ -5371,6 +9104,53 @@ " '3': {'-1': 71, '0': 0, '1': 1, '2': 6, '3': 6, '4': 17, '5': 3},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 3, '3': 0, '4': 1, '5': 1},\n", " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.12878305028989678,\n", + " 'Cohen': 0.1652203463288745,\n", + " 'Spearman': 0.6829730918908239,\n", + " 'Kendall': 0.5860764105625597,\n", + " 'Krippendorff': 0.5910578537109343,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.7465618860510805,\n", + " 'TA-4.0': 0.9607072691552063,\n", + " 'Acc': 0.34577603143418467,\n", + " 'MAE': 0.7819253438113946,\n", + " 'MSE': 1.0316524776249725,\n", + " 'CA-0': 0.24193548387096775,\n", + " 'CA-1': 0.3,\n", + " 'CA-2': 0.5943396226415094,\n", + " 'CA-3': 0.37254901960784315,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.23627587639892403,\n", + " 'Micro-F1': 0.34577603143418467,\n", + " 'F1-0_vs_rest': 0.38461538461538464,\n", + " 'F1-1_vs_rest': 0.23255813953488372,\n", + " 'F1-2_vs_rest': 0.39622641509433965,\n", + " 'F1-3_vs_rest': 0.40425531914893614,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8163265306122449,\n", + " 'Recall-0.5': 0.9907120743034056,\n", + " 'Precision-0.5': 0.6941431670281996,\n", + " 'F1-1.5': 0.779467680608365,\n", + " 'Recall-1.5': 0.9192825112107623,\n", + " 'Precision-1.5': 0.6765676567656765,\n", + " 'F1-2.5': 0.47115384615384615,\n", + " 'Recall-2.5': 0.4188034188034188,\n", + " 'Precision-2.5': 0.5384615384615384,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8884655583516098},\n", + " 'CM': {'0': {'-1': 0, '0': 45, '1': 111, '2': 27, '3': 2, '4': 1, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 30, '2': 58, '3': 8, '4': 2, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 13, '2': 63, '3': 28, '4': 1, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 4, '2': 59, '3': 38, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1507098993034647,\n", " 'Cohen': 0.169010889292196,\n", " 'Spearman': 0.6237927948607579,\n", @@ -5390,12 +9170,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2893074848531905,\n", " 'Micro-F1': 0.3310810810810811,\n", - " 'F1-0': 0.5087719298245614,\n", - " 'F1-1': 0.1518987341772152,\n", - " 'F1-2': 0.3620689655172414,\n", - " 'F1-3': 0.3393939393939394,\n", - " 'F1-4': 0.12371134020618557,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.5087719298245614,\n", + " 'F1-1_vs_rest': 0.1518987341772152,\n", + " 'F1-2_vs_rest': 0.3620689655172414,\n", + " 'F1-3_vs_rest': 0.3393939393939394,\n", + " 'F1-4_vs_rest': 0.12371134020618557,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8303030303030303,\n", + " 'Recall-0.5': 0.9415807560137457,\n", + " 'Precision-0.5': 0.7425474254742548,\n", + " 'F1-1.5': 0.7609561752988048,\n", + " 'Recall-1.5': 0.9052132701421801,\n", + " 'Precision-1.5': 0.6563573883161512,\n", + " 'F1-2.5': 0.6,\n", + " 'Recall-2.5': 0.7105263157894737,\n", + " 'Precision-2.5': 0.5192307692307693,\n", + " 'F1-3.5': 0.17142857142857143,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.9131769794503989},\n", " 'CM': {'0': {'-1': 33, '0': 58, '1': 53, '2': 30, '3': 6, '4': 6, '5': 0},\n", " '1': {'-1': 20, '0': 10, '1': 12, '2': 34, '3': 16, '4': 7, '5': 1},\n", @@ -5422,12 +9217,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1168622935202779,\n", " 'Micro-F1': 0.14285714285714285,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.09230769230769231,\n", - " 'F1-2': 0.12244897959183673,\n", - " 'F1-3': 0.25217391304347825,\n", - " 'F1-4': 0.14193548387096774,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.09230769230769231,\n", + " 'F1-2_vs_rest': 0.12244897959183673,\n", + " 'F1-3_vs_rest': 0.25217391304347825,\n", + " 'F1-4_vs_rest': 0.14193548387096774,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.680379746835443,\n", + " 'Recall-1.5': 0.9555555555555556,\n", + " 'Precision-1.5': 0.5282555282555282,\n", + " 'F1-2.5': 0.5529715762273901,\n", + " 'Recall-2.5': 0.8991596638655462,\n", + " 'Precision-2.5': 0.39925373134328357,\n", + " 'F1-3.5': 0.16560509554140126,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.09154929577464789,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.902583633391591},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 76, '2': 74, '3': 19, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 39, '3': 34, '4': 18, '5': 0},\n", @@ -5435,7 +9245,54 @@ " '3': {'-1': 0, '0': 0, '1': 1, '2': 11, '3': 29, '4': 63, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 11, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'pl': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06613538655122309,\n", + " 'pl': {'phi-4': {'metrics': {'Fleiss': 0.20557117590481178,\n", + " 'Cohen': 0.21682025414686212,\n", + " 'Spearman': 0.6459685747609837,\n", + " 'Kendall': 0.5375851907089526,\n", + " 'Krippendorff': 0.5524020541565153,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7221135029354208,\n", + " 'TA-4.0': 0.8806262230919765,\n", + " 'Acc': 0.3816046966731898,\n", + " 'MAE': 0.8998695368558385,\n", + " 'MSE': 1.6394324853228965,\n", + " 'CA-0': 0.478494623655914,\n", + " 'CA-1': 0.18,\n", + " 'CA-2': 0.29245283018867924,\n", + " 'CA-3': 0.49038461538461536,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2775383222771797,\n", + " 'Micro-F1': 0.3816046966731898,\n", + " 'F1-0_vs_rest': 0.6180555555555556,\n", + " 'F1-1_vs_rest': 0.19148936170212766,\n", + " 'F1-2_vs_rest': 0.2938388625592417,\n", + " 'F1-3_vs_rest': 0.408,\n", + " 'F1-4_vs_rest': 0.15384615384615385,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8501362397820164,\n", + " 'Recall-0.5': 0.96,\n", + " 'Precision-0.5': 0.7628361858190709,\n", + " 'F1-1.5': 0.7655677655677655,\n", + " 'Recall-1.5': 0.9288888888888889,\n", + " 'Precision-1.5': 0.6510903426791277,\n", + " 'F1-2.5': 0.5611940298507463,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.4351851851851852,\n", + " 'F1-3.5': 0.18823529411764706,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.11428571428571428,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8809883287880375},\n", + " 'CM': {'0': {'-1': 0, '0': 89, '1': 56, '2': 21, '3': 15, '4': 4, '5': 1},\n", + " '1': {'-1': 0, '0': 11, '1': 18, '2': 33, '3': 28, '4': 9, '5': 1},\n", + " '2': {'-1': 0, '0': 2, '1': 9, '2': 31, '3': 47, '4': 15, '5': 2},\n", + " '3': {'-1': 0, '0': 0, '1': 5, '2': 18, '3': 51, '4': 29, '5': 1},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 2, '3': 5, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06613538655122309,\n", " 'Cohen': 0.1013593054040679,\n", " 'Spearman': 0.5815503177914422,\n", " 'Kendall': 0.48956607654426004,\n", @@ -5454,12 +9311,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2204371301512267,\n", " 'Micro-F1': 0.2837573385518591,\n", - " 'F1-0': 0.28699551569506726,\n", - " 'F1-1': 0.22456140350877193,\n", - " 'F1-2': 0.29365079365079366,\n", - " 'F1-3': 0.3778801843317972,\n", - " 'F1-4': 0.13953488372093023,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.28699551569506726,\n", + " 'F1-1_vs_rest': 0.22456140350877193,\n", + " 'F1-2_vs_rest': 0.29365079365079366,\n", + " 'F1-3_vs_rest': 0.3778801843317972,\n", + " 'F1-4_vs_rest': 0.13953488372093023,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8010012515644556,\n", + " 'Recall-0.5': 0.9846153846153847,\n", + " 'Precision-0.5': 0.6751054852320675,\n", + " 'F1-1.5': 0.7276264591439688,\n", + " 'Recall-1.5': 0.8311111111111111,\n", + " 'Precision-1.5': 0.6470588235294118,\n", + " 'F1-2.5': 0.5038167938931297,\n", + " 'Recall-2.5': 0.5546218487394958,\n", + " 'Precision-2.5': 0.46153846153846156,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.16666666666666666,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8915379457181469},\n", " 'CM': {'0': {'-1': 0, '0': 32, '1': 115, '2': 28, '3': 7, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 32, '2': 40, '3': 17, '4': 6, '5': 0},\n", @@ -5486,12 +9358,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.30676653904880774,\n", " 'Micro-F1': 0.3796477495107632,\n", - " 'F1-0': 0.625,\n", - " 'F1-1': 0.3277310924369748,\n", - " 'F1-2': 0.3487179487179487,\n", - " 'F1-3': 0.25766871165644173,\n", - " 'F1-4': 0.14814814814814814,\n", - " 'F1-5': 0.13333333333333333,\n", + " 'F1-0_vs_rest': 0.625,\n", + " 'F1-1_vs_rest': 0.3277310924369748,\n", + " 'F1-2_vs_rest': 0.3487179487179487,\n", + " 'F1-3_vs_rest': 0.25766871165644173,\n", + " 'F1-4_vs_rest': 0.14814814814814814,\n", + " 'F1-5_vs_rest': 0.13333333333333333,\n", + " 'F1-0.5': 0.8528610354223434,\n", + " 'Recall-0.5': 0.963076923076923,\n", + " 'Precision-0.5': 0.7652811735941321,\n", + " 'F1-1.5': 0.7943548387096774,\n", + " 'Recall-1.5': 0.8755555555555555,\n", + " 'Precision-1.5': 0.7269372693726938,\n", + " 'F1-2.5': 0.6112956810631229,\n", + " 'Recall-2.5': 0.773109243697479,\n", + " 'Precision-2.5': 0.5054945054945055,\n", + " 'F1-3.5': 0.15942028985507245,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08943089430894309,\n", + " 'F1-4.5': 0.13333333333333333,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.07142857142857142,\n", " 'NDCG@all': 0.893028125368284},\n", " 'CM': {'0': {'-1': 0, '0': 90, '1': 72, '2': 12, '3': 4, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 11, '1': 39, '2': 21, '3': 10, '4': 13, '5': 6},\n", @@ -5518,12 +9405,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1964753380490095,\n", " 'Micro-F1': 0.2759295499021526,\n", - " 'F1-0': 0.042105263157894736,\n", - " 'F1-1': 0.2647887323943662,\n", - " 'F1-2': 0.351931330472103,\n", - " 'F1-3': 0.4485981308411215,\n", - " 'F1-4': 0.07142857142857142,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.042105263157894736,\n", + " 'F1-1_vs_rest': 0.2647887323943662,\n", + " 'F1-2_vs_rest': 0.351931330472103,\n", + " 'F1-3_vs_rest': 0.4485981308411215,\n", + " 'F1-4_vs_rest': 0.07142857142857142,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78125,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6410256410256411,\n", + " 'F1-1.5': 0.7463312368972747,\n", + " 'Recall-1.5': 0.7911111111111111,\n", + " 'Precision-1.5': 0.7063492063492064,\n", + " 'F1-2.5': 0.5573770491803278,\n", + " 'Recall-2.5': 0.5714285714285714,\n", + " 'Precision-2.5': 0.544,\n", + " 'F1-3.5': 0.13333333333333333,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.13333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9062881539149782},\n", " 'CM': {'0': {'-1': 0, '0': 4, '1': 161, '2': 16, '3': 4, '4': 1, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 47, '2': 35, '3': 16, '4': 2, '5': 0},\n", @@ -5550,12 +9452,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.26534343539060523,\n", " 'Micro-F1': 0.34833659491193736,\n", - " 'F1-0': 0.5494505494505495,\n", - " 'F1-1': 0.2916666666666667,\n", - " 'F1-2': 0.26,\n", - " 'F1-3': 0.34,\n", - " 'F1-4': 0.1509433962264151,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5494505494505495,\n", + " 'F1-1_vs_rest': 0.2916666666666667,\n", + " 'F1-2_vs_rest': 0.26,\n", + " 'F1-3_vs_rest': 0.34,\n", + " 'F1-4_vs_rest': 0.1509433962264151,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.835781041388518,\n", + " 'Recall-0.5': 0.963076923076923,\n", + " 'Precision-0.5': 0.7382075471698113,\n", + " 'F1-1.5': 0.7426326129666012,\n", + " 'Recall-1.5': 0.84,\n", + " 'Precision-1.5': 0.6654929577464789,\n", + " 'F1-2.5': 0.5954692556634305,\n", + " 'Recall-2.5': 0.773109243697479,\n", + " 'Precision-2.5': 0.4842105263157895,\n", + " 'F1-3.5': 0.1834862385321101,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.10638297872340426,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8845149553825653},\n", " 'CM': {'0': {'-1': 0, '0': 75, '1': 75, '2': 22, '3': 7, '4': 6, '5': 1},\n", " '1': {'-1': 0, '0': 6, '1': 35, '2': 30, '3': 15, '4': 14, '5': 0},\n", @@ -5582,12 +9499,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07762555496973654,\n", " 'Micro-F1': 0.0958904109589041,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.08376963350785341,\n", - " 'F1-2': 0.1630901287553648,\n", - " 'F1-3': 0.10752688172043011,\n", - " 'F1-4': 0.09009009009009009,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.08376963350785341,\n", + " 'F1-2_vs_rest': 0.1630901287553648,\n", + " 'F1-3_vs_rest': 0.10752688172043011,\n", + " 'F1-4_vs_rest': 0.09009009009009009,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6687402799377916,\n", + " 'Recall-1.5': 0.9555555555555556,\n", + " 'Precision-1.5': 0.5143540669856459,\n", + " 'F1-2.5': 0.5170731707317073,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.3642611683848797,\n", + " 'F1-3.5': 0.10714285714285714,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.05741626794258373,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.885901770953761},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 73, '2': 70, '3': 24, '4': 17, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 30, '3': 23, '4': 39, '5': 0},\n", @@ -5614,12 +9546,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08380752103405281,\n", " 'Micro-F1': 0.10980392156862745,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.04807692307692308,\n", - " 'F1-2': 0.07106598984771574,\n", - " 'F1-3': 0.24285714285714285,\n", - " 'F1-4': 0.14084507042253522,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.04807692307692308,\n", + " 'F1-2_vs_rest': 0.07106598984771574,\n", + " 'F1-3_vs_rest': 0.24285714285714285,\n", + " 'F1-4_vs_rest': 0.14084507042253522,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.7028753993610224,\n", + " 'Recall-1.5': 0.9821428571428571,\n", + " 'Precision-1.5': 0.5472636815920398,\n", + " 'F1-2.5': 0.5407925407925408,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.3741935483870968,\n", + " 'F1-3.5': 0.1610738255033557,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08955223880597014,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9018338533995509},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 99, '2': 54, '3': 28, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 29, '3': 51, '4': 14, '5': 1},\n", @@ -5646,12 +9593,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.297054525135468,\n", " 'Micro-F1': 0.3776908023483366,\n", - " 'F1-0': 0.4085106382978723,\n", - " 'F1-1': 0.30656934306569344,\n", - " 'F1-2': 0.3925925925925926,\n", - " 'F1-3': 0.46632124352331605,\n", - " 'F1-4': 0.20833333333333334,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4085106382978723,\n", + " 'F1-1_vs_rest': 0.30656934306569344,\n", + " 'F1-2_vs_rest': 0.3925925925925926,\n", + " 'F1-3_vs_rest': 0.46632124352331605,\n", + " 'F1-4_vs_rest': 0.20833333333333334,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8233799237611181,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.7012987012987013,\n", + " 'F1-1.5': 0.7680311890838206,\n", + " 'Recall-1.5': 0.8755555555555555,\n", + " 'Precision-1.5': 0.6840277777777778,\n", + " 'F1-2.5': 0.5761316872427984,\n", + " 'Recall-2.5': 0.5882352941176471,\n", + " 'Precision-2.5': 0.5645161290322581,\n", + " 'F1-3.5': 0.24,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.17142857142857143,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9026522574185668},\n", " 'CM': {'0': {'-1': 0, '0': 48, '1': 104, '2': 27, '3': 3, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 1, '1': 42, '2': 39, '3': 13, '4': 5, '5': 0},\n", @@ -5678,12 +9640,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12791244703009408,\n", " 'Micro-F1': 0.1527777777777778,\n", - " 'F1-0': 0.1282051282051282,\n", - " 'F1-1': 0.16666666666666666,\n", - " 'F1-2': 0.21153846153846154,\n", - " 'F1-3': 0.19047619047619047,\n", - " 'F1-4': 0.07058823529411765,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.1282051282051282,\n", + " 'F1-1_vs_rest': 0.16666666666666666,\n", + " 'F1-2_vs_rest': 0.21153846153846154,\n", + " 'F1-3_vs_rest': 0.19047619047619047,\n", + " 'F1-4_vs_rest': 0.07058823529411765,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.807909604519774,\n", + " 'Recall-0.5': 0.9862068965517241,\n", + " 'Precision-0.5': 0.6842105263157895,\n", + " 'F1-1.5': 0.6666666666666666,\n", + " 'Recall-1.5': 0.9591836734693877,\n", + " 'Precision-1.5': 0.5108695652173914,\n", + " 'F1-2.5': 0.4606741573033708,\n", + " 'Recall-2.5': 0.82,\n", + " 'Precision-2.5': 0.3203125,\n", + " 'F1-3.5': 0.0851063829787234,\n", + " 'Recall-3.5': 0.5,\n", + " 'Precision-3.5': 0.046511627906976744,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8339288289090923},\n", " 'CM': {'0': {'-1': 115, '0': 5, '1': 16, '2': 32, '3': 9, '4': 8, '5': 1},\n", " '1': {'-1': 53, '0': 1, '1': 6, '2': 6, '3': 12, '4': 20, '5': 2},\n", @@ -5691,6 +9668,53 @@ " '3': {'-1': 62, '0': 0, '1': 2, '2': 5, '3': 8, '4': 26, '5': 1},\n", " '4': {'-1': 6, '0': 0, '1': 0, '2': 2, '3': 2, '4': 3, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.15530440935918408,\n", + " 'Cohen': 0.19071083621142826,\n", + " 'Spearman': 0.6930929484312037,\n", + " 'Kendall': 0.5966648842718432,\n", + " 'Krippendorff': 0.6119524971832113,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7549019607843137,\n", + " 'TA-4.0': 0.9627450980392157,\n", + " 'Acc': 0.36666666666666664,\n", + " 'MAE': 0.7522875816993461,\n", + " 'MSE': 0.9766884531590411,\n", + " 'CA-0': 0.26881720430107525,\n", + " 'CA-1': 0.35,\n", + " 'CA-2': 0.6132075471698113,\n", + " 'CA-3': 0.34951456310679613,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.26689187319178337,\n", + " 'Micro-F1': 0.36666666666666664,\n", + " 'F1-0_vs_rest': 0.41841004184100417,\n", + " 'F1-1_vs_rest': 0.2681992337164751,\n", + " 'F1-2_vs_rest': 0.40498442367601245,\n", + " 'F1-3_vs_rest': 0.4044943820224719,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8220230473751601,\n", + " 'Recall-0.5': 0.9907407407407407,\n", + " 'Precision-0.5': 0.7024070021881839,\n", + " 'F1-1.5': 0.7846153846153846,\n", + " 'Recall-1.5': 0.9107142857142857,\n", + " 'Precision-1.5': 0.6891891891891891,\n", + " 'F1-2.5': 0.4723618090452261,\n", + " 'Recall-2.5': 0.3983050847457627,\n", + " 'Precision-2.5': 0.5802469135802469,\n", + " 'F1-3.5': 0.09523809523809523,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.16666666666666666,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8982051512922291},\n", + " 'CM': {'0': {'-1': 0, '0': 50, '1': 107, '2': 27, '3': 0, '4': 2, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 35, '2': 54, '3': 9, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 17, '2': 65, '3': 22, '4': 1, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 2, '2': 63, '3': 36, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 6, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.13846374079950372,\n", " 'Cohen': 0.15877018771003082,\n", " 'Spearman': 0.6524395016623825,\n", @@ -5710,12 +9734,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2685201789773479,\n", " 'Micro-F1': 0.3173913043478261,\n", - " 'F1-0': 0.5086206896551724,\n", - " 'F1-1': 0.19631901840490798,\n", - " 'F1-2': 0.3116883116883117,\n", - " 'F1-3': 0.30857142857142855,\n", - " 'F1-4': 0.1320754716981132,\n", - " 'F1-5': 0.15384615384615385,\n", + " 'F1-0_vs_rest': 0.5086206896551724,\n", + " 'F1-1_vs_rest': 0.19631901840490798,\n", + " 'F1-2_vs_rest': 0.3116883116883117,\n", + " 'F1-3_vs_rest': 0.30857142857142855,\n", + " 'F1-4_vs_rest': 0.1320754716981132,\n", + " 'F1-5_vs_rest': 0.15384615384615385,\n", + " 'F1-0.5': 0.8343023255813954,\n", + " 'Recall-0.5': 0.9503311258278145,\n", + " 'Precision-0.5': 0.7435233160621761,\n", + " 'F1-1.5': 0.7619047619047619,\n", + " 'Recall-1.5': 0.9345794392523364,\n", + " 'Precision-1.5': 0.6430868167202572,\n", + " 'F1-2.5': 0.6190476190476191,\n", + " 'Recall-2.5': 0.7711864406779662,\n", + " 'Precision-2.5': 0.5170454545454546,\n", + " 'F1-3.5': 0.16806722689075632,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.09615384615384616,\n", + " 'F1-4.5': 0.15384615384615385,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.09090909090909091,\n", " 'NDCG@all': 0.914083301360287},\n", " 'CM': {'0': {'-1': 28, '0': 59, '1': 50, '2': 36, '3': 8, '4': 4, '5': 1},\n", " '1': {'-1': 12, '0': 10, '1': 16, '2': 37, '3': 12, '4': 13, '5': 0},\n", @@ -5742,12 +9781,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1198336741205766,\n", " 'Micro-F1': 0.1487279843444227,\n", - " 'F1-0': 0.08247422680412371,\n", - " 'F1-1': 0.10526315789473684,\n", - " 'F1-2': 0.14007782101167315,\n", - " 'F1-3': 0.26956521739130435,\n", - " 'F1-4': 0.12162162162162163,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.08247422680412371,\n", + " 'F1-1_vs_rest': 0.10526315789473684,\n", + " 'F1-2_vs_rest': 0.14007782101167315,\n", + " 'F1-3_vs_rest': 0.26956521739130435,\n", + " 'F1-4_vs_rest': 0.12162162162162163,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.785024154589372,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6461232604373758,\n", + " 'F1-1.5': 0.6739811912225705,\n", + " 'Recall-1.5': 0.9555555555555556,\n", + " 'Precision-1.5': 0.5205811138014528,\n", + " 'F1-2.5': 0.5511811023622047,\n", + " 'Recall-2.5': 0.8823529411764706,\n", + " 'Precision-2.5': 0.40076335877862596,\n", + " 'F1-3.5': 0.1456953642384106,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08088235294117647,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8816677522551835},\n", " 'CM': {'0': {'-1': 0, '0': 8, '1': 70, '2': 79, '3': 21, '4': 7, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 10, '2': 43, '3': 27, '4': 20, '5': 0},\n", @@ -5755,7 +9809,54 @@ " '3': {'-1': 0, '0': 0, '1': 3, '2': 11, '3': 31, '4': 59, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'cs': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10366826955604394,\n", + " 'cs': {'phi-4': {'metrics': {'Fleiss': 0.22243601700322982,\n", + " 'Cohen': 0.23355686513581264,\n", + " 'Spearman': 0.6363744178790373,\n", + " 'Kendall': 0.5280921365915271,\n", + " 'Krippendorff': 0.5496139767674719,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7045009784735812,\n", + " 'TA-4.0': 0.8708414872798435,\n", + " 'Acc': 0.3933463796477495,\n", + " 'MAE': 0.898238747553816,\n", + " 'MSE': 1.6133942161339425,\n", + " 'CA-0': 0.45698924731182794,\n", + " 'CA-1': 0.28,\n", + " 'CA-2': 0.27358490566037735,\n", + " 'CA-3': 0.5,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.33866695374356565,\n", + " 'Micro-F1': 0.3933463796477495,\n", + " 'F1-0_vs_rest': 0.6071428571428571,\n", + " 'F1-1_vs_rest': 0.27860696517412936,\n", + " 'F1-2_vs_rest': 0.2600896860986547,\n", + " 'F1-3_vs_rest': 0.4425531914893617,\n", + " 'F1-4_vs_rest': 0.15789473684210525,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.8517520215633423,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7577937649880095,\n", + " 'F1-1.5': 0.7356746765249538,\n", + " 'Recall-1.5': 0.8844444444444445,\n", + " 'Precision-1.5': 0.629746835443038,\n", + " 'F1-2.5': 0.5849056603773585,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.46733668341708545,\n", + " 'F1-3.5': 0.1927710843373494,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.11764705882352941,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", + " 'NDCG@all': 0.8916828049194883},\n", + " 'CM': {'0': {'-1': 0, '0': 85, '1': 49, '2': 37, '3': 11, '4': 4, '5': 0},\n", + " '1': {'-1': 0, '0': 7, '1': 28, '2': 33, '3': 19, '4': 11, '5': 2},\n", + " '2': {'-1': 0, '0': 2, '1': 16, '2': 29, '3': 45, '4': 13, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 8, '2': 15, '3': 52, '4': 28, '5': 1},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 3, '3': 4, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10366826955604394,\n", " 'Cohen': 0.13900175232520073,\n", " 'Spearman': 0.593417788553288,\n", " 'Kendall': 0.5012203022231464,\n", @@ -5774,12 +9875,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23650831477923276,\n", " 'Micro-F1': 0.3150684931506849,\n", - " 'F1-0': 0.30493273542600896,\n", - " 'F1-1': 0.28378378378378377,\n", - " 'F1-2': 0.2938775510204082,\n", - " 'F1-3': 0.43119266055045874,\n", - " 'F1-4': 0.10526315789473684,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.30493273542600896,\n", + " 'F1-1_vs_rest': 0.28378378378378377,\n", + " 'F1-2_vs_rest': 0.2938775510204082,\n", + " 'F1-3_vs_rest': 0.43119266055045874,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8060075093867334,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.679324894514768,\n", + " 'F1-1.5': 0.7395626242544732,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6690647482014388,\n", + " 'F1-2.5': 0.5116279069767442,\n", + " 'Recall-2.5': 0.5546218487394958,\n", + " 'Precision-2.5': 0.4748201438848921,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.16,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8875229010354008},\n", " 'CM': {'0': {'-1': 0, '0': 34, '1': 116, '2': 27, '3': 5, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 42, '2': 35, '3': 16, '4': 5, '5': 0},\n", @@ -5806,12 +9922,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2992686601398587,\n", " 'Micro-F1': 0.38551859099804303,\n", - " 'F1-0': 0.6551724137931034,\n", - " 'F1-1': 0.3739130434782609,\n", - " 'F1-2': 0.3125,\n", - " 'F1-3': 0.2222222222222222,\n", - " 'F1-4': 0.1651376146788991,\n", - " 'F1-5': 0.06666666666666667,\n", + " 'F1-0_vs_rest': 0.6551724137931034,\n", + " 'F1-1_vs_rest': 0.3739130434782609,\n", + " 'F1-2_vs_rest': 0.3125,\n", + " 'F1-3_vs_rest': 0.2222222222222222,\n", + " 'F1-4_vs_rest': 0.1651376146788991,\n", + " 'F1-5_vs_rest': 0.06666666666666667,\n", + " 'F1-0.5': 0.8633879781420765,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7764127764127764,\n", + " 'F1-1.5': 0.7888446215139442,\n", + " 'Recall-1.5': 0.88,\n", + " 'Precision-1.5': 0.7148014440433214,\n", + " 'F1-2.5': 0.6129032258064516,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.4973821989528796,\n", + " 'F1-3.5': 0.15827338129496402,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08870967741935484,\n", + " 'F1-4.5': 0.06666666666666667,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.03571428571428571,\n", " 'NDCG@all': 0.8874012015264107},\n", " 'CM': {'0': {'-1': 0, '0': 95, '1': 61, '2': 15, '3': 7, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 8, '1': 43, '2': 21, '3': 11, '4': 10, '5': 7},\n", @@ -5838,12 +9969,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.20393159458601184,\n", " 'Micro-F1': 0.2876712328767123,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.27380952380952384,\n", - " 'F1-2': 0.3559322033898305,\n", - " 'F1-3': 0.4657534246575342,\n", - " 'F1-4': 0.05555555555555555,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.27380952380952384,\n", + " 'F1-2_vs_rest': 0.3559322033898305,\n", + " 'F1-3_vs_rest': 0.4657534246575342,\n", + " 'F1-4_vs_rest': 0.05555555555555555,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7789046653144016,\n", + " 'Recall-1.5': 0.8533333333333334,\n", + " 'Precision-1.5': 0.7164179104477612,\n", + " 'F1-2.5': 0.5758754863813229,\n", + " 'Recall-2.5': 0.6218487394957983,\n", + " 'Precision-2.5': 0.5362318840579711,\n", + " 'F1-3.5': 0.10526315789473684,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.08695652173913043,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8995980042802314},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 157, '2': 18, '3': 2, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 46, '2': 34, '3': 15, '4': 5, '5': 0},\n", @@ -5870,12 +10016,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.27707072423221535,\n", " 'Micro-F1': 0.36007827788649704,\n", - " 'F1-0': 0.5303030303030303,\n", - " 'F1-1': 0.2948207171314741,\n", - " 'F1-2': 0.3036649214659686,\n", - " 'F1-3': 0.37037037037037035,\n", - " 'F1-4': 0.16326530612244897,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5303030303030303,\n", + " 'F1-1_vs_rest': 0.2948207171314741,\n", + " 'F1-2_vs_rest': 0.3036649214659686,\n", + " 'F1-3_vs_rest': 0.37037037037037035,\n", + " 'F1-4_vs_rest': 0.16326530612244897,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8364116094986808,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7321016166281755,\n", + " 'F1-1.5': 0.7534516765285996,\n", + " 'Recall-1.5': 0.8488888888888889,\n", + " 'Precision-1.5': 0.6773049645390071,\n", + " 'F1-2.5': 0.6012658227848101,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.48223350253807107,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.11764705882352941,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9042666072410066},\n", " 'CM': {'0': {'-1': 0, '0': 70, '1': 84, '2': 17, '3': 10, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 37, '2': 25, '3': 20, '4': 14, '5': 0},\n", @@ -5902,12 +10063,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08720545976316496,\n", " 'Micro-F1': 0.10567514677103718,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.08121827411167512,\n", - " 'F1-2': 0.14150943396226415,\n", - " 'F1-3': 0.16161616161616163,\n", - " 'F1-4': 0.10714285714285714,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.08121827411167512,\n", + " 'F1-2_vs_rest': 0.14150943396226415,\n", + " 'F1-3_vs_rest': 0.16161616161616163,\n", + " 'F1-4_vs_rest': 0.10714285714285714,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78031212484994,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.639763779527559,\n", + " 'F1-1.5': 0.6855345911949685,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5304136253041363,\n", + " 'F1-2.5': 0.5283018867924528,\n", + " 'Recall-2.5': 0.9411764705882353,\n", + " 'Precision-2.5': 0.36721311475409835,\n", + " 'F1-3.5': 0.12389380530973451,\n", + " 'Recall-3.5': 0.9333333333333333,\n", + " 'Precision-3.5': 0.06635071090047394,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8896682527530413},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 82, '2': 60, '3': 26, '4': 15, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 27, '3': 25, '4': 40, '5': 0},\n", @@ -5934,12 +10110,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09631717759667496,\n", " 'Micro-F1': 0.1232876712328767,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.06930693069306931,\n", - " 'F1-2': 0.14218009478672985,\n", - " 'F1-3': 0.23308270676691728,\n", - " 'F1-4': 0.13333333333333333,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.06930693069306931,\n", + " 'F1-2_vs_rest': 0.14218009478672985,\n", + " 'F1-3_vs_rest': 0.23308270676691728,\n", + " 'F1-4_vs_rest': 0.13333333333333333,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7097791798107256,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.5501222493887531,\n", + " 'F1-2.5': 0.5484633569739953,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.3815789473684211,\n", + " 'F1-3.5': 0.15286624203821655,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08450704225352113,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9061480943591828},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 95, '2': 58, '3': 28, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 29, '3': 47, '4': 17, '5': 0},\n", @@ -5966,12 +10157,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.31540959577191463,\n", " 'Micro-F1': 0.4050880626223092,\n", - " 'F1-0': 0.38461538461538464,\n", - " 'F1-1': 0.2740740740740741,\n", - " 'F1-2': 0.463768115942029,\n", - " 'F1-3': 0.57,\n", - " 'F1-4': 0.2,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.38461538461538464,\n", + " 'F1-1_vs_rest': 0.2740740740740741,\n", + " 'F1-2_vs_rest': 0.463768115942029,\n", + " 'F1-3_vs_rest': 0.57,\n", + " 'F1-4_vs_rest': 0.2,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.817258883248731,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.6954643628509719,\n", + " 'F1-1.5': 0.7915057915057915,\n", + " 'Recall-1.5': 0.9111111111111111,\n", + " 'Precision-1.5': 0.6996587030716723,\n", + " 'F1-2.5': 0.628099173553719,\n", + " 'Recall-2.5': 0.6386554621848739,\n", + " 'Precision-2.5': 0.6178861788617886,\n", + " 'F1-3.5': 0.23809523809523808,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.18518518518518517,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8987066064699049},\n", " 'CM': {'0': {'-1': 0, '0': 45, '1': 113, '2': 21, '3': 2, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 37, '2': 44, '3': 11, '4': 5, '5': 0},\n", @@ -5998,12 +10204,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.12377601238123707,\n", " 'Micro-F1': 0.13043478260869565,\n", - " 'F1-0': 0.125,\n", - " 'F1-1': 0.08695652173913043,\n", - " 'F1-2': 0.12244897959183673,\n", - " 'F1-3': 0.24675324675324675,\n", - " 'F1-4': 0.07058823529411765,\n", - " 'F1-5': 0.09090909090909091,\n", + " 'F1-0_vs_rest': 0.125,\n", + " 'F1-1_vs_rest': 0.08695652173913043,\n", + " 'F1-2_vs_rest': 0.12244897959183673,\n", + " 'F1-3_vs_rest': 0.24675324675324675,\n", + " 'F1-4_vs_rest': 0.07058823529411765,\n", + " 'F1-5_vs_rest': 0.09090909090909091,\n", + " 'F1-0.5': 0.8157894736842105,\n", + " 'Recall-0.5': 0.9841269841269841,\n", + " 'Precision-0.5': 0.6966292134831461,\n", + " 'F1-1.5': 0.6815415821501014,\n", + " 'Recall-1.5': 0.9824561403508771,\n", + " 'Precision-1.5': 0.5217391304347826,\n", + " 'F1-2.5': 0.47398843930635837,\n", + " 'Recall-2.5': 0.9213483146067416,\n", + " 'Precision-2.5': 0.31906614785992216,\n", + " 'F1-3.5': 0.08333333333333333,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.044444444444444446,\n", + " 'F1-4.5': 0.09090909090909091,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.047619047619047616,\n", " 'NDCG@all': 0.8802281301427953},\n", " 'CM': {'0': {'-1': 70, '0': 8, '1': 27, '2': 38, '3': 19, '4': 22, '5': 2},\n", " '1': {'-1': 19, '0': 3, '1': 5, '2': 11, '3': 22, '4': 38, '5': 2},\n", @@ -6011,6 +10232,53 @@ " '3': {'-1': 27, '0': 0, '1': 0, '2': 6, '3': 19, '4': 42, '5': 10},\n", " '4': {'-1': 2, '0': 0, '1': 0, '2': 1, '3': 3, '4': 6, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10993622236195418,\n", + " 'Cohen': 0.14939123097903406,\n", + " 'Spearman': 0.6876006389085294,\n", + " 'Kendall': 0.5914530906678815,\n", + " 'Krippendorff': 0.5969666383991323,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7470588235294118,\n", + " 'TA-4.0': 0.9686274509803922,\n", + " 'Acc': 0.3333333333333333,\n", + " 'MAE': 0.7787581699346403,\n", + " 'MSE': 0.9830610021786489,\n", + " 'CA-0': 0.23118279569892472,\n", + " 'CA-1': 0.28,\n", + " 'CA-2': 0.5943396226415094,\n", + " 'CA-3': 0.34951456310679613,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.22707311593268473,\n", + " 'Micro-F1': 0.3333333333333333,\n", + " 'F1-0_vs_rest': 0.3706896551724138,\n", + " 'F1-1_vs_rest': 0.21455938697318008,\n", + " 'F1-2_vs_rest': 0.39009287925696595,\n", + " 'F1-3_vs_rest': 0.3870967741935484,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8147208121827412,\n", + " 'Recall-0.5': 0.9907407407407407,\n", + " 'Precision-0.5': 0.6918103448275862,\n", + " 'F1-1.5': 0.7741935483870968,\n", + " 'Recall-1.5': 0.9107142857142857,\n", + " 'Precision-1.5': 0.6732673267326733,\n", + " 'F1-2.5': 0.46078431372549017,\n", + " 'Recall-2.5': 0.3983050847457627,\n", + " 'Precision-2.5': 0.5465116279069767,\n", + " 'F1-3.5': 0.1111111111111111,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.3333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9180803947747568},\n", + " 'CM': {'0': {'-1': 0, '0': 43, '1': 113, '2': 27, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 3, '1': 28, '2': 59, '3': 10, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 17, '2': 63, '3': 25, '4': 1, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 3, '2': 63, '3': 36, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.14277890619122852,\n", " 'Cohen': 0.16148819685641957,\n", " 'Spearman': 0.663418006202801,\n", @@ -6030,12 +10298,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2668091376574577,\n", " 'Micro-F1': 0.32096069868995636,\n", - " 'F1-0': 0.5414847161572053,\n", - " 'F1-1': 0.12738853503184713,\n", - " 'F1-2': 0.3620689655172414,\n", - " 'F1-3': 0.29213483146067415,\n", - " 'F1-4': 0.1111111111111111,\n", - " 'F1-5': 0.16666666666666666,\n", + " 'F1-0_vs_rest': 0.5414847161572053,\n", + " 'F1-1_vs_rest': 0.12738853503184713,\n", + " 'F1-2_vs_rest': 0.3620689655172414,\n", + " 'F1-3_vs_rest': 0.29213483146067415,\n", + " 'F1-4_vs_rest': 0.1111111111111111,\n", + " 'F1-5_vs_rest': 0.16666666666666666,\n", + " 'F1-0.5': 0.8471615720524017,\n", + " 'Recall-0.5': 0.9572368421052632,\n", + " 'Precision-0.5': 0.7597911227154047,\n", + " 'F1-1.5': 0.7735849056603774,\n", + " 'Recall-1.5': 0.9403669724770642,\n", + " 'Precision-1.5': 0.657051282051282,\n", + " 'F1-2.5': 0.6308724832214765,\n", + " 'Recall-2.5': 0.8034188034188035,\n", + " 'Precision-2.5': 0.5193370165745856,\n", + " 'F1-3.5': 0.15,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.08571428571428572,\n", + " 'F1-4.5': 0.16666666666666666,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.1,\n", " 'NDCG@all': 0.9097481095507928},\n", " 'CM': {'0': {'-1': 32, '0': 62, '1': 50, '2': 28, '3': 6, '4': 7, '5': 1},\n", " '1': {'-1': 14, '0': 11, '1': 10, '2': 38, '3': 15, '4': 11, '5': 1},\n", @@ -6062,12 +10345,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.13569619693456028,\n", " 'Micro-F1': 0.17025440313111545,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.09944751381215469,\n", - " 'F1-2': 0.16279069767441862,\n", - " 'F1-3': 0.30578512396694213,\n", - " 'F1-4': 0.15384615384615385,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.09944751381215469,\n", + " 'F1-2_vs_rest': 0.16279069767441862,\n", + " 'F1-3_vs_rest': 0.30578512396694213,\n", + " 'F1-4_vs_rest': 0.15384615384615385,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6749226006191951,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.517814726840855,\n", + " 'F1-2.5': 0.5567010309278351,\n", + " 'Recall-2.5': 0.907563025210084,\n", + " 'Precision-2.5': 0.40148698884758366,\n", + " 'F1-3.5': 0.1780821917808219,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.09923664122137404,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8923032732644883},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 65, '2': 81, '3': 24, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 41, '3': 33, '4': 16, '5': 1},\n", @@ -6075,7 +10373,54 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 9, '3': 37, '4': 56, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 11, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'es': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06451348837209307,\n", + " 'es': {'phi-4': {'metrics': {'Fleiss': 0.22566967921538816,\n", + " 'Cohen': 0.2365711226823689,\n", + " 'Spearman': 0.6368830818583854,\n", + " 'Kendall': 0.5339696804020988,\n", + " 'Krippendorff': 0.547890180694453,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.6888454011741683,\n", + " 'TA-4.0': 0.8923679060665362,\n", + " 'Acc': 0.39921722113502933,\n", + " 'MAE': 0.8871493803000652,\n", + " 'MSE': 1.5936073059360727,\n", + " 'CA-0': 0.4731182795698925,\n", + " 'CA-1': 0.24,\n", + " 'CA-2': 0.27358490566037735,\n", + " 'CA-3': 0.5576923076923077,\n", + " 'CA-4': 0.38461538461538464,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2894779243326146,\n", + " 'Micro-F1': 0.39921722113502933,\n", + " 'F1-0_vs_rest': 0.6175438596491228,\n", + " 'F1-1_vs_rest': 0.2513089005235602,\n", + " 'F1-2_vs_rest': 0.2648401826484018,\n", + " 'F1-3_vs_rest': 0.4603174603174603,\n", + " 'F1-4_vs_rest': 0.14285714285714285,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8521031207598372,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7621359223300971,\n", + " 'F1-1.5': 0.7326007326007326,\n", + " 'Recall-1.5': 0.8888888888888888,\n", + " 'Precision-1.5': 0.6230529595015576,\n", + " 'F1-2.5': 0.599388379204893,\n", + " 'Recall-2.5': 0.8235294117647058,\n", + " 'Precision-2.5': 0.47115384615384615,\n", + " 'F1-3.5': 0.18666666666666668,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.11666666666666667,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.88559946123781},\n", + " 'CM': {'0': {'-1': 0, '0': 88, '1': 45, '2': 34, '3': 14, '4': 5, '5': 0},\n", + " '1': {'-1': 0, '0': 8, '1': 24, '2': 34, '3': 26, '4': 6, '5': 2},\n", + " '2': {'-1': 0, '0': 3, '1': 17, '2': 29, '3': 43, '4': 13, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 5, '2': 15, '3': 58, '4': 26, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 7, '4': 5, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06451348837209307,\n", " 'Cohen': 0.10390924989544925,\n", " 'Spearman': 0.6051553774551707,\n", " 'Kendall': 0.5135226552908125,\n", @@ -6094,12 +10439,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.21688934384504244,\n", " 'Micro-F1': 0.27788649706457924,\n", - " 'F1-0': 0.20095693779904306,\n", - " 'F1-1': 0.20863309352517986,\n", - " 'F1-2': 0.2777777777777778,\n", - " 'F1-3': 0.4711111111111111,\n", - " 'F1-4': 0.14285714285714285,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.20095693779904306,\n", + " 'F1-1_vs_rest': 0.20863309352517986,\n", + " 'F1-2_vs_rest': 0.2777777777777778,\n", + " 'F1-3_vs_rest': 0.4711111111111111,\n", + " 'F1-4_vs_rest': 0.14285714285714285,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7945879458794588,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6618852459016393,\n", + " 'F1-1.5': 0.7252336448598131,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6258064516129033,\n", + " 'F1-2.5': 0.5724381625441696,\n", + " 'Recall-2.5': 0.680672268907563,\n", + " 'Precision-2.5': 0.49390243902439024,\n", + " 'F1-3.5': 0.20689655172413793,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.13953488372093023,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.890918266071231},\n", " 'CM': {'0': {'-1': 0, '0': 21, '1': 119, '2': 35, '3': 7, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 1, '1': 29, '2': 47, '3': 12, '4': 11, '5': 0},\n", @@ -6126,12 +10486,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.27918090363742537,\n", " 'Micro-F1': 0.3522504892367906,\n", - " 'F1-0': 0.6285714285714286,\n", - " 'F1-1': 0.32727272727272727,\n", - " 'F1-2': 0.33653846153846156,\n", - " 'F1-3': 0.16149068322981366,\n", - " 'F1-4': 0.1,\n", - " 'F1-5': 0.12121212121212122,\n", + " 'F1-0_vs_rest': 0.6285714285714286,\n", + " 'F1-1_vs_rest': 0.32727272727272727,\n", + " 'F1-2_vs_rest': 0.33653846153846156,\n", + " 'F1-3_vs_rest': 0.16149068322981366,\n", + " 'F1-4_vs_rest': 0.1,\n", + " 'F1-5_vs_rest': 0.12121212121212122,\n", + " 'F1-0.5': 0.8598382749326146,\n", + " 'Recall-0.5': 0.9815384615384616,\n", + " 'Precision-0.5': 0.7649880095923262,\n", + " 'F1-1.5': 0.7969348659003831,\n", + " 'Recall-1.5': 0.9244444444444444,\n", + " 'Precision-1.5': 0.7003367003367004,\n", + " 'F1-2.5': 0.6114649681528662,\n", + " 'Recall-2.5': 0.8067226890756303,\n", + " 'Precision-2.5': 0.49230769230769234,\n", + " 'F1-3.5': 0.13071895424836602,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07246376811594203,\n", + " 'F1-4.5': 0.12121212121212122,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.06451612903225806,\n", " 'NDCG@all': 0.892492436917667},\n", " 'CM': {'0': {'-1': 0, '0': 88, '1': 68, '2': 17, '3': 5, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 5, '1': 36, '2': 30, '3': 7, '4': 14, '5': 8},\n", @@ -6158,12 +10533,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23168196397228838,\n", " 'Micro-F1': 0.30332681017612523,\n", - " 'F1-0': 0.0625,\n", - " 'F1-1': 0.2634730538922156,\n", - " 'F1-2': 0.3881856540084388,\n", - " 'F1-3': 0.5045045045045045,\n", - " 'F1-4': 0.17142857142857143,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0625,\n", + " 'F1-1_vs_rest': 0.2634730538922156,\n", + " 'F1-2_vs_rest': 0.3881856540084388,\n", + " 'F1-3_vs_rest': 0.5045045045045045,\n", + " 'F1-4_vs_rest': 0.17142857142857143,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7831325301204819,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6435643564356436,\n", + " 'F1-1.5': 0.7701612903225806,\n", + " 'Recall-1.5': 0.8488888888888889,\n", + " 'Precision-1.5': 0.7047970479704797,\n", + " 'F1-2.5': 0.5945945945945946,\n", + " 'Recall-2.5': 0.6470588235294118,\n", + " 'Precision-2.5': 0.55,\n", + " 'F1-3.5': 0.21621621621621623,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.18181818181818182,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9034092500125896},\n", " 'CM': {'0': {'-1': 0, '0': 6, '1': 156, '2': 16, '3': 5, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 44, '2': 37, '3': 17, '4': 2, '5': 0},\n", @@ -6190,12 +10580,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.24714590069977482,\n", " 'Micro-F1': 0.324853228962818,\n", - " 'F1-0': 0.5358490566037736,\n", - " 'F1-1': 0.304,\n", - " 'F1-2': 0.233502538071066,\n", - " 'F1-3': 0.26666666666666666,\n", - " 'F1-4': 0.14285714285714285,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5358490566037736,\n", + " 'F1-1_vs_rest': 0.304,\n", + " 'F1-2_vs_rest': 0.233502538071066,\n", + " 'F1-3_vs_rest': 0.26666666666666666,\n", + " 'F1-4_vs_rest': 0.14285714285714285,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8375165125495376,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7337962962962963,\n", + " 'F1-1.5': 0.7495069033530573,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.6737588652482269,\n", + " 'F1-2.5': 0.5806451612903226,\n", + " 'Recall-2.5': 0.7563025210084033,\n", + " 'Precision-2.5': 0.4712041884816754,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9027848177718728},\n", " 'CM': {'0': {'-1': 0, '0': 71, '1': 80, '2': 21, '3': 10, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 38, '2': 29, '3': 17, '4': 11, '5': 0},\n", @@ -6222,12 +10627,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09360751548069444,\n", " 'Micro-F1': 0.11741682974559686,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.0967741935483871,\n", - " 'F1-2': 0.18532818532818532,\n", - " 'F1-3': 0.15463917525773196,\n", - " 'F1-4': 0.10362694300518134,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.0967741935483871,\n", + " 'F1-2_vs_rest': 0.18532818532818532,\n", + " 'F1-3_vs_rest': 0.15463917525773196,\n", + " 'F1-4_vs_rest': 0.10362694300518134,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6790123456790124,\n", + " 'Recall-1.5': 0.9777777777777777,\n", + " 'Precision-1.5': 0.5200945626477541,\n", + " 'F1-2.5': 0.5295629820051414,\n", + " 'Recall-2.5': 0.865546218487395,\n", + " 'Precision-2.5': 0.3814814814814815,\n", + " 'F1-3.5': 0.12307692307692308,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.06666666666666667,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8902914405546271},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 72, '2': 82, '3': 17, '4': 13, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 33, '3': 24, '4': 34, '5': 0},\n", @@ -6254,12 +10674,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08591669186407967,\n", " 'Micro-F1': 0.11545988258317025,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.06796116504854369,\n", - " 'F1-2': 0.08737864077669903,\n", - " 'F1-3': 0.2608695652173913,\n", - " 'F1-4': 0.09929078014184398,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.06796116504854369,\n", + " 'F1-2_vs_rest': 0.08737864077669903,\n", + " 'F1-3_vs_rest': 0.2608695652173913,\n", + " 'F1-4_vs_rest': 0.09929078014184398,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7111111111111111,\n", + " 'Recall-1.5': 0.9955555555555555,\n", + " 'Precision-1.5': 0.5530864197530864,\n", + " 'F1-2.5': 0.5424528301886793,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.3770491803278688,\n", + " 'F1-3.5': 0.12162162162162163,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.06766917293233082,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8939431282681429},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 98, '2': 58, '3': 22, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 30, '3': 41, '4': 21, '5': 1},\n", @@ -6286,12 +10721,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.30017606824893345,\n", " 'Micro-F1': 0.38943248532289626,\n", - " 'F1-0': 0.36681222707423583,\n", - " 'F1-1': 0.2846715328467153,\n", - " 'F1-2': 0.4444444444444444,\n", - " 'F1-3': 0.5384615384615384,\n", - " 'F1-4': 0.16666666666666666,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.36681222707423583,\n", + " 'F1-1_vs_rest': 0.2846715328467153,\n", + " 'F1-2_vs_rest': 0.4444444444444444,\n", + " 'F1-3_vs_rest': 0.5384615384615384,\n", + " 'F1-4_vs_rest': 0.16666666666666666,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8171500630517023,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6923076923076923,\n", + " 'F1-1.5': 0.7784200385356455,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.6870748299319728,\n", + " 'F1-2.5': 0.627906976744186,\n", + " 'Recall-2.5': 0.680672268907563,\n", + " 'Precision-2.5': 0.5827338129496403,\n", + " 'F1-3.5': 0.24,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.17142857142857143,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8998704265053911},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 112, '2': 26, '3': 1, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 1, '1': 39, '2': 39, '3': 15, '4': 6, '5': 0},\n", @@ -6318,12 +10768,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11056661516961867,\n", " 'Micro-F1': 0.13945578231292516,\n", - " 'F1-0': 0.0970873786407767,\n", - " 'F1-1': 0.07142857142857142,\n", - " 'F1-2': 0.15492957746478872,\n", - " 'F1-3': 0.2727272727272727,\n", - " 'F1-4': 0.06722689075630252,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0970873786407767,\n", + " 'F1-1_vs_rest': 0.07142857142857142,\n", + " 'F1-2_vs_rest': 0.15492957746478872,\n", + " 'F1-3_vs_rest': 0.2727272727272727,\n", + " 'F1-4_vs_rest': 0.06722689075630252,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8082474226804124,\n", + " 'Recall-0.5': 0.9949238578680203,\n", + " 'Precision-0.5': 0.6805555555555556,\n", + " 'F1-1.5': 0.6733167082294265,\n", + " 'Recall-1.5': 0.9926470588235294,\n", + " 'Precision-1.5': 0.5094339622641509,\n", + " 'F1-2.5': 0.5714285714285714,\n", + " 'Recall-2.5': 0.9487179487179487,\n", + " 'Precision-2.5': 0.4088397790055249,\n", + " 'F1-3.5': 0.07874015748031496,\n", + " 'Recall-3.5': 0.5555555555555556,\n", + " 'Precision-3.5': 0.0423728813559322,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8523634509050897},\n", " 'CM': {'0': {'-1': 89, '0': 5, '1': 19, '2': 51, '3': 10, '4': 11, '5': 1},\n", " '1': {'-1': 39, '0': 1, '1': 3, '2': 18, '3': 17, '4': 18, '5': 4},\n", @@ -6331,6 +10796,53 @@ " '3': {'-1': 35, '0': 0, '1': 0, '2': 3, '3': 18, '4': 47, '5': 1},\n", " '4': {'-1': 5, '0': 0, '1': 0, '2': 1, '3': 3, '4': 4, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.14288647938229013,\n", + " 'Cohen': 0.17726428251110027,\n", + " 'Spearman': 0.659290830507018,\n", + " 'Kendall': 0.5643714819828817,\n", + " 'Krippendorff': 0.5751105381373665,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.7465618860510805,\n", + " 'TA-4.0': 0.9705304518664047,\n", + " 'Acc': 0.3555992141453831,\n", + " 'MAE': 0.7858546168958739,\n", + " 'MSE': 1.0526086007421958,\n", + " 'CA-0': 0.23655913978494625,\n", + " 'CA-1': 0.36,\n", + " 'CA-2': 0.5660377358490566,\n", + " 'CA-3': 0.39215686274509803,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.26349368054630506,\n", + " 'Micro-F1': 0.3555992141453831,\n", + " 'F1-0_vs_rest': 0.3776824034334764,\n", + " 'F1-1_vs_rest': 0.27169811320754716,\n", + " 'F1-2_vs_rest': 0.39215686274509803,\n", + " 'F1-3_vs_rest': 0.40609137055837563,\n", + " 'F1-4_vs_rest': 0.13333333333333333,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8152866242038217,\n", + " 'Recall-0.5': 0.9907120743034056,\n", + " 'Precision-0.5': 0.6926406926406926,\n", + " 'F1-1.5': 0.7769230769230769,\n", + " 'Recall-1.5': 0.905829596412556,\n", + " 'Precision-1.5': 0.6801346801346801,\n", + " 'F1-2.5': 0.45794392523364486,\n", + " 'Recall-2.5': 0.4188034188034188,\n", + " 'Precision-2.5': 0.5051546391752577,\n", + " 'F1-3.5': 0.11764705882352941,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.5,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9099249074034136},\n", + " 'CM': {'0': {'-1': 0, '0': 44, '1': 110, '2': 27, '3': 5, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 36, '2': 50, '3': 13, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 2, '1': 14, '2': 60, '3': 30, '4': 0, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 5, '2': 56, '3': 40, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 5, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.18629669426711326,\n", " 'Cohen': 0.20134498824376057,\n", " 'Spearman': 0.6427462053819742,\n", @@ -6350,12 +10862,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.30303383195312056,\n", " 'Micro-F1': 0.35570469798657717,\n", - " 'F1-0': 0.5333333333333333,\n", - " 'F1-1': 0.18181818181818182,\n", - " 'F1-2': 0.3891402714932127,\n", - " 'F1-3': 0.37209302325581395,\n", - " 'F1-4': 0.16,\n", - " 'F1-5': 0.18181818181818182,\n", + " 'F1-0_vs_rest': 0.5333333333333333,\n", + " 'F1-1_vs_rest': 0.18181818181818182,\n", + " 'F1-2_vs_rest': 0.3891402714932127,\n", + " 'F1-3_vs_rest': 0.37209302325581395,\n", + " 'F1-4_vs_rest': 0.16,\n", + " 'F1-5_vs_rest': 0.18181818181818182,\n", + " 'F1-0.5': 0.8430493273542601,\n", + " 'Recall-0.5': 0.9368770764119602,\n", + " 'Precision-0.5': 0.7663043478260869,\n", + " 'F1-1.5': 0.7777777777777778,\n", + " 'Recall-1.5': 0.9245283018867925,\n", + " 'Precision-1.5': 0.6712328767123288,\n", + " 'F1-2.5': 0.6431095406360424,\n", + " 'Recall-2.5': 0.7844827586206896,\n", + " 'Precision-2.5': 0.5449101796407185,\n", + " 'F1-3.5': 0.18018018018018017,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.10416666666666667,\n", + " 'F1-4.5': 0.18181818181818182,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.1111111111111111,\n", " 'NDCG@all': 0.9074997802988962},\n", " 'CM': {'0': {'-1': 40, '0': 60, '1': 48, '2': 25, '3': 8, '4': 4, '5': 1},\n", " '1': {'-1': 11, '0': 16, '1': 15, '2': 35, '3': 10, '4': 12, '5': 1},\n", @@ -6382,12 +10909,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11173976835824016,\n", " 'Micro-F1': 0.13894324853228962,\n", - " 'F1-0': 0.10152284263959391,\n", - " 'F1-1': 0.06779661016949153,\n", - " 'F1-2': 0.09795918367346938,\n", - " 'F1-3': 0.2612244897959184,\n", - " 'F1-4': 0.14193548387096774,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.10152284263959391,\n", + " 'F1-1_vs_rest': 0.06779661016949153,\n", + " 'F1-2_vs_rest': 0.09795918367346938,\n", + " 'F1-3_vs_rest': 0.2612244897959184,\n", + " 'F1-4_vs_rest': 0.14193548387096774,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7854545454545454,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.648,\n", + " 'F1-1.5': 0.6666666666666666,\n", + " 'Recall-1.5': 0.96,\n", + " 'Precision-1.5': 0.5106382978723404,\n", + " 'F1-2.5': 0.5409429280397022,\n", + " 'Recall-2.5': 0.9159663865546218,\n", + " 'Precision-2.5': 0.38380281690140844,\n", + " 'F1-3.5': 0.16455696202531644,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.09090909090909091,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8957959135574456},\n", " 'CM': {'0': {'-1': 0, '0': 10, '1': 63, '2': 78, '3': 27, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 40, '3': 35, '4': 19, '5': 0},\n", @@ -6395,7 +10937,54 @@ " '3': {'-1': 0, '0': 0, '1': 1, '2': 9, '3': 32, '4': 62, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 11, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'tr': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.14126882113018063,\n", + " 'tr': {'phi-4': {'metrics': {'Fleiss': 0.24017114637544867,\n", + " 'Cohen': 0.25351301933430404,\n", + " 'Spearman': 0.6506139785053923,\n", + " 'Kendall': 0.5419714998542989,\n", + " 'Krippendorff': 0.5565940981983335,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.735812133072407,\n", + " 'TA-4.0': 0.8864970645792564,\n", + " 'Acc': 0.4090019569471624,\n", + " 'MAE': 0.8685583822570124,\n", + " 'MSE': 1.5681126331811268,\n", + " 'CA-0': 0.43548387096774194,\n", + " 'CA-1': 0.35,\n", + " 'CA-2': 0.24528301886792453,\n", + " 'CA-3': 0.5673076923076923,\n", + " 'CA-4': 0.5384615384615384,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3868890094470198,\n", + " 'Micro-F1': 0.4090019569471624,\n", + " 'F1-0_vs_rest': 0.5827338129496403,\n", + " 'F1-1_vs_rest': 0.33175355450236965,\n", + " 'F1-2_vs_rest': 0.2694300518134715,\n", + " 'F1-3_vs_rest': 0.4555984555984556,\n", + " 'F1-4_vs_rest': 0.18181818181818182,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8440860215053764,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7494033412887828,\n", + " 'F1-1.5': 0.7654784240150094,\n", + " 'Recall-1.5': 0.9066666666666666,\n", + " 'Precision-1.5': 0.6623376623376623,\n", + " 'F1-2.5': 0.5941176470588235,\n", + " 'Recall-2.5': 0.8487394957983193,\n", + " 'Precision-2.5': 0.45701357466063347,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.13636363636363635,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", + " 'NDCG@all': 0.908851982759894},\n", + " 'CM': {'0': {'-1': 0, '0': 81, '1': 59, '2': 27, '3': 15, '4': 4, '5': 0},\n", + " '1': {'-1': 0, '0': 7, '1': 35, '2': 19, '3': 27, '4': 12, '5': 0},\n", + " '2': {'-1': 0, '0': 4, '1': 14, '2': 26, '3': 49, '4': 12, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 3, '2': 14, '3': 59, '4': 28, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 5, '4': 7, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.14126882113018063,\n", " 'Cohen': 0.1782717940127786,\n", " 'Spearman': 0.6133730350071849,\n", " 'Kendall': 0.5214167879150541,\n", @@ -6414,12 +11003,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.252865770687466,\n", " 'Micro-F1': 0.3424657534246575,\n", - " 'F1-0': 0.2347417840375587,\n", - " 'F1-1': 0.30344827586206896,\n", - " 'F1-2': 0.4,\n", - " 'F1-3': 0.48598130841121495,\n", - " 'F1-4': 0.09302325581395349,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.2347417840375587,\n", + " 'F1-1_vs_rest': 0.30344827586206896,\n", + " 'F1-2_vs_rest': 0.4,\n", + " 'F1-3_vs_rest': 0.48598130841121495,\n", + " 'F1-4_vs_rest': 0.09302325581395349,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7985166872682324,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6673553719008265,\n", + " 'F1-1.5': 0.7591522157996147,\n", + " 'Recall-1.5': 0.8755555555555555,\n", + " 'Precision-1.5': 0.6700680272108843,\n", + " 'F1-2.5': 0.5714285714285714,\n", + " 'Recall-2.5': 0.6218487394957983,\n", + " 'Precision-2.5': 0.5285714285714286,\n", + " 'F1-3.5': 0.17777777777777778,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.13333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8905670879786425},\n", " 'CM': {'0': {'-1': 0, '0': 25, '1': 118, '2': 35, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 44, '2': 32, '3': 16, '4': 6, '5': 0},\n", @@ -6446,12 +11050,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.32479770872766955,\n", " 'Micro-F1': 0.4227005870841487,\n", - " 'F1-0': 0.6733333333333333,\n", - " 'F1-1': 0.379746835443038,\n", - " 'F1-2': 0.37894736842105264,\n", - " 'F1-3': 0.3312883435582822,\n", - " 'F1-4': 0.11650485436893204,\n", - " 'F1-5': 0.06896551724137931,\n", + " 'F1-0_vs_rest': 0.6733333333333333,\n", + " 'F1-1_vs_rest': 0.379746835443038,\n", + " 'F1-2_vs_rest': 0.37894736842105264,\n", + " 'F1-3_vs_rest': 0.3312883435582822,\n", + " 'F1-4_vs_rest': 0.11650485436893204,\n", + " 'F1-5_vs_rest': 0.06896551724137931,\n", + " 'F1-0.5': 0.8642659279778393,\n", + " 'Recall-0.5': 0.96,\n", + " 'Precision-0.5': 0.7858942065491183,\n", + " 'F1-1.5': 0.7958762886597938,\n", + " 'Recall-1.5': 0.8577777777777778,\n", + " 'Precision-1.5': 0.7423076923076923,\n", + " 'F1-2.5': 0.6508474576271186,\n", + " 'Recall-2.5': 0.8067226890756303,\n", + " 'Precision-2.5': 0.5454545454545454,\n", + " 'F1-3.5': 0.15151515151515152,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08547008547008547,\n", + " 'F1-4.5': 0.06896551724137931,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.037037037037037035,\n", " 'NDCG@all': 0.8873207597444019},\n", " 'CM': {'0': {'-1': 0, '0': 101, '1': 63, '2': 10, '3': 5, '4': 3, '5': 4},\n", " '1': {'-1': 0, '0': 10, '1': 45, '2': 20, '3': 6, '4': 11, '5': 8},\n", @@ -6478,12 +11097,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22122803951433004,\n", " 'Micro-F1': 0.30980392156862746,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.28486646884273,\n", - " 'F1-2': 0.3900414937759336,\n", - " 'F1-3': 0.49765258215962443,\n", - " 'F1-4': 0.0625,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.28486646884273,\n", + " 'F1-2_vs_rest': 0.3900414937759336,\n", + " 'F1-3_vs_rest': 0.49765258215962443,\n", + " 'F1-4_vs_rest': 0.0625,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7854545454545454,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6467065868263473,\n", + " 'F1-1.5': 0.7704918032786885,\n", + " 'Recall-1.5': 0.8392857142857143,\n", + " 'Precision-1.5': 0.7121212121212122,\n", + " 'F1-2.5': 0.5991902834008097,\n", + " 'Recall-2.5': 0.6218487394957983,\n", + " 'Precision-2.5': 0.578125,\n", + " 'F1-3.5': 0.058823529411764705,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.05263157894736842,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8984967091197534},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 153, '2': 18, '3': 4, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 48, '2': 35, '3': 14, '4': 3, '5': 0},\n", @@ -6510,12 +11144,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.359412793577373,\n", " 'Micro-F1': 0.32289628180039137,\n", - " 'F1-0': 0.5153846153846153,\n", - " 'F1-1': 0.29411764705882354,\n", - " 'F1-2': 0.2146341463414634,\n", - " 'F1-3': 0.31313131313131315,\n", - " 'F1-4': 0.15254237288135594,\n", - " 'F1-5': 0.6666666666666666,\n", + " 'F1-0_vs_rest': 0.5153846153846153,\n", + " 'F1-1_vs_rest': 0.29411764705882354,\n", + " 'F1-2_vs_rest': 0.2146341463414634,\n", + " 'F1-3_vs_rest': 0.31313131313131315,\n", + " 'F1-4_vs_rest': 0.15254237288135594,\n", + " 'F1-5_vs_rest': 0.6666666666666666,\n", + " 'F1-0.5': 0.8346456692913385,\n", + " 'Recall-0.5': 0.9784615384615385,\n", + " 'Precision-0.5': 0.7276887871853547,\n", + " 'F1-1.5': 0.7404580152671756,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6488294314381271,\n", + " 'F1-2.5': 0.5830721003134797,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.465,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.10377358490566038,\n", + " 'F1-4.5': 0.6666666666666666,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 1.0,\n", " 'NDCG@all': 0.9192249037770744},\n", " 'CM': {'0': {'-1': 0, '0': 67, '1': 75, '2': 31, '3': 6, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 35, '2': 28, '3': 17, '4': 16, '5': 0},\n", @@ -6542,12 +11191,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07298003526951538,\n", " 'Micro-F1': 0.09001956947162426,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07692307692307693,\n", - " 'F1-2': 0.13278008298755187,\n", - " 'F1-3': 0.12698412698412698,\n", - " 'F1-4': 0.09049773755656108,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07692307692307693,\n", + " 'F1-2_vs_rest': 0.13278008298755187,\n", + " 'F1-3_vs_rest': 0.12698412698412698,\n", + " 'F1-4_vs_rest': 0.09049773755656108,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6799387442572741,\n", + " 'Recall-1.5': 0.9866666666666667,\n", + " 'Precision-1.5': 0.5186915887850467,\n", + " 'F1-2.5': 0.5339805825242718,\n", + " 'Recall-2.5': 0.9243697478991597,\n", + " 'Precision-2.5': 0.37542662116040953,\n", + " 'F1-3.5': 0.10762331838565023,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.057692307692307696,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8879370577608351},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 72, '2': 79, '3': 17, '4': 17, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 32, '3': 21, '4': 40, '5': 0},\n", @@ -6574,12 +11238,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10501598623514531,\n", " 'Micro-F1': 0.13894324853228962,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.09,\n", - " 'F1-2': 0.12682926829268293,\n", - " 'F1-3': 0.27586206896551724,\n", - " 'F1-4': 0.13740458015267176,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.09,\n", + " 'F1-2_vs_rest': 0.12682926829268293,\n", + " 'F1-3_vs_rest': 0.27586206896551724,\n", + " 'F1-4_vs_rest': 0.13740458015267176,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7044025157232704,\n", + " 'Recall-1.5': 0.9955555555555555,\n", + " 'Precision-1.5': 0.5450121654501217,\n", + " 'F1-2.5': 0.5290023201856149,\n", + " 'Recall-2.5': 0.957983193277311,\n", + " 'Precision-2.5': 0.36538461538461536,\n", + " 'F1-3.5': 0.15602836879432624,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.0873015873015873,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8914288151941983},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 59, '3': 32, '4': 4, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 22, '3': 51, '4': 17, '5': 1},\n", @@ -6606,12 +11285,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.3065987686299177,\n", " 'Micro-F1': 0.4050880626223092,\n", - " 'F1-0': 0.39316239316239315,\n", - " 'F1-1': 0.3014705882352941,\n", - " 'F1-2': 0.48201438848920863,\n", - " 'F1-3': 0.5050505050505051,\n", - " 'F1-4': 0.15789473684210525,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.39316239316239315,\n", + " 'F1-1_vs_rest': 0.3014705882352941,\n", + " 'F1-2_vs_rest': 0.48201438848920863,\n", + " 'F1-3_vs_rest': 0.5050505050505051,\n", + " 'F1-4_vs_rest': 0.15789473684210525,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8197969543147208,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6976241900647948,\n", + " 'F1-1.5': 0.810077519379845,\n", + " 'Recall-1.5': 0.9288888888888889,\n", + " 'Precision-1.5': 0.718213058419244,\n", + " 'F1-2.5': 0.6134453781512605,\n", + " 'Recall-2.5': 0.6134453781512605,\n", + " 'Precision-2.5': 0.6134453781512605,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.16,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9069509455784583},\n", " 'CM': {'0': {'-1': 0, '0': 46, '1': 115, '2': 19, '3': 2, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 41, '2': 44, '3': 10, '4': 3, '5': 0},\n", @@ -6638,12 +11332,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.052398496915138176,\n", " 'Micro-F1': 0.06374501992031872,\n", - " 'F1-0': 0.08421052631578947,\n", - " 'F1-1': 0.0,\n", - " 'F1-2': 0.038834951456310676,\n", - " 'F1-3': 0.1568627450980392,\n", - " 'F1-4': 0.034482758620689655,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.08421052631578947,\n", + " 'F1-1_vs_rest': 0.0,\n", + " 'F1-2_vs_rest': 0.038834951456310676,\n", + " 'F1-3_vs_rest': 0.1568627450980392,\n", + " 'F1-4_vs_rest': 0.034482758620689655,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7862407862407862,\n", + " 'Recall-0.5': 0.9937888198757764,\n", + " 'Precision-0.5': 0.6504065040650406,\n", + " 'F1-1.5': 0.6488095238095238,\n", + " 'Recall-1.5': 0.9819819819819819,\n", + " 'Precision-1.5': 0.48444444444444446,\n", + " 'F1-2.5': 0.45493562231759654,\n", + " 'Recall-2.5': 0.9137931034482759,\n", + " 'Precision-2.5': 0.3028571428571429,\n", + " 'F1-3.5': 0.04580152671755725,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.023809523809523808,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8723762759163569},\n", " 'CM': {'0': {'-1': 96, '0': 4, '1': 20, '2': 31, '3': 11, '4': 23, '5': 1},\n", " '1': {'-1': 50, '0': 0, '1': 0, '2': 12, '3': 13, '4': 23, '5': 2},\n", @@ -6651,6 +11360,53 @@ " '3': {'-1': 51, '0': 0, '1': 0, '2': 4, '3': 8, '4': 35, '5': 6},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 1, '3': 1, '4': 2, '5': 1},\n", " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10878683601647034,\n", + " 'Cohen': 0.152539069162285,\n", + " 'Spearman': 0.6938344515526925,\n", + " 'Kendall': 0.5980867072597336,\n", + " 'Krippendorff': 0.5864204698396918,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7509803921568627,\n", + " 'TA-4.0': 0.9607843137254902,\n", + " 'Acc': 0.33137254901960783,\n", + " 'MAE': 0.7928104575163394,\n", + " 'MSE': 1.0224400871459691,\n", + " 'CA-0': 0.1774193548387097,\n", + " 'CA-1': 0.32,\n", + " 'CA-2': 0.6226415094339622,\n", + " 'CA-3': 0.36893203883495146,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.22511574844908178,\n", + " 'Micro-F1': 0.33137254901960783,\n", + " 'F1-0_vs_rest': 0.3,\n", + " 'F1-1_vs_rest': 0.24242424242424243,\n", + " 'F1-2_vs_rest': 0.40615384615384614,\n", + " 'F1-3_vs_rest': 0.4021164021164021,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8075,\n", + " 'Recall-0.5': 0.9969135802469136,\n", + " 'Precision-0.5': 0.6785714285714286,\n", + " 'F1-1.5': 0.7873134328358209,\n", + " 'Recall-1.5': 0.9419642857142857,\n", + " 'Precision-1.5': 0.6762820512820513,\n", + " 'F1-2.5': 0.4834123222748815,\n", + " 'Recall-2.5': 0.4322033898305085,\n", + " 'Precision-2.5': 0.5483870967741935,\n", + " 'F1-3.5': 0.09090909090909091,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9143245263471723},\n", + " 'CM': {'0': {'-1': 0, '0': 33, '1': 119, '2': 30, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 32, '2': 56, '3': 11, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 13, '2': 66, '3': 24, '4': 3, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 0, '2': 62, '3': 38, '4': 3, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.16597729293282615,\n", " 'Cohen': 0.1854538415113246,\n", " 'Spearman': 0.6436484930824882,\n", @@ -6670,12 +11426,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.30798921285156383,\n", " 'Micro-F1': 0.34120171673819744,\n", - " 'F1-0': 0.42857142857142855,\n", - " 'F1-1': 0.2011173184357542,\n", - " 'F1-2': 0.33766233766233766,\n", - " 'F1-3': 0.4639175257731959,\n", - " 'F1-4': 0.16666666666666666,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.42857142857142855,\n", + " 'F1-1_vs_rest': 0.2011173184357542,\n", + " 'F1-2_vs_rest': 0.33766233766233766,\n", + " 'F1-3_vs_rest': 0.4639175257731959,\n", + " 'F1-4_vs_rest': 0.16666666666666666,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8192090395480226,\n", + " 'Recall-0.5': 0.9508196721311475,\n", + " 'Precision-0.5': 0.7196029776674938,\n", + " 'F1-1.5': 0.7637051039697542,\n", + " 'Recall-1.5': 0.9439252336448598,\n", + " 'Precision-1.5': 0.6412698412698413,\n", + " 'F1-2.5': 0.6375838926174496,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.5307262569832403,\n", + " 'F1-3.5': 0.19230769230769232,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.11235955056179775,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.8870842125450512},\n", " 'CM': {'0': {'-1': 25, '0': 48, '1': 62, '2': 41, '3': 5, '4': 3, '5': 2},\n", " '1': {'-1': 9, '0': 11, '1': 18, '2': 34, '3': 11, '4': 16, '5': 1},\n", @@ -6702,12 +11473,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11851453443619704,\n", " 'Micro-F1': 0.14677103718199608,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.08376963350785341,\n", - " 'F1-2': 0.14960629921259844,\n", - " 'F1-3': 0.2672413793103448,\n", - " 'F1-4': 0.13793103448275862,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.08376963350785341,\n", + " 'F1-2_vs_rest': 0.14960629921259844,\n", + " 'F1-3_vs_rest': 0.2672413793103448,\n", + " 'F1-4_vs_rest': 0.13793103448275862,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.6833855799373041,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5278450363196125,\n", + " 'F1-2.5': 0.5416666666666666,\n", + " 'Recall-2.5': 0.8739495798319328,\n", + " 'Precision-2.5': 0.39245283018867927,\n", + " 'F1-3.5': 0.15789473684210525,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08759124087591241,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8772886572077317},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 76, '2': 73, '3': 23, '4': 6, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 41, '3': 32, '4': 17, '5': 2},\n", @@ -6715,7 +11501,54 @@ " '3': {'-1': 0, '0': 0, '1': 0, '2': 15, '3': 31, '4': 58, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'fr': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06362515290936376,\n", + " 'fr': {'phi-4': {'metrics': {'Fleiss': 0.18072474074377248,\n", + " 'Cohen': 0.19381585505218069,\n", + " 'Spearman': 0.6118911419547828,\n", + " 'Kendall': 0.507501915945731,\n", + " 'Krippendorff': 0.524659445400935,\n", + " 'Invalid': 9,\n", + " 'TA-2.0': 0.703187250996016,\n", + " 'TA-4.0': 0.8884462151394422,\n", + " 'Acc': 0.3645418326693227,\n", + " 'MAE': 0.9243027888446214,\n", + " 'MSE': 1.6658919876051348,\n", + " 'CA-0': 0.43783783783783786,\n", + " 'CA-1': 0.21875,\n", + " 'CA-2': 0.26666666666666666,\n", + " 'CA-3': 0.504950495049505,\n", + " 'CA-4': 0.15384615384615385,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.255745120135307,\n", + " 'Micro-F1': 0.3645418326693227,\n", + " 'F1-0_vs_rest': 0.5848375451263538,\n", + " 'F1-1_vs_rest': 0.21212121212121213,\n", + " 'F1-2_vs_rest': 0.27053140096618356,\n", + " 'F1-3_vs_rest': 0.4063745019920319,\n", + " 'F1-4_vs_rest': 0.06060606060606061,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8418156808803301,\n", + " 'Recall-0.5': 0.9652996845425867,\n", + " 'Precision-0.5': 0.7463414634146341,\n", + " 'F1-1.5': 0.7410207939508506,\n", + " 'Recall-1.5': 0.8868778280542986,\n", + " 'Precision-1.5': 0.6363636363636364,\n", + " 'F1-2.5': 0.5590062111801242,\n", + " 'Recall-2.5': 0.7758620689655172,\n", + " 'Precision-2.5': 0.4368932038834951,\n", + " 'F1-3.5': 0.14084507042253522,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.08928571428571429,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8752006625762642},\n", + " 'CM': {'0': {'-1': 1, '0': 81, '1': 59, '2': 25, '3': 15, '4': 4, '5': 1},\n", + " '1': {'-1': 4, '0': 8, '1': 21, '2': 30, '3': 24, '4': 12, '5': 1},\n", + " '2': {'-1': 1, '0': 2, '1': 16, '2': 28, '3': 50, '4': 9, '5': 0},\n", + " '3': {'-1': 3, '0': 1, '1': 6, '2': 19, '3': 51, '4': 24, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 10, '4': 2, '5': 1},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06362515290936376,\n", " 'Cohen': 0.10511269512206667,\n", " 'Spearman': 0.6169962220796649,\n", " 'Kendall': 0.5219195837240582,\n", @@ -6734,12 +11567,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2112006770953666,\n", " 'Micro-F1': 0.2759295499021526,\n", - " 'F1-0': 0.20095693779904306,\n", - " 'F1-1': 0.2593856655290102,\n", - " 'F1-2': 0.2648401826484018,\n", - " 'F1-3': 0.41702127659574467,\n", - " 'F1-4': 0.125,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.20095693779904306,\n", + " 'F1-1_vs_rest': 0.2593856655290102,\n", + " 'F1-2_vs_rest': 0.2648401826484018,\n", + " 'F1-3_vs_rest': 0.41702127659574467,\n", + " 'F1-4_vs_rest': 0.125,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7945879458794588,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6618852459016393,\n", + " 'F1-1.5': 0.7461538461538462,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6576271186440678,\n", + " 'F1-2.5': 0.5714285714285714,\n", + " 'Recall-2.5': 0.7226890756302521,\n", + " 'Precision-2.5': 0.4725274725274725,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.11764705882352941,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.898344917756121},\n", " 'CM': {'0': {'-1': 0, '0': 21, '1': 124, '2': 28, '3': 9, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 38, '2': 32, '3': 18, '4': 10, '5': 0},\n", @@ -6766,12 +11614,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2787877657702042,\n", " 'Micro-F1': 0.3561643835616438,\n", - " 'F1-0': 0.6,\n", - " 'F1-1': 0.3116883116883117,\n", - " 'F1-2': 0.3626943005181347,\n", - " 'F1-3': 0.23809523809523808,\n", - " 'F1-4': 0.10619469026548672,\n", - " 'F1-5': 0.05405405405405406,\n", + " 'F1-0_vs_rest': 0.6,\n", + " 'F1-1_vs_rest': 0.3116883116883117,\n", + " 'F1-2_vs_rest': 0.3626943005181347,\n", + " 'F1-3_vs_rest': 0.23809523809523808,\n", + " 'F1-4_vs_rest': 0.10619469026548672,\n", + " 'F1-5_vs_rest': 0.05405405405405406,\n", + " 'F1-0.5': 0.8490566037735849,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7553956834532374,\n", + " 'F1-1.5': 0.7984344422700587,\n", + " 'Recall-1.5': 0.9066666666666666,\n", + " 'Precision-1.5': 0.7132867132867133,\n", + " 'F1-2.5': 0.6352201257861635,\n", + " 'Recall-2.5': 0.8487394957983193,\n", + " 'Precision-2.5': 0.507537688442211,\n", + " 'F1-3.5': 0.14666666666666667,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08148148148148149,\n", + " 'F1-4.5': 0.05405405405405406,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.02857142857142857,\n", " 'NDCG@all': 0.8934492839155558},\n", " 'CM': {'0': {'-1': 0, '0': 84, '1': 74, '2': 15, '3': 5, '4': 3, '5': 5},\n", " '1': {'-1': 0, '0': 10, '1': 36, '2': 23, '3': 11, '4': 12, '5': 8},\n", @@ -6798,12 +11661,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2287673187940822,\n", " 'Micro-F1': 0.29354207436399216,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.25936599423631124,\n", - " 'F1-2': 0.37344398340248963,\n", - " 'F1-3': 0.4854368932038835,\n", - " 'F1-4': 0.18181818181818182,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.25936599423631124,\n", + " 'F1-2_vs_rest': 0.37344398340248963,\n", + " 'F1-3_vs_rest': 0.4854368932038835,\n", + " 'F1-4_vs_rest': 0.18181818181818182,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7593360995850622,\n", + " 'Recall-1.5': 0.8133333333333334,\n", + " 'Precision-1.5': 0.7120622568093385,\n", + " 'F1-2.5': 0.5394190871369294,\n", + " 'Recall-2.5': 0.5462184873949579,\n", + " 'Precision-2.5': 0.5327868852459017,\n", + " 'F1-3.5': 0.22857142857142856,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9001173990478823},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 160, '2': 13, '3': 4, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 45, '2': 36, '3': 17, '4': 2, '5': 0},\n", @@ -6830,12 +11708,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.24304336749142572,\n", " 'Micro-F1': 0.31702544031311153,\n", - " 'F1-0': 0.49429657794676807,\n", - " 'F1-1': 0.29133858267716534,\n", - " 'F1-2': 0.2094240837696335,\n", - " 'F1-3': 0.32160804020100503,\n", - " 'F1-4': 0.1415929203539823,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.49429657794676807,\n", + " 'F1-1_vs_rest': 0.29133858267716534,\n", + " 'F1-2_vs_rest': 0.2094240837696335,\n", + " 'F1-3_vs_rest': 0.32160804020100503,\n", + " 'F1-4_vs_rest': 0.1415929203539823,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8247694334650857,\n", + " 'Recall-0.5': 0.963076923076923,\n", + " 'Precision-0.5': 0.7211981566820277,\n", + " 'F1-1.5': 0.7287128712871287,\n", + " 'Recall-1.5': 0.8177777777777778,\n", + " 'Precision-1.5': 0.6571428571428571,\n", + " 'F1-2.5': 0.5987261146496815,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.48205128205128206,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9048978448480057},\n", " 'CM': {'0': {'-1': 0, '0': 65, '1': 82, '2': 22, '3': 13, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 6, '1': 37, '2': 32, '3': 12, '4': 13, '5': 0},\n", @@ -6862,12 +11755,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12586077068779725,\n", " 'Micro-F1': 0.15459882583170254,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.15384615384615385,\n", - " 'F1-2': 0.1991701244813278,\n", - " 'F1-3': 0.2613065326633166,\n", - " 'F1-4': 0.11956521739130435,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.15384615384615385,\n", + " 'F1-2_vs_rest': 0.1991701244813278,\n", + " 'F1-3_vs_rest': 0.2613065326633166,\n", + " 'F1-4_vs_rest': 0.11956521739130435,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6932907348242812,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5411471321695761,\n", + " 'F1-2.5': 0.5402597402597402,\n", + " 'Recall-2.5': 0.8739495798319328,\n", + " 'Precision-2.5': 0.39097744360902253,\n", + " 'F1-3.5': 0.13978494623655913,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.07602339181286549,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8841606882232718},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 84, '2': 66, '3': 18, '4': 16, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 16, '2': 32, '3': 18, '4': 34, '5': 0},\n", @@ -6894,12 +11802,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09087318076434688,\n", " 'Micro-F1': 0.11764705882352941,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.05102040816326531,\n", - " 'F1-2': 0.14953271028037382,\n", - " 'F1-3': 0.22388059701492538,\n", - " 'F1-4': 0.12080536912751678,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.05102040816326531,\n", + " 'F1-2_vs_rest': 0.14953271028037382,\n", + " 'F1-3_vs_rest': 0.22388059701492538,\n", + " 'F1-4_vs_rest': 0.12080536912751678,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.6990595611285266,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5399515738498789,\n", + " 'F1-2.5': 0.5424528301886793,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.3770491803278688,\n", + " 'F1-3.5': 0.14102564102564102,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07801418439716312,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8943926676385515},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 63, '3': 26, '4': 7, '5': 0},\n", " '1': {'-1': 1, '0': 0, '1': 5, '2': 27, '3': 44, '4': 21, '5': 2},\n", @@ -6926,12 +11849,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2637798796000384,\n", " 'Micro-F1': 0.3639921722113503,\n", - " 'F1-0': 0.3684210526315789,\n", - " 'F1-1': 0.2661596958174905,\n", - " 'F1-2': 0.42962962962962964,\n", - " 'F1-3': 0.4784688995215311,\n", - " 'F1-4': 0.04,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3684210526315789,\n", + " 'F1-1_vs_rest': 0.2661596958174905,\n", + " 'F1-2_vs_rest': 0.42962962962962964,\n", + " 'F1-3_vs_rest': 0.4784688995215311,\n", + " 'F1-4_vs_rest': 0.04,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.818639798488665,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6929637526652452,\n", + " 'F1-1.5': 0.7796610169491526,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.6764705882352942,\n", + " 'F1-2.5': 0.6053639846743295,\n", + " 'Recall-2.5': 0.6638655462184874,\n", + " 'Precision-2.5': 0.5563380281690141,\n", + " 'F1-3.5': 0.11538461538461539,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.08108108108108109,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8965302081569092},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 110, '2': 26, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 35, '2': 44, '3': 13, '4': 8, '5': 0},\n", @@ -6958,12 +11896,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1161079336924143,\n", " 'Micro-F1': 0.15384615384615385,\n", - " 'F1-0': 0.029411764705882353,\n", - " 'F1-1': 0.06349206349206349,\n", - " 'F1-2': 0.19148936170212766,\n", - " 'F1-3': 0.3516483516483517,\n", - " 'F1-4': 0.06060606060606061,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.029411764705882353,\n", + " 'F1-1_vs_rest': 0.06349206349206349,\n", + " 'F1-2_vs_rest': 0.19148936170212766,\n", + " 'F1-3_vs_rest': 0.3516483516483517,\n", + " 'F1-4_vs_rest': 0.06060606060606061,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7950310559006211,\n", + " 'Recall-0.5': 0.9922480620155039,\n", + " 'Precision-0.5': 0.6632124352331606,\n", + " 'F1-1.5': 0.6486486486486487,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.48,\n", + " 'F1-2.5': 0.48484848484848486,\n", + " 'Recall-2.5': 0.9090909090909091,\n", + " 'Precision-2.5': 0.3305785123966942,\n", + " 'F1-3.5': 0.08108108108108109,\n", + " 'Recall-3.5': 0.5,\n", + " 'Precision-3.5': 0.04411764705882353,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8356932100976866},\n", " 'CM': {'0': {'-1': 120, '0': 1, '1': 16, '2': 32, '3': 8, '4': 8, '5': 1},\n", " '1': {'-1': 55, '0': 1, '1': 2, '2': 9, '3': 15, '4': 17, '5': 1},\n", @@ -6971,6 +11924,53 @@ " '3': {'-1': 66, '0': 0, '1': 0, '2': 4, '3': 16, '4': 15, '5': 3},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 0, '3': 3, '4': 2, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.180527320889546,\n", + " 'Cohen': 0.21268735851010834,\n", + " 'Spearman': 0.684715626756924,\n", + " 'Kendall': 0.5904873212279812,\n", + " 'Krippendorff': 0.6181251861397463,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7627450980392156,\n", + " 'TA-4.0': 0.9627450980392157,\n", + " 'Acc': 0.3862745098039216,\n", + " 'MAE': 0.7326797385620912,\n", + " 'MSE': 0.9570806100217862,\n", + " 'CA-0': 0.3118279569892473,\n", + " 'CA-1': 0.4,\n", + " 'CA-2': 0.6226415094339622,\n", + " 'CA-3': 0.32038834951456313,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2620799278160441,\n", + " 'Micro-F1': 0.3862745098039216,\n", + " 'F1-0_vs_rest': 0.46963562753036436,\n", + " 'F1-1_vs_rest': 0.29739776951672864,\n", + " 'F1-2_vs_rest': 0.4217252396166134,\n", + " 'F1-3_vs_rest': 0.38372093023255816,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8305304010349288,\n", + " 'Recall-0.5': 0.9907407407407407,\n", + " 'Precision-0.5': 0.7149220489977728,\n", + " 'F1-1.5': 0.7817460317460317,\n", + " 'Recall-1.5': 0.8794642857142857,\n", + " 'Precision-1.5': 0.7035714285714286,\n", + " 'F1-2.5': 0.450261780104712,\n", + " 'Recall-2.5': 0.3644067796610169,\n", + " 'Precision-2.5': 0.589041095890411,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8889693056880895},\n", + " 'CM': {'0': {'-1': 0, '0': 58, '1': 103, '2': 22, '3': 2, '4': 1, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 40, '2': 49, '3': 7, '4': 2, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 21, '2': 66, '3': 18, '4': 0, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 5, '2': 64, '3': 33, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 7, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1354924433004306,\n", " 'Cohen': 0.1587893213599848,\n", " 'Spearman': 0.6674861259461091,\n", @@ -6990,12 +11990,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23734296325446383,\n", " 'Micro-F1': 0.3165618448637317,\n", - " 'F1-0': 0.5396825396825397,\n", - " 'F1-1': 0.17751479289940827,\n", - " 'F1-2': 0.345679012345679,\n", - " 'F1-3': 0.22784810126582278,\n", - " 'F1-4': 0.13333333333333333,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5396825396825397,\n", + " 'F1-1_vs_rest': 0.17751479289940827,\n", + " 'F1-2_vs_rest': 0.345679012345679,\n", + " 'F1-3_vs_rest': 0.22784810126582278,\n", + " 'F1-4_vs_rest': 0.13333333333333333,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8347578347578347,\n", + " 'Recall-0.5': 0.9451612903225807,\n", + " 'Precision-0.5': 0.7474489795918368,\n", + " 'F1-1.5': 0.7654784240150094,\n", + " 'Recall-1.5': 0.9272727272727272,\n", + " 'Precision-1.5': 0.6517571884984026,\n", + " 'F1-2.5': 0.6275862068965518,\n", + " 'Recall-2.5': 0.7647058823529411,\n", + " 'Precision-2.5': 0.5321637426900585,\n", + " 'F1-3.5': 0.16666666666666666,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.09401709401709402,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8985141342922355},\n", " 'CM': {'0': {'-1': 19, '0': 68, '1': 54, '2': 34, '3': 5, '4': 5, '5': 1},\n", " '1': {'-1': 10, '0': 11, '1': 15, '2': 39, '3': 10, '4': 14, '5': 1},\n", @@ -7022,12 +12037,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12332508204998106,\n", " 'Micro-F1': 0.15459882583170254,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.08602150537634409,\n", - " 'F1-2': 0.16091954022988506,\n", - " 'F1-3': 0.2807017543859649,\n", - " 'F1-4': 0.12,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.08602150537634409,\n", + " 'F1-2_vs_rest': 0.16091954022988506,\n", + " 'F1-3_vs_rest': 0.2807017543859649,\n", + " 'F1-4_vs_rest': 0.12,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6833073322932918,\n", + " 'Recall-1.5': 0.9733333333333334,\n", + " 'Precision-1.5': 0.5264423076923077,\n", + " 'F1-2.5': 0.5473684210526316,\n", + " 'Recall-2.5': 0.8739495798319328,\n", + " 'Precision-2.5': 0.39846743295019155,\n", + " 'F1-3.5': 0.14473684210526316,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08029197080291971,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8955451032568394},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 72, '2': 78, '3': 17, '4': 10, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 44, '3': 29, '4': 19, '5': 0},\n", @@ -7035,7 +12065,54 @@ " '3': {'-1': 0, '0': 0, '1': 3, '2': 12, '3': 32, '4': 57, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'nl': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10490512706951376,\n", + " 'nl': {'phi-4': {'metrics': {'Fleiss': 0.19749905527500086,\n", + " 'Cohen': 0.21062413408576375,\n", + " 'Spearman': 0.5962768953243347,\n", + " 'Kendall': 0.49417415317567037,\n", + " 'Krippendorff': 0.4962034728408595,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7025440313111546,\n", + " 'TA-4.0': 0.863013698630137,\n", + " 'Acc': 0.37377690802348335,\n", + " 'MAE': 0.9530332681017614,\n", + " 'MSE': 1.8063709502065668,\n", + " 'CA-0': 0.43548387096774194,\n", + " 'CA-1': 0.22,\n", + " 'CA-2': 0.330188679245283,\n", + " 'CA-3': 0.4519230769230769,\n", + " 'CA-4': 0.38461538461538464,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3207586938773494,\n", + " 'Micro-F1': 0.37377690802348335,\n", + " 'F1-0_vs_rest': 0.5848375451263538,\n", + " 'F1-1_vs_rest': 0.2328042328042328,\n", + " 'F1-2_vs_rest': 0.3125,\n", + " 'F1-3_vs_rest': 0.3821138211382114,\n", + " 'F1-4_vs_rest': 0.12658227848101267,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.8456375838926175,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.75,\n", + " 'F1-1.5': 0.7410071942446043,\n", + " 'Recall-1.5': 0.9155555555555556,\n", + " 'Precision-1.5': 0.622356495468278,\n", + " 'F1-2.5': 0.5421686746987951,\n", + " 'Recall-2.5': 0.7563025210084033,\n", + " 'Precision-2.5': 0.4225352112676056,\n", + " 'F1-3.5': 0.16279069767441862,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.09859154929577464,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", + " 'NDCG@all': 0.8878042159771785},\n", + " 'CM': {'0': {'-1': 0, '0': 81, '1': 49, '2': 30, '3': 19, '4': 6, '5': 1},\n", + " '1': {'-1': 0, '0': 9, '1': 22, '2': 32, '3': 27, '4': 9, '5': 1},\n", + " '2': {'-1': 0, '0': 1, '1': 10, '2': 35, '3': 42, '4': 16, '5': 2},\n", + " '3': {'-1': 0, '0': 0, '1': 8, '2': 20, '3': 47, '4': 29, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 7, '4': 5, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10490512706951376,\n", " 'Cohen': 0.14144702299695477,\n", " 'Spearman': 0.6143398745511875,\n", " 'Kendall': 0.5252208293659809,\n", @@ -7054,12 +12131,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23587008131798212,\n", " 'Micro-F1': 0.3111545988258317,\n", - " 'F1-0': 0.22748815165876776,\n", - " 'F1-1': 0.21978021978021978,\n", - " 'F1-2': 0.34509803921568627,\n", - " 'F1-3': 0.4978540772532189,\n", - " 'F1-4': 0.125,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.22748815165876776,\n", + " 'F1-1_vs_rest': 0.21978021978021978,\n", + " 'F1-2_vs_rest': 0.34509803921568627,\n", + " 'F1-3_vs_rest': 0.4978540772532189,\n", + " 'F1-4_vs_rest': 0.125,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7990135635018496,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6666666666666666,\n", + " 'F1-1.5': 0.7323420074349443,\n", + " 'Recall-1.5': 0.8755555555555555,\n", + " 'Precision-1.5': 0.6293929712460063,\n", + " 'F1-2.5': 0.5865724381625441,\n", + " 'Recall-2.5': 0.6974789915966386,\n", + " 'Precision-2.5': 0.5060975609756098,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8923656274873517},\n", " 'CM': {'0': {'-1': 0, '0': 24, '1': 116, '2': 34, '3': 8, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 30, '2': 45, '3': 18, '4': 7, '5': 0},\n", @@ -7086,12 +12178,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.31887113331322364,\n", " 'Micro-F1': 0.3953033268101761,\n", - " 'F1-0': 0.6458333333333334,\n", - " 'F1-1': 0.3722943722943723,\n", - " 'F1-2': 0.35978835978835977,\n", - " 'F1-3': 0.27380952380952384,\n", - " 'F1-4': 0.11864406779661017,\n", - " 'F1-5': 0.14285714285714285,\n", + " 'F1-0_vs_rest': 0.6458333333333334,\n", + " 'F1-1_vs_rest': 0.3722943722943723,\n", + " 'F1-2_vs_rest': 0.35978835978835977,\n", + " 'F1-3_vs_rest': 0.27380952380952384,\n", + " 'F1-4_vs_rest': 0.11864406779661017,\n", + " 'F1-5_vs_rest': 0.14285714285714285,\n", + " 'F1-0.5': 0.8610354223433242,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7726161369193154,\n", + " 'F1-1.5': 0.7952286282306164,\n", + " 'Recall-1.5': 0.8888888888888888,\n", + " 'Precision-1.5': 0.7194244604316546,\n", + " 'F1-2.5': 0.6178343949044586,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.49743589743589745,\n", + " 'F1-3.5': 0.136986301369863,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.07633587786259542,\n", + " 'F1-4.5': 0.14285714285714285,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.07692307692307693,\n", " 'NDCG@all': 0.8838794121135759},\n", " 'CM': {'0': {'-1': 0, '0': 93, '1': 64, '2': 13, '3': 6, '4': 5, '5': 5},\n", " '1': {'-1': 0, '0': 8, '1': 43, '2': 18, '3': 10, '4': 14, '5': 7},\n", @@ -7118,12 +12225,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.19758125613181132,\n", " 'Micro-F1': 0.28823529411764703,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.2711864406779661,\n", - " 'F1-2': 0.3950617283950617,\n", - " 'F1-3': 0.4467005076142132,\n", - " 'F1-4': 0.0,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.2711864406779661,\n", + " 'F1-2_vs_rest': 0.3950617283950617,\n", + " 'F1-3_vs_rest': 0.4467005076142132,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7835550181378477,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6441351888667992,\n", + " 'F1-1.5': 0.7526427061310782,\n", + " 'Recall-1.5': 0.7946428571428571,\n", + " 'Precision-1.5': 0.714859437751004,\n", + " 'F1-2.5': 0.5478260869565217,\n", + " 'Recall-2.5': 0.5338983050847458,\n", + " 'Precision-2.5': 0.5625,\n", + " 'F1-3.5': 0.06060606060606061,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.05555555555555555,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9046818520982339},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 160, '2': 16, '3': 3, '4': 0, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 48, '2': 35, '3': 15, '4': 2, '5': 0},\n", @@ -7150,12 +12272,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2254903489772561,\n", " 'Micro-F1': 0.29354207436399216,\n", - " 'F1-0': 0.484375,\n", - " 'F1-1': 0.2777777777777778,\n", - " 'F1-2': 0.15217391304347827,\n", - " 'F1-3': 0.2898550724637681,\n", - " 'F1-4': 0.1487603305785124,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.484375,\n", + " 'F1-1_vs_rest': 0.2777777777777778,\n", + " 'F1-2_vs_rest': 0.15217391304347827,\n", + " 'F1-3_vs_rest': 0.2898550724637681,\n", + " 'F1-4_vs_rest': 0.1487603305785124,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8276762402088773,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7188208616780045,\n", + " 'F1-1.5': 0.7315175097276264,\n", + " 'Recall-1.5': 0.8355555555555556,\n", + " 'Precision-1.5': 0.6505190311418685,\n", + " 'F1-2.5': 0.593939393939394,\n", + " 'Recall-2.5': 0.8235294117647058,\n", + " 'Precision-2.5': 0.46445497630331756,\n", + " 'F1-3.5': 0.17886178861788618,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.10185185185185185,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9073660140657527},\n", " 'CM': {'0': {'-1': 0, '0': 62, '1': 84, '2': 25, '3': 9, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 35, '2': 29, '3': 18, '4': 14, '5': 0},\n", @@ -7182,12 +12319,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08500385097208112,\n", " 'Micro-F1': 0.10567514677103718,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.0855614973262032,\n", - " 'F1-2': 0.19130434782608696,\n", - " 'F1-3': 0.1414141414141414,\n", - " 'F1-4': 0.09174311926605505,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.0855614973262032,\n", + " 'F1-2_vs_rest': 0.19130434782608696,\n", + " 'F1-3_vs_rest': 0.1414141414141414,\n", + " 'F1-4_vs_rest': 0.09174311926605505,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.687211093990755,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5259433962264151,\n", + " 'F1-2.5': 0.5298329355608592,\n", + " 'Recall-2.5': 0.9327731092436975,\n", + " 'Precision-2.5': 0.37,\n", + " 'F1-3.5': 0.1085972850678733,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.05825242718446602,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8813650869255497},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 77, '2': 67, '3': 28, '4': 14, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 28, '3': 24, '4': 39, '5': 1},\n", @@ -7214,12 +12366,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.14449612430812778,\n", " 'Micro-F1': 0.13725490196078433,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.08737864077669903,\n", - " 'F1-2': 0.13023255813953488,\n", - " 'F1-3': 0.2733812949640288,\n", - " 'F1-4': 0.12598425196850394,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.08737864077669903,\n", + " 'F1-2_vs_rest': 0.13023255813953488,\n", + " 'F1-3_vs_rest': 0.2733812949640288,\n", + " 'F1-4_vs_rest': 0.12598425196850394,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.7038216560509554,\n", + " 'Recall-1.5': 0.9866071428571429,\n", + " 'Precision-1.5': 0.5470297029702971,\n", + " 'F1-2.5': 0.5520581113801453,\n", + " 'Recall-2.5': 0.9661016949152542,\n", + " 'Precision-2.5': 0.3864406779661017,\n", + " 'F1-3.5': 0.14814814814814814,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08333333333333333,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.9000938222966306},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 94, '2': 61, '3': 24, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 31, '3': 46, '4': 11, '5': 3},\n", @@ -7246,12 +12413,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2829278894056704,\n", " 'Micro-F1': 0.37573385518590996,\n", - " 'F1-0': 0.36123348017621143,\n", - " 'F1-1': 0.2813688212927757,\n", - " 'F1-2': 0.4076923076923077,\n", - " 'F1-3': 0.5272727272727272,\n", - " 'F1-4': 0.12,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.36123348017621143,\n", + " 'F1-1_vs_rest': 0.2813688212927757,\n", + " 'F1-2_vs_rest': 0.4076923076923077,\n", + " 'F1-3_vs_rest': 0.5272727272727272,\n", + " 'F1-4_vs_rest': 0.12,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8176100628930818,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6914893617021277,\n", + " 'F1-1.5': 0.7781954887218046,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.6742671009771987,\n", + " 'F1-2.5': 0.6397058823529411,\n", + " 'Recall-2.5': 0.7310924369747899,\n", + " 'Precision-2.5': 0.5686274509803921,\n", + " 'F1-3.5': 0.15384615384615385,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.10810810810810811,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9046410710985197},\n", " 'CM': {'0': {'-1': 0, '0': 41, '1': 108, '2': 28, '3': 6, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 37, '2': 43, '3': 14, '4': 6, '5': 0},\n", @@ -7278,12 +12460,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.1764116863148725,\n", " 'Micro-F1': 0.17898832684824903,\n", - " 'F1-0': 0.18,\n", - " 'F1-1': 0.11267605633802817,\n", - " 'F1-2': 0.183206106870229,\n", - " 'F1-3': 0.2905982905982906,\n", - " 'F1-4': 0.06976744186046512,\n", - " 'F1-5': 0.2222222222222222,\n", + " 'F1-0_vs_rest': 0.18,\n", + " 'F1-1_vs_rest': 0.11267605633802817,\n", + " 'F1-2_vs_rest': 0.183206106870229,\n", + " 'F1-3_vs_rest': 0.2905982905982906,\n", + " 'F1-4_vs_rest': 0.06976744186046512,\n", + " 'F1-5_vs_rest': 0.2222222222222222,\n", + " 'F1-0.5': 0.8019323671497585,\n", + " 'Recall-0.5': 0.9940119760479041,\n", + " 'Precision-0.5': 0.6720647773279352,\n", + " 'F1-1.5': 0.6938775510204082,\n", + " 'Recall-1.5': 0.9916666666666667,\n", + " 'Precision-1.5': 0.5336322869955157,\n", + " 'F1-2.5': 0.5377358490566038,\n", + " 'Recall-2.5': 0.9047619047619048,\n", + " 'Precision-2.5': 0.3825503355704698,\n", + " 'F1-3.5': 0.10526315789473684,\n", + " 'Recall-3.5': 0.5555555555555556,\n", + " 'Precision-3.5': 0.05813953488372093,\n", + " 'F1-4.5': 0.2222222222222222,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.14285714285714285,\n", " 'NDCG@all': 0.8757754788412403},\n", " 'CM': {'0': {'-1': 96, '0': 9, '1': 20, '2': 39, '3': 14, '4': 8, '5': 0},\n", " '1': {'-1': 53, '0': 0, '1': 4, '2': 17, '3': 11, '4': 13, '5': 2},\n", @@ -7291,6 +12488,53 @@ " '3': {'-1': 50, '0': 0, '1': 0, '2': 5, '3': 17, '4': 30, '5': 2},\n", " '4': {'-1': 6, '0': 0, '1': 0, '2': 1, '3': 3, '4': 3, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.15799694327070032,\n", + " 'Cohen': 0.19207544007532185,\n", + " 'Spearman': 0.6768434765887341,\n", + " 'Kendall': 0.5805122775735712,\n", + " 'Krippendorff': 0.6020436066257648,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.756385068762279,\n", + " 'TA-4.0': 0.962671905697446,\n", + " 'Acc': 0.36738703339882123,\n", + " 'MAE': 0.7590045841519317,\n", + " 'MSE': 1.0061122025758564,\n", + " 'CA-0': 0.26344086021505375,\n", + " 'CA-1': 0.37,\n", + " 'CA-2': 0.5754716981132075,\n", + " 'CA-3': 0.38235294117647056,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2699213039736042,\n", + " 'Micro-F1': 0.36738703339882123,\n", + " 'F1-0_vs_rest': 0.4117647058823529,\n", + " 'F1-1_vs_rest': 0.2730627306273063,\n", + " 'F1-2_vs_rest': 0.3961038961038961,\n", + " 'F1-3_vs_rest': 0.43333333333333335,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8205128205128205,\n", + " 'Recall-0.5': 0.9907120743034056,\n", + " 'Precision-0.5': 0.700218818380744,\n", + " 'F1-1.5': 0.7779960707269156,\n", + " 'Recall-1.5': 0.8878923766816144,\n", + " 'Precision-1.5': 0.6923076923076923,\n", + " 'F1-2.5': 0.46766169154228854,\n", + " 'Recall-2.5': 0.4017094017094017,\n", + " 'Precision-2.5': 0.5595238095238095,\n", + " 'F1-3.5': 0.09523809523809523,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.16666666666666666,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8935872189606235},\n", + " 'CM': {'0': {'-1': 0, '0': 49, '1': 109, '2': 24, '3': 3, '4': 1, '5': 0},\n", + " '1': {'-1': 0, '0': 3, '1': 37, '2': 50, '3': 9, '4': 1, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 22, '2': 61, '3': 20, '4': 3, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 3, '2': 60, '3': 39, '4': 0, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 5, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.11857815860347998,\n", " 'Cohen': 0.13881004185948898,\n", " 'Spearman': 0.6261108170842574,\n", @@ -7310,12 +12554,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22946862423767375,\n", " 'Micro-F1': 0.3059071729957806,\n", - " 'F1-0': 0.5271966527196653,\n", - " 'F1-1': 0.2033898305084746,\n", - " 'F1-2': 0.304,\n", - " 'F1-3': 0.2441860465116279,\n", - " 'F1-4': 0.09803921568627451,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5271966527196653,\n", + " 'F1-1_vs_rest': 0.2033898305084746,\n", + " 'F1-2_vs_rest': 0.304,\n", + " 'F1-3_vs_rest': 0.2441860465116279,\n", + " 'F1-4_vs_rest': 0.09803921568627451,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.840620592383639,\n", + " 'Recall-0.5': 0.9612903225806452,\n", + " 'Precision-0.5': 0.7468671679197995,\n", + " 'F1-1.5': 0.7368421052631579,\n", + " 'Recall-1.5': 0.9074074074074074,\n", + " 'Precision-1.5': 0.620253164556962,\n", + " 'F1-2.5': 0.5815602836879432,\n", + " 'Recall-2.5': 0.7192982456140351,\n", + " 'Precision-2.5': 0.4880952380952381,\n", + " 'F1-3.5': 0.14545454545454545,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.08421052631578947,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9007244831741236},\n", " 'CM': {'0': {'-1': 22, '0': 63, '1': 48, '2': 40, '3': 7, '4': 6, '5': 0},\n", " '1': {'-1': 6, '0': 9, '1': 18, '2': 40, '3': 16, '4': 10, '5': 1},\n", @@ -7342,12 +12601,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.13630448447380356,\n", " 'Micro-F1': 0.17025440313111545,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.11458333333333333,\n", - " 'F1-2': 0.18823529411764706,\n", - " 'F1-3': 0.2857142857142857,\n", - " 'F1-4': 0.136986301369863,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.11458333333333333,\n", + " 'F1-2_vs_rest': 0.18823529411764706,\n", + " 'F1-3_vs_rest': 0.2857142857142857,\n", + " 'F1-4_vs_rest': 0.136986301369863,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6834645669291338,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5292682926829269,\n", + " 'F1-2.5': 0.5684210526315789,\n", + " 'Recall-2.5': 0.907563025210084,\n", + " 'Precision-2.5': 0.41379310344827586,\n", + " 'F1-3.5': 0.1610738255033557,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08955223880597014,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8962718208043471},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 73, '2': 73, '3': 23, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 11, '2': 42, '3': 30, '4': 17, '5': 0},\n", @@ -7355,7 +12629,54 @@ " '3': {'-1': 0, '0': 0, '1': 1, '2': 10, '3': 33, '4': 60, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'de': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06454252633411683,\n", + " 'de': {'phi-4': {'metrics': {'Fleiss': 0.21790219457404525,\n", + " 'Cohen': 0.230746818047172,\n", + " 'Spearman': 0.6225697181989267,\n", + " 'Kendall': 0.5152196309359278,\n", + " 'Krippendorff': 0.5229276850254223,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7103718199608611,\n", + " 'TA-4.0': 0.898238747553816,\n", + " 'Acc': 0.3933463796477495,\n", + " 'MAE': 0.9145466405740379,\n", + " 'MSE': 1.6921069797782131,\n", + " 'CA-0': 0.44086021505376344,\n", + " 'CA-1': 0.23,\n", + " 'CA-2': 0.29245283018867924,\n", + " 'CA-3': 0.5673076923076923,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.28928157771472457,\n", + " 'Micro-F1': 0.3933463796477495,\n", + " 'F1-0_vs_rest': 0.5836298932384342,\n", + " 'F1-1_vs_rest': 0.24083769633507854,\n", + " 'F1-2_vs_rest': 0.29523809523809524,\n", + " 'F1-3_vs_rest': 0.44696969696969696,\n", + " 'F1-4_vs_rest': 0.16901408450704225,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8421052631578947,\n", + " 'Recall-0.5': 0.96,\n", + " 'Precision-0.5': 0.75,\n", + " 'F1-1.5': 0.76,\n", + " 'Recall-1.5': 0.9288888888888889,\n", + " 'Precision-1.5': 0.6430769230769231,\n", + " 'F1-2.5': 0.5529411764705883,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.4253393665158371,\n", + " 'F1-3.5': 0.21052631578947367,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.13114754098360656,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8696382309232812},\n", + " 'CM': {'0': {'-1': 0, '0': 82, '1': 55, '2': 28, '3': 16, '4': 3, '5': 2},\n", + " '1': {'-1': 0, '0': 10, '1': 23, '2': 24, '3': 32, '4': 10, '5': 1},\n", + " '2': {'-1': 0, '0': 2, '1': 10, '2': 31, '3': 47, '4': 16, '5': 0},\n", + " '3': {'-1': 0, '0': 1, '1': 3, '2': 20, '3': 59, '4': 21, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 6, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06454252633411683,\n", " 'Cohen': 0.10418780577270281,\n", " 'Spearman': 0.5817115492713107,\n", " 'Kendall': 0.4914502119354108,\n", @@ -7374,12 +12695,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2086523333521653,\n", " 'Micro-F1': 0.27984344422700586,\n", - " 'F1-0': 0.21904761904761905,\n", - " 'F1-1': 0.2323943661971831,\n", - " 'F1-2': 0.2903225806451613,\n", - " 'F1-3': 0.43171806167400884,\n", - " 'F1-4': 0.0784313725490196,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.21904761904761905,\n", + " 'F1-1_vs_rest': 0.2323943661971831,\n", + " 'F1-2_vs_rest': 0.2903225806451613,\n", + " 'F1-3_vs_rest': 0.43171806167400884,\n", + " 'F1-4_vs_rest': 0.0784313725490196,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7980295566502463,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6652977412731006,\n", + " 'F1-1.5': 0.7234848484848485,\n", + " 'Recall-1.5': 0.8488888888888889,\n", + " 'Precision-1.5': 0.6303630363036303,\n", + " 'F1-2.5': 0.5428571428571428,\n", + " 'Recall-2.5': 0.6386554621848739,\n", + " 'Precision-2.5': 0.4720496894409938,\n", + " 'F1-3.5': 0.1509433962264151,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.10526315789473684,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.887835609950167},\n", " 'CM': {'0': {'-1': 0, '0': 23, '1': 117, '2': 34, '3': 9, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 1, '1': 33, '2': 42, '3': 14, '4': 10, '5': 0},\n", @@ -7406,12 +12742,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.30740814425317636,\n", " 'Micro-F1': 0.3816046966731898,\n", - " 'F1-0': 0.657439446366782,\n", - " 'F1-1': 0.3392857142857143,\n", - " 'F1-2': 0.336734693877551,\n", - " 'F1-3': 0.21428571428571427,\n", - " 'F1-4': 0.15384615384615385,\n", - " 'F1-5': 0.14285714285714285,\n", + " 'F1-0_vs_rest': 0.657439446366782,\n", + " 'F1-1_vs_rest': 0.3392857142857143,\n", + " 'F1-2_vs_rest': 0.336734693877551,\n", + " 'F1-3_vs_rest': 0.21428571428571427,\n", + " 'F1-4_vs_rest': 0.15384615384615385,\n", + " 'F1-5_vs_rest': 0.14285714285714285,\n", + " 'F1-0.5': 0.8649386084583902,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7769607843137255,\n", + " 'F1-1.5': 0.793713163064833,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.7112676056338029,\n", + " 'F1-2.5': 0.6070287539936102,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.4896907216494845,\n", + " 'F1-3.5': 0.15172413793103448,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08461538461538462,\n", + " 'F1-4.5': 0.14285714285714285,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.07692307692307693,\n", " 'NDCG@all': 0.888307241396973},\n", " 'CM': {'0': {'-1': 0, '0': 95, '1': 64, '2': 12, '3': 7, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 7, '1': 38, '2': 25, '3': 11, '4': 12, '5': 7},\n", @@ -7438,12 +12789,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.21218675173488102,\n", " 'Micro-F1': 0.273972602739726,\n", - " 'F1-0': 0.042105263157894736,\n", - " 'F1-1': 0.254957507082153,\n", - " 'F1-2': 0.36585365853658536,\n", - " 'F1-3': 0.4387755102040816,\n", - " 'F1-4': 0.17142857142857143,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.042105263157894736,\n", + " 'F1-1_vs_rest': 0.254957507082153,\n", + " 'F1-2_vs_rest': 0.36585365853658536,\n", + " 'F1-3_vs_rest': 0.4387755102040816,\n", + " 'F1-4_vs_rest': 0.17142857142857143,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78125,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6410256410256411,\n", + " 'F1-1.5': 0.7473903966597077,\n", + " 'Recall-1.5': 0.7955555555555556,\n", + " 'Precision-1.5': 0.7047244094488189,\n", + " 'F1-2.5': 0.5150214592274678,\n", + " 'Recall-2.5': 0.5042016806722689,\n", + " 'Precision-2.5': 0.5263157894736842,\n", + " 'F1-3.5': 0.21621621621621623,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.18181818181818182,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9007058645820878},\n", " 'CM': {'0': {'-1': 0, '0': 4, '1': 162, '2': 15, '3': 3, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 45, '2': 39, '3': 14, '4': 2, '5': 0},\n", @@ -7470,12 +12836,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.25579678404801615,\n", " 'Micro-F1': 0.3424657534246575,\n", - " 'F1-0': 0.5631768953068592,\n", - " 'F1-1': 0.3107569721115538,\n", - " 'F1-2': 0.2541436464088398,\n", - " 'F1-3': 0.27586206896551724,\n", - " 'F1-4': 0.1308411214953271,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5631768953068592,\n", + " 'F1-1_vs_rest': 0.3107569721115538,\n", + " 'F1-2_vs_rest': 0.2541436464088398,\n", + " 'F1-3_vs_rest': 0.27586206896551724,\n", + " 'F1-4_vs_rest': 0.1308411214953271,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8375838926174497,\n", + " 'Recall-0.5': 0.96,\n", + " 'Precision-0.5': 0.7428571428571429,\n", + " 'F1-1.5': 0.7327935222672065,\n", + " 'Recall-1.5': 0.8044444444444444,\n", + " 'Precision-1.5': 0.6728624535315985,\n", + " 'F1-2.5': 0.5942492012779552,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.4793814432989691,\n", + " 'F1-3.5': 0.16363636363636364,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.09473684210526316,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8909737450169314},\n", " 'CM': {'0': {'-1': 0, '0': 78, '1': 73, '2': 20, '3': 10, '4': 4, '5': 1},\n", " '1': {'-1': 0, '0': 8, '1': 39, '2': 24, '3': 18, '4': 11, '5': 0},\n", @@ -7502,12 +12883,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.0948310031252849,\n", " 'Micro-F1': 0.11545988258317025,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.11822660098522167,\n", - " 'F1-2': 0.15789473684210525,\n", - " 'F1-3': 0.16161616161616163,\n", - " 'F1-4': 0.09950248756218906,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.11822660098522167,\n", + " 'F1-2_vs_rest': 0.15789473684210525,\n", + " 'F1-3_vs_rest': 0.16161616161616163,\n", + " 'F1-4_vs_rest': 0.09950248756218906,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78031212484994,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.639763779527559,\n", + " 'F1-1.5': 0.6888888888888889,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5358024691358024,\n", + " 'F1-2.5': 0.527363184079602,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.3745583038869258,\n", + " 'F1-3.5': 0.11764705882352941,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.06349206349206349,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8808942097429604},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 83, '2': 64, '3': 22, '4': 14, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 12, '2': 29, '3': 25, '4': 33, '5': 1},\n", @@ -7534,12 +12930,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10670129640586483,\n", " 'Micro-F1': 0.14285714285714285,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.08653846153846154,\n", - " 'F1-2': 0.16113744075829384,\n", - " 'F1-3': 0.2777777777777778,\n", - " 'F1-4': 0.11475409836065574,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.08653846153846154,\n", + " 'F1-2_vs_rest': 0.16113744075829384,\n", + " 'F1-3_vs_rest': 0.2777777777777778,\n", + " 'F1-4_vs_rest': 0.11475409836065574,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7101910828025477,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5533498759305211,\n", + " 'F1-2.5': 0.5419664268585132,\n", + " 'Recall-2.5': 0.9495798319327731,\n", + " 'Precision-2.5': 0.37919463087248323,\n", + " 'F1-3.5': 0.13953488372093023,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.07894736842105263,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8936061435556232},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 97, '2': 55, '3': 28, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 28, '3': 48, '4': 14, '5': 1},\n", @@ -7566,12 +12977,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.28409274186480665,\n", " 'Micro-F1': 0.3933463796477495,\n", - " 'F1-0': 0.3684210526315789,\n", - " 'F1-1': 0.27205882352941174,\n", - " 'F1-2': 0.47191011235955055,\n", - " 'F1-3': 0.5395348837209303,\n", - " 'F1-4': 0.05263157894736842,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3684210526315789,\n", + " 'F1-1_vs_rest': 0.27205882352941174,\n", + " 'F1-2_vs_rest': 0.47191011235955055,\n", + " 'F1-3_vs_rest': 0.5395348837209303,\n", + " 'F1-4_vs_rest': 0.05263157894736842,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.818639798488665,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6929637526652452,\n", + " 'F1-1.5': 0.7931034482758621,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.696969696969697,\n", + " 'F1-2.5': 0.6274509803921569,\n", + " 'Recall-2.5': 0.6722689075630253,\n", + " 'Precision-2.5': 0.5882352941176471,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.08,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8981042135033636},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 117, '2': 19, '3': 5, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 37, '2': 43, '3': 15, '4': 5, '5': 0},\n", @@ -7598,12 +13024,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.14642442250271173,\n", " 'Micro-F1': 0.1902834008097166,\n", - " 'F1-0': 0.06451612903225806,\n", - " 'F1-1': 0.06741573033707865,\n", - " 'F1-2': 0.2714285714285714,\n", - " 'F1-3': 0.34615384615384615,\n", - " 'F1-4': 0.12903225806451613,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.06451612903225806,\n", + " 'F1-1_vs_rest': 0.06741573033707865,\n", + " 'F1-2_vs_rest': 0.2714285714285714,\n", + " 'F1-3_vs_rest': 0.34615384615384615,\n", + " 'F1-4_vs_rest': 0.12903225806451613,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7830423940149626,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6434426229508197,\n", + " 'F1-1.5': 0.6602564102564102,\n", + " 'Recall-1.5': 0.9903846153846154,\n", + " 'Precision-1.5': 0.4951923076923077,\n", + " 'F1-2.5': 0.5697674418604651,\n", + " 'Recall-2.5': 0.8909090909090909,\n", + " 'Precision-2.5': 0.4188034188034188,\n", + " 'F1-3.5': 0.14705882352941177,\n", + " 'Recall-3.5': 0.7142857142857143,\n", + " 'Precision-3.5': 0.08196721311475409,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8667433696165903},\n", " 'CM': {'0': {'-1': 96, '0': 3, '1': 32, '2': 42, '3': 6, '4': 7, '5': 0},\n", " '1': {'-1': 47, '0': 0, '1': 3, '2': 24, '3': 16, '4': 9, '5': 1},\n", @@ -7611,6 +13052,53 @@ " '3': {'-1': 56, '0': 0, '1': 0, '2': 6, '3': 18, '4': 22, '5': 2},\n", " '4': {'-1': 7, '0': 0, '1': 0, '2': 0, '3': 2, '4': 4, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1632721595730228,\n", + " 'Cohen': 0.1972651926907848,\n", + " 'Spearman': 0.6880854445039468,\n", + " 'Kendall': 0.5926759477956665,\n", + " 'Krippendorff': 0.6120759836155344,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7607843137254902,\n", + " 'TA-4.0': 0.9686274509803922,\n", + " 'Acc': 0.37254901960784315,\n", + " 'MAE': 0.7392156862745096,\n", + " 'MSE': 0.9505446623093681,\n", + " 'CA-0': 0.2903225806451613,\n", + " 'CA-1': 0.37,\n", + " 'CA-2': 0.6226415094339622,\n", + " 'CA-3': 0.32038834951456313,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2523974919326858,\n", + " 'Micro-F1': 0.37254901960784315,\n", + " 'F1-0_vs_rest': 0.44813278008298757,\n", + " 'F1-1_vs_rest': 0.2824427480916031,\n", + " 'F1-2_vs_rest': 0.41509433962264153,\n", + " 'F1-3_vs_rest': 0.3687150837988827,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8292682926829268,\n", + " 'Recall-0.5': 0.9969135802469136,\n", + " 'Precision-0.5': 0.7098901098901099,\n", + " 'F1-1.5': 0.7852998065764023,\n", + " 'Recall-1.5': 0.90625,\n", + " 'Precision-1.5': 0.6928327645051194,\n", + " 'F1-2.5': 0.44221105527638194,\n", + " 'Recall-2.5': 0.3728813559322034,\n", + " 'Precision-2.5': 0.5432098765432098,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.4,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9219570052241717},\n", + " 'CM': {'0': {'-1': 0, '0': 54, '1': 104, '2': 25, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 37, '2': 52, '3': 10, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 16, '2': 66, '3': 23, '4': 1, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 5, '2': 63, '3': 33, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 7, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1843475459257938,\n", " 'Cohen': 0.200375640873788,\n", " 'Spearman': 0.6188050023143503,\n", @@ -7630,12 +13118,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.3119381593141282,\n", " 'Micro-F1': 0.3609341825902335,\n", - " 'F1-0': 0.5900383141762452,\n", - " 'F1-1': 0.22727272727272727,\n", - " 'F1-2': 0.35684647302904565,\n", - " 'F1-3': 0.2893081761006289,\n", - " 'F1-4': 0.12244897959183673,\n", - " 'F1-5': 0.2857142857142857,\n", + " 'F1-0_vs_rest': 0.5900383141762452,\n", + " 'F1-1_vs_rest': 0.22727272727272727,\n", + " 'F1-2_vs_rest': 0.35684647302904565,\n", + " 'F1-3_vs_rest': 0.2893081761006289,\n", + " 'F1-4_vs_rest': 0.12244897959183673,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.8428781204111601,\n", + " 'Recall-0.5': 0.9318181818181818,\n", + " 'Precision-0.5': 0.7694369973190348,\n", + " 'F1-1.5': 0.7485148514851485,\n", + " 'Recall-1.5': 0.8790697674418605,\n", + " 'Precision-1.5': 0.6517241379310345,\n", + " 'F1-2.5': 0.5681818181818182,\n", + " 'Recall-2.5': 0.635593220338983,\n", + " 'Precision-2.5': 0.5136986301369864,\n", + " 'F1-3.5': 0.17142857142857143,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", " 'NDCG@all': 0.9125261939174565},\n", " 'CM': {'0': {'-1': 23, '0': 77, '1': 48, '2': 27, '3': 5, '4': 6, '5': 0},\n", " '1': {'-1': 7, '0': 10, '1': 20, '2': 36, '3': 14, '4': 13, '5': 0},\n", @@ -7662,12 +13165,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.13412316589431966,\n", " 'Micro-F1': 0.16634050880626222,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.1116751269035533,\n", - " 'F1-2': 0.184,\n", - " 'F1-3': 0.2807017543859649,\n", - " 'F1-4': 0.1360544217687075,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.1116751269035533,\n", + " 'F1-2_vs_rest': 0.184,\n", + " 'F1-3_vs_rest': 0.2807017543859649,\n", + " 'F1-4_vs_rest': 0.1360544217687075,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6857142857142857,\n", + " 'Recall-1.5': 0.96,\n", + " 'Precision-1.5': 0.5333333333333333,\n", + " 'F1-2.5': 0.5684210526315789,\n", + " 'Recall-2.5': 0.907563025210084,\n", + " 'Precision-2.5': 0.41379310344827586,\n", + " 'F1-3.5': 0.15789473684210525,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08759124087591241,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8888846101799195},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 77, '2': 74, '3': 17, '4': 9, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 11, '2': 40, '3': 33, '4': 15, '5': 1},\n", @@ -7675,7 +13193,54 @@ " '3': {'-1': 0, '0': 0, '1': 4, '2': 7, '3': 32, '4': 61, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'it': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06173214241285798,\n", + " 'it': {'phi-4': {'metrics': {'Fleiss': 0.24044996078800035,\n", + " 'Cohen': 0.2530726637537587,\n", + " 'Spearman': 0.6174805183356731,\n", + " 'Kendall': 0.5142921540855047,\n", + " 'Krippendorff': 0.526819018233728,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7294117647058823,\n", + " 'TA-4.0': 0.9,\n", + " 'Acc': 0.40980392156862744,\n", + " 'MAE': 0.8852941176470588,\n", + " 'MSE': 1.6316448801742915,\n", + " 'CA-0': 0.44623655913978494,\n", + " 'CA-1': 0.3,\n", + " 'CA-2': 0.3113207547169811,\n", + " 'CA-3': 0.5436893203883495,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3863470679147348,\n", + " 'Micro-F1': 0.40980392156862744,\n", + " 'F1-0_vs_rest': 0.6014492753623188,\n", + " 'F1-1_vs_rest': 0.29411764705882354,\n", + " 'F1-2_vs_rest': 0.3142857142857143,\n", + " 'F1-3_vs_rest': 0.4392156862745098,\n", + " 'F1-4_vs_rest': 0.16901408450704225,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8521505376344086,\n", + " 'Recall-0.5': 0.9783950617283951,\n", + " 'Precision-0.5': 0.7547619047619047,\n", + " 'F1-1.5': 0.7666666666666667,\n", + " 'Recall-1.5': 0.9241071428571429,\n", + " 'Precision-1.5': 0.6550632911392406,\n", + " 'F1-2.5': 0.5454545454545454,\n", + " 'Recall-2.5': 0.7627118644067796,\n", + " 'Precision-2.5': 0.42452830188679247,\n", + " 'F1-3.5': 0.21333333333333335,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.13333333333333333,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", + " 'NDCG@all': 0.8890307847692244},\n", + " 'CM': {'0': {'-1': 0, '0': 83, '1': 57, '2': 23, '3': 16, '4': 7, '5': 0},\n", + " '1': {'-1': 0, '0': 7, '1': 30, '2': 27, '3': 25, '4': 10, '5': 1},\n", + " '2': {'-1': 0, '0': 0, '1': 10, '2': 33, '3': 49, '4': 14, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 7, '2': 20, '3': 56, '4': 20, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 6, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06173214241285798,\n", " 'Cohen': 0.10228381807534659,\n", " 'Spearman': 0.5772739847353938,\n", " 'Kendall': 0.4877496825068927,\n", @@ -7694,12 +13259,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2112400487533117,\n", " 'Micro-F1': 0.27788649706457924,\n", - " 'F1-0': 0.20095693779904306,\n", - " 'F1-1': 0.22916666666666666,\n", - " 'F1-2': 0.28085106382978725,\n", - " 'F1-3': 0.4388185654008439,\n", - " 'F1-4': 0.11764705882352941,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.20095693779904306,\n", + " 'F1-1_vs_rest': 0.22916666666666666,\n", + " 'F1-2_vs_rest': 0.28085106382978725,\n", + " 'F1-3_vs_rest': 0.4388185654008439,\n", + " 'F1-4_vs_rest': 0.11764705882352941,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7945879458794588,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6618852459016393,\n", + " 'F1-1.5': 0.7161904761904762,\n", + " 'Recall-1.5': 0.8355555555555556,\n", + " 'Precision-1.5': 0.6266666666666667,\n", + " 'F1-2.5': 0.5655172413793104,\n", + " 'Recall-2.5': 0.6890756302521008,\n", + " 'Precision-2.5': 0.47953216374269003,\n", + " 'F1-3.5': 0.18867924528301888,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.13157894736842105,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8913863623277738},\n", " 'CM': {'0': {'-1': 0, '0': 21, '1': 118, '2': 33, '3': 10, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 33, '2': 36, '3': 21, '4': 8, '5': 0},\n", @@ -7726,12 +13306,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.29904766672586375,\n", " 'Micro-F1': 0.37181996086105673,\n", - " 'F1-0': 0.6293706293706294,\n", - " 'F1-1': 0.32142857142857145,\n", - " 'F1-2': 0.35467980295566504,\n", - " 'F1-3': 0.21818181818181817,\n", - " 'F1-4': 0.1415929203539823,\n", - " 'F1-5': 0.12903225806451613,\n", + " 'F1-0_vs_rest': 0.6293706293706294,\n", + " 'F1-1_vs_rest': 0.32142857142857145,\n", + " 'F1-2_vs_rest': 0.35467980295566504,\n", + " 'F1-3_vs_rest': 0.21818181818181817,\n", + " 'F1-4_vs_rest': 0.1415929203539823,\n", + " 'F1-5_vs_rest': 0.12903225806451613,\n", + " 'F1-0.5': 0.8559782608695652,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7664233576642335,\n", + " 'F1-1.5': 0.79296875,\n", + " 'Recall-1.5': 0.9022222222222223,\n", + " 'Precision-1.5': 0.7073170731707317,\n", + " 'F1-2.5': 0.5954692556634305,\n", + " 'Recall-2.5': 0.773109243697479,\n", + " 'Precision-2.5': 0.4842105263157895,\n", + " 'F1-3.5': 0.1527777777777778,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08527131782945736,\n", + " 'F1-4.5': 0.12903225806451613,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.06896551724137931,\n", " 'NDCG@all': 0.8892769479381065},\n", " 'CM': {'0': {'-1': 0, '0': 90, '1': 68, '2': 13, '3': 8, '4': 2, '5': 5},\n", " '1': {'-1': 0, '0': 8, '1': 36, '2': 25, '3': 10, '4': 15, '5': 6},\n", @@ -7758,12 +13353,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.19828577774604758,\n", " 'Micro-F1': 0.2784313725490196,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.2608695652173913,\n", - " 'F1-2': 0.36507936507936506,\n", - " 'F1-3': 0.4630541871921182,\n", - " 'F1-4': 0.06896551724137931,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.2608695652173913,\n", + " 'F1-2_vs_rest': 0.36507936507936506,\n", + " 'F1-3_vs_rest': 0.4630541871921182,\n", + " 'F1-4_vs_rest': 0.06896551724137931,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.779783393501805,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6390532544378699,\n", + " 'F1-1.5': 0.757201646090535,\n", + " 'Recall-1.5': 0.8214285714285714,\n", + " 'Precision-1.5': 0.7022900763358778,\n", + " 'F1-2.5': 0.5213675213675214,\n", + " 'Recall-2.5': 0.5169491525423728,\n", + " 'Precision-2.5': 0.5258620689655172,\n", + " 'F1-3.5': 0.12903225806451613,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.125,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8918213317029476},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 160, '2': 17, '3': 4, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 45, '2': 38, '3': 15, '4': 2, '5': 0},\n", @@ -7790,12 +13400,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23795745671497778,\n", " 'Micro-F1': 0.3150684931506849,\n", - " 'F1-0': 0.5373134328358209,\n", - " 'F1-1': 0.28688524590163933,\n", - " 'F1-2': 0.1978021978021978,\n", - " 'F1-3': 0.2641509433962264,\n", - " 'F1-4': 0.1415929203539823,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5373134328358209,\n", + " 'F1-1_vs_rest': 0.28688524590163933,\n", + " 'F1-2_vs_rest': 0.1978021978021978,\n", + " 'F1-3_vs_rest': 0.2641509433962264,\n", + " 'F1-4_vs_rest': 0.1415929203539823,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8355437665782494,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7342657342657343,\n", + " 'F1-1.5': 0.7607843137254902,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6807017543859649,\n", + " 'F1-2.5': 0.5792682926829268,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.45454545454545453,\n", + " 'F1-3.5': 0.1724137931034483,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.09900990099009901,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8949908435847219},\n", " 'CM': {'0': {'-1': 0, '0': 72, '1': 83, '2': 16, '3': 8, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 35, '2': 27, '3': 17, '4': 15, '5': 1},\n", @@ -7822,12 +13447,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10582328366976557,\n", " 'Micro-F1': 0.13111545988258316,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.11940298507462686,\n", - " 'F1-2': 0.19008264462809918,\n", - " 'F1-3': 0.2079207920792079,\n", - " 'F1-4': 0.0962566844919786,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.11940298507462686,\n", + " 'F1-2_vs_rest': 0.19008264462809918,\n", + " 'F1-3_vs_rest': 0.2079207920792079,\n", + " 'F1-4_vs_rest': 0.0962566844919786,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.688783570300158,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5343137254901961,\n", + " 'F1-2.5': 0.5319693094629157,\n", + " 'Recall-2.5': 0.8739495798319328,\n", + " 'Precision-2.5': 0.38235294117647056,\n", + " 'F1-3.5': 0.1164021164021164,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.06321839080459771,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8876000718308812},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 82, '2': 72, '3': 16, '4': 14, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 12, '2': 27, '3': 27, '4': 34, '5': 0},\n", @@ -7854,12 +13494,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.13617459660615897,\n", " 'Micro-F1': 0.11937377690802348,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.06763285024154589,\n", - " 'F1-2': 0.06862745098039216,\n", - " 'F1-3': 0.27007299270072993,\n", - " 'F1-4': 0.125,\n", - " 'F1-5': 0.2857142857142857,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.06763285024154589,\n", + " 'F1-2_vs_rest': 0.06862745098039216,\n", + " 'F1-3_vs_rest': 0.27007299270072993,\n", + " 'F1-4_vs_rest': 0.125,\n", + " 'F1-5_vs_rest': 0.2857142857142857,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7058823529411765,\n", + " 'Recall-1.5': 0.9866666666666667,\n", + " 'Precision-1.5': 0.5495049504950495,\n", + " 'F1-2.5': 0.5411764705882353,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.3758169934640523,\n", + " 'F1-3.5': 0.1456953642384106,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08088235294117647,\n", + " 'F1-4.5': 0.2857142857142857,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.2,\n", " 'NDCG@all': 0.9095851845950752},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 97, '2': 57, '3': 25, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 31, '3': 41, '4': 21, '5': 0},\n", @@ -7886,12 +13541,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2844742855149427,\n", " 'Micro-F1': 0.37377690802348335,\n", - " 'F1-0': 0.37554585152838427,\n", - " 'F1-1': 0.2753623188405797,\n", - " 'F1-2': 0.42379182156133827,\n", - " 'F1-3': 0.49261083743842365,\n", - " 'F1-4': 0.13953488372093023,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.37554585152838427,\n", + " 'F1-1_vs_rest': 0.2753623188405797,\n", + " 'F1-2_vs_rest': 0.42379182156133827,\n", + " 'F1-3_vs_rest': 0.49261083743842365,\n", + " 'F1-4_vs_rest': 0.13953488372093023,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.819672131147541,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6944444444444444,\n", + " 'F1-1.5': 0.7736943907156673,\n", + " 'Recall-1.5': 0.8888888888888888,\n", + " 'Precision-1.5': 0.684931506849315,\n", + " 'F1-2.5': 0.5806451612903226,\n", + " 'Recall-2.5': 0.6050420168067226,\n", + " 'Precision-2.5': 0.5581395348837209,\n", + " 'F1-3.5': 0.13333333333333333,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8911118391489357},\n", " 'CM': {'0': {'-1': 0, '0': 43, '1': 113, '2': 23, '3': 2, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 38, '2': 43, '3': 13, '4': 6, '5': 0},\n", @@ -7918,12 +13588,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1371898181552723,\n", " 'Micro-F1': 0.1760299625468165,\n", - " 'F1-0': 0.14893617021276595,\n", - " 'F1-1': 0.1282051282051282,\n", - " 'F1-2': 0.2,\n", - " 'F1-3': 0.2814814814814815,\n", - " 'F1-4': 0.06451612903225806,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.14893617021276595,\n", + " 'F1-1_vs_rest': 0.1282051282051282,\n", + " 'F1-2_vs_rest': 0.2,\n", + " 'F1-3_vs_rest': 0.2814814814814815,\n", + " 'F1-4_vs_rest': 0.06451612903225806,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8181818181818182,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6923076923076923,\n", + " 'F1-1.5': 0.6795580110497238,\n", + " 'Recall-1.5': 0.984,\n", + " 'Precision-1.5': 0.5189873417721519,\n", + " 'F1-2.5': 0.5086206896551724,\n", + " 'Recall-2.5': 0.8805970149253731,\n", + " 'Precision-2.5': 0.3575757575757576,\n", + " 'F1-3.5': 0.08247422680412371,\n", + " 'Recall-3.5': 0.5,\n", + " 'Precision-3.5': 0.0449438202247191,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8822217327335828},\n", " 'CM': {'0': {'-1': 99, '0': 7, '1': 16, '2': 35, '3': 16, '4': 13, '5': 0},\n", " '1': {'-1': 45, '0': 0, '1': 5, '2': 17, '3': 21, '4': 12, '5': 0},\n", @@ -7931,6 +13616,53 @@ " '3': {'-1': 45, '0': 0, '1': 1, '2': 5, '3': 19, '4': 33, '5': 1},\n", " '4': {'-1': 6, '0': 0, '1': 0, '2': 2, '3': 1, '4': 3, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.16688217084830123,\n", + " 'Cohen': 0.20078403631326092,\n", + " 'Spearman': 0.6721136282022295,\n", + " 'Kendall': 0.5768533675004286,\n", + " 'Krippendorff': 0.6016761061967593,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7686274509803922,\n", + " 'TA-4.0': 0.9686274509803922,\n", + " 'Acc': 0.37450980392156863,\n", + " 'MAE': 0.749019607843137,\n", + " 'MSE': 0.9812636165577341,\n", + " 'CA-0': 0.26881720430107525,\n", + " 'CA-1': 0.43,\n", + " 'CA-2': 0.5849056603773585,\n", + " 'CA-3': 0.34951456310679613,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2553913776882253,\n", + " 'Micro-F1': 0.37450980392156863,\n", + " 'F1-0_vs_rest': 0.4219409282700422,\n", + " 'F1-1_vs_rest': 0.30714285714285716,\n", + " 'F1-2_vs_rest': 0.4119601328903654,\n", + " 'F1-3_vs_rest': 0.391304347826087,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8250319284802043,\n", + " 'Recall-0.5': 0.9969135802469136,\n", + " 'Precision-0.5': 0.7037037037037037,\n", + " 'F1-1.5': 0.7833001988071571,\n", + " 'Recall-1.5': 0.8794642857142857,\n", + " 'Precision-1.5': 0.7060931899641577,\n", + " 'F1-2.5': 0.44554455445544555,\n", + " 'Recall-2.5': 0.3813559322033898,\n", + " 'Precision-2.5': 0.5357142857142857,\n", + " 'F1-3.5': 0.1111111111111111,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.3333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9102540413838333},\n", + " 'CM': {'0': {'-1': 0, '0': 50, '1': 110, '2': 21, '3': 5, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 43, '2': 43, '3': 13, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 23, '2': 62, '3': 20, '4': 1, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 4, '2': 62, '3': 36, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 6, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1392825964538014,\n", " 'Cohen': 0.15901508579280466,\n", " 'Spearman': 0.6687193415411001,\n", @@ -7950,12 +13682,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2850082065793031,\n", " 'Micro-F1': 0.3173913043478261,\n", - " 'F1-0': 0.5,\n", - " 'F1-1': 0.19101123595505617,\n", - " 'F1-2': 0.35555555555555557,\n", - " 'F1-3': 0.28735632183908044,\n", - " 'F1-4': 0.12612612612612611,\n", - " 'F1-5': 0.25,\n", + " 'F1-0_vs_rest': 0.5,\n", + " 'F1-1_vs_rest': 0.19101123595505617,\n", + " 'F1-2_vs_rest': 0.35555555555555557,\n", + " 'F1-3_vs_rest': 0.28735632183908044,\n", + " 'F1-4_vs_rest': 0.12612612612612611,\n", + " 'F1-5_vs_rest': 0.25,\n", + " 'F1-0.5': 0.8390804597701149,\n", + " 'Recall-0.5': 0.9511400651465798,\n", + " 'Precision-0.5': 0.7506426735218509,\n", + " 'F1-1.5': 0.7799227799227799,\n", + " 'Recall-1.5': 0.9223744292237442,\n", + " 'Precision-1.5': 0.6755852842809364,\n", + " 'F1-2.5': 0.6416382252559727,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.5402298850574713,\n", + " 'F1-3.5': 0.15126050420168066,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.08653846153846154,\n", + " 'F1-4.5': 0.25,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.16666666666666666,\n", " 'NDCG@all': 0.9122718348963341},\n", " 'CM': {'0': {'-1': 33, '0': 56, '1': 60, '2': 26, '3': 5, '4': 6, '5': 0},\n", " '1': {'-1': 12, '0': 11, '1': 17, '2': 34, '3': 12, '4': 13, '5': 1},\n", @@ -7982,12 +13729,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12372388299950626,\n", " 'Micro-F1': 0.15459882583170254,\n", - " 'F1-0': 0.09183673469387756,\n", - " 'F1-1': 0.08743169398907104,\n", - " 'F1-2': 0.16279069767441862,\n", - " 'F1-3': 0.26956521739130435,\n", - " 'F1-4': 0.13071895424836602,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09183673469387756,\n", + " 'F1-1_vs_rest': 0.08743169398907104,\n", + " 'F1-2_vs_rest': 0.16279069767441862,\n", + " 'F1-3_vs_rest': 0.26956521739130435,\n", + " 'F1-4_vs_rest': 0.13071895424836602,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.784503631961259,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6467065868263473,\n", + " 'F1-1.5': 0.6780715396578538,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5215311004784688,\n", + " 'F1-2.5': 0.5506493506493506,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.39849624060150374,\n", + " 'F1-3.5': 0.15483870967741936,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.08571428571428572,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8963504900865995},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 69, '2': 77, '3': 21, '4': 10, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 43, '3': 28, '4': 21, '5': 0},\n", @@ -7995,11 +13757,58 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 11, '3': 31, '4': 60, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'ro': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08649983396625897,\n", - " 'Cohen': 0.12671672641694087,\n", - " 'Spearman': 0.5916588804446729,\n", - " 'Kendall': 0.5006393262937947,\n", - " 'Krippendorff': 0.4941370166641462,\n", + " 'ro': {'phi-4': {'metrics': {'Fleiss': 0.17982575986962762,\n", + " 'Cohen': 0.19075655561708782,\n", + " 'Spearman': 0.6406325280640629,\n", + " 'Kendall': 0.530183011869488,\n", + " 'Krippendorff': 0.5514652151776293,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7338551859099804,\n", + " 'TA-4.0': 0.8590998043052838,\n", + " 'Acc': 0.36203522504892366,\n", + " 'MAE': 0.9279191128506198,\n", + " 'MSE': 1.666394868449663,\n", + " 'CA-0': 0.4731182795698925,\n", + " 'CA-1': 0.16,\n", + " 'CA-2': 0.22641509433962265,\n", + " 'CA-3': 0.4807692307692308,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.31419056523974637,\n", + " 'Micro-F1': 0.36203522504892366,\n", + " 'F1-0_vs_rest': 0.5966101694915255,\n", + " 'F1-1_vs_rest': 0.17486338797814208,\n", + " 'F1-2_vs_rest': 0.23076923076923078,\n", + " 'F1-3_vs_rest': 0.4032258064516129,\n", + " 'F1-4_vs_rest': 0.14634146341463414,\n", + " 'F1-5_vs_rest': 0.3333333333333333,\n", + " 'F1-0.5': 0.8363136176066025,\n", + " 'Recall-0.5': 0.9353846153846154,\n", + " 'Precision-0.5': 0.7562189054726368,\n", + " 'F1-1.5': 0.7647058823529411,\n", + " 'Recall-1.5': 0.9244444444444444,\n", + " 'Precision-1.5': 0.6520376175548589,\n", + " 'F1-2.5': 0.5595238095238095,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.43317972350230416,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.1095890410958904,\n", + " 'F1-4.5': 0.3333333333333333,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.25,\n", + " 'NDCG@all': 0.8922818031812116},\n", + " 'CM': {'0': {'-1': 0, '0': 88, '1': 53, '2': 27, '3': 11, '4': 6, '5': 1},\n", + " '1': {'-1': 0, '0': 18, '1': 16, '2': 29, '3': 26, '4': 10, '5': 1},\n", + " '2': {'-1': 0, '0': 3, '1': 11, '2': 24, '3': 51, '4': 17, '5': 0},\n", + " '3': {'-1': 0, '0': 0, '1': 3, '2': 21, '3': 50, '4': 29, '5': 1},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 6, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08649983396625897,\n", + " 'Cohen': 0.12671672641694087,\n", + " 'Spearman': 0.5916588804446729,\n", + " 'Kendall': 0.5006393262937947,\n", + " 'Krippendorff': 0.4941370166641462,\n", " 'Invalid': 0,\n", " 'TA-2.0': 0.7084148727984344,\n", " 'TA-4.0': 0.923679060665362,\n", @@ -8014,12 +13823,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2294857520055369,\n", " 'Micro-F1': 0.299412915851272,\n", - " 'F1-0': 0.2169811320754717,\n", - " 'F1-1': 0.24,\n", - " 'F1-2': 0.3076923076923077,\n", - " 'F1-3': 0.4845814977973568,\n", - " 'F1-4': 0.1276595744680851,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.2169811320754717,\n", + " 'F1-1_vs_rest': 0.24,\n", + " 'F1-2_vs_rest': 0.3076923076923077,\n", + " 'F1-3_vs_rest': 0.4845814977973568,\n", + " 'F1-4_vs_rest': 0.1276595744680851,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7950617283950617,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.6639175257731958,\n", + " 'F1-1.5': 0.7294117647058823,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6526315789473685,\n", + " 'F1-2.5': 0.5579710144927537,\n", + " 'Recall-2.5': 0.6470588235294118,\n", + " 'Precision-2.5': 0.49044585987261147,\n", + " 'F1-3.5': 0.20408163265306123,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.14705882352941177,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8877087338901798},\n", " 'CM': {'0': {'-1': 0, '0': 23, '1': 125, '2': 29, '3': 5, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 36, '2': 37, '3': 16, '4': 8, '5': 0},\n", @@ -8046,12 +13870,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.2980824218780301,\n", " 'Micro-F1': 0.37573385518590996,\n", - " 'F1-0': 0.6312056737588653,\n", - " 'F1-1': 0.35135135135135137,\n", - " 'F1-2': 0.39215686274509803,\n", - " 'F1-3': 0.189873417721519,\n", - " 'F1-4': 0.11864406779661017,\n", - " 'F1-5': 0.10526315789473684,\n", + " 'F1-0_vs_rest': 0.6312056737588653,\n", + " 'F1-1_vs_rest': 0.35135135135135137,\n", + " 'F1-2_vs_rest': 0.39215686274509803,\n", + " 'F1-3_vs_rest': 0.189873417721519,\n", + " 'F1-4_vs_rest': 0.11864406779661017,\n", + " 'F1-5_vs_rest': 0.10526315789473684,\n", + " 'F1-0.5': 0.8594594594594595,\n", + " 'Recall-0.5': 0.9784615384615385,\n", + " 'Precision-0.5': 0.7662650602409639,\n", + " 'F1-1.5': 0.7992277992277992,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.7064846416382252,\n", + " 'F1-2.5': 0.6178343949044586,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.49743589743589745,\n", + " 'F1-3.5': 0.14102564102564102,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07801418439716312,\n", + " 'F1-4.5': 0.10526315789473684,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.05555555555555555,\n", " 'NDCG@all': 0.8942754866925002},\n", " 'CM': {'0': {'-1': 0, '0': 89, '1': 66, '2': 15, '3': 7, '4': 5, '5': 4},\n", " '1': {'-1': 0, '0': 6, '1': 39, '2': 23, '3': 12, '4': 12, '5': 8},\n", @@ -8078,12 +13917,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2332471696752915,\n", " 'Micro-F1': 0.29469548133595286,\n", - " 'F1-0': 0.1306532663316583,\n", - " 'F1-1': 0.23423423423423423,\n", - " 'F1-2': 0.3770491803278688,\n", - " 'F1-3': 0.47572815533980584,\n", - " 'F1-4': 0.18181818181818182,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.1306532663316583,\n", + " 'F1-1_vs_rest': 0.23423423423423423,\n", + " 'F1-2_vs_rest': 0.3770491803278688,\n", + " 'F1-3_vs_rest': 0.47572815533980584,\n", + " 'F1-4_vs_rest': 0.18181818181818182,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7887667887667887,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6512096774193549,\n", + " 'F1-1.5': 0.7530864197530864,\n", + " 'Recall-1.5': 0.820627802690583,\n", + " 'Precision-1.5': 0.6958174904942965,\n", + " 'F1-2.5': 0.5454545454545454,\n", + " 'Recall-2.5': 0.5641025641025641,\n", + " 'Precision-2.5': 0.528,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.19047619047619047,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9032298521738927},\n", " 'CM': {'0': {'-1': 0, '0': 13, '1': 154, '2': 12, '3': 6, '4': 1, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 39, '2': 41, '3': 18, '4': 2, '5': 0},\n", @@ -8110,12 +13964,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23909870115413612,\n", " 'Micro-F1': 0.3131115459882583,\n", - " 'F1-0': 0.5283018867924528,\n", - " 'F1-1': 0.2727272727272727,\n", - " 'F1-2': 0.18181818181818182,\n", - " 'F1-3': 0.29245283018867924,\n", - " 'F1-4': 0.1592920353982301,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5283018867924528,\n", + " 'F1-1_vs_rest': 0.2727272727272727,\n", + " 'F1-2_vs_rest': 0.18181818181818182,\n", + " 'F1-3_vs_rest': 0.29245283018867924,\n", + " 'F1-4_vs_rest': 0.1592920353982301,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8348745046235139,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7314814814814815,\n", + " 'F1-1.5': 0.7378640776699029,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.6551724137931034,\n", + " 'F1-2.5': 0.5792682926829268,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.45454545454545453,\n", + " 'F1-3.5': 0.1896551724137931,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.10891089108910891,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8959112072350262},\n", " 'CM': {'0': {'-1': 0, '0': 70, '1': 78, '2': 24, '3': 9, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 33, '2': 27, '3': 20, '4': 14, '5': 1},\n", @@ -8142,12 +14011,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08993055510740922,\n", " 'Micro-F1': 0.1095890410958904,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07142857142857142,\n", - " 'F1-2': 0.1452991452991453,\n", - " 'F1-3': 0.19895287958115182,\n", - " 'F1-4': 0.11320754716981132,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07142857142857142,\n", + " 'F1-2_vs_rest': 0.1452991452991453,\n", + " 'F1-3_vs_rest': 0.19895287958115182,\n", + " 'F1-4_vs_rest': 0.11320754716981132,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6823161189358372,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5265700483091788,\n", + " 'F1-2.5': 0.5382716049382716,\n", + " 'Recall-2.5': 0.9159663865546218,\n", + " 'Precision-2.5': 0.3811188811188811,\n", + " 'F1-3.5': 0.1308411214953271,\n", + " 'Recall-3.5': 0.9333333333333333,\n", + " 'Precision-3.5': 0.07035175879396985,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.886270281640181},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 82, '2': 71, '3': 13, '4': 19, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 32, '3': 25, '4': 36, '5': 0},\n", @@ -8174,12 +14058,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08679651859594735,\n", " 'Micro-F1': 0.11591355599214145,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.041025641025641026,\n", - " 'F1-2': 0.0966183574879227,\n", - " 'F1-3': 0.2517482517482518,\n", - " 'F1-4': 0.13138686131386862,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.041025641025641026,\n", + " 'F1-2_vs_rest': 0.0966183574879227,\n", + " 'F1-3_vs_rest': 0.2517482517482518,\n", + " 'F1-4_vs_rest': 0.13138686131386862,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7764423076923077,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6345776031434185,\n", + " 'F1-1.5': 0.6970172684458399,\n", + " 'Recall-1.5': 0.9866666666666667,\n", + " 'Precision-1.5': 0.5388349514563107,\n", + " 'F1-2.5': 0.5395348837209303,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.3729903536977492,\n", + " 'F1-3.5': 0.1527777777777778,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08527131782945736,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9043028559545201},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 63, '3': 28, '4': 5, '5': 0},\n", " '1': {'-1': 2, '0': 0, '1': 4, '2': 26, '3': 51, '4': 16, '5': 1},\n", @@ -8206,12 +14105,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2889933199383591,\n", " 'Micro-F1': 0.3913894324853229,\n", - " 'F1-0': 0.39655172413793105,\n", - " 'F1-1': 0.26717557251908397,\n", - " 'F1-2': 0.45588235294117646,\n", - " 'F1-3': 0.5213270142180095,\n", - " 'F1-4': 0.09302325581395349,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.39655172413793105,\n", + " 'F1-1_vs_rest': 0.26717557251908397,\n", + " 'F1-2_vs_rest': 0.45588235294117646,\n", + " 'F1-3_vs_rest': 0.5213270142180095,\n", + " 'F1-4_vs_rest': 0.09302325581395349,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8227848101265823,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6989247311827957,\n", + " 'F1-1.5': 0.7765151515151515,\n", + " 'Recall-1.5': 0.9111111111111111,\n", + " 'Precision-1.5': 0.6765676567656765,\n", + " 'F1-2.5': 0.6171875,\n", + " 'Recall-2.5': 0.6638655462184874,\n", + " 'Precision-2.5': 0.5766423357664233,\n", + " 'F1-3.5': 0.13333333333333333,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8971983011165344},\n", " 'CM': {'0': {'-1': 0, '0': 46, '1': 107, '2': 25, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 35, '2': 42, '3': 19, '4': 4, '5': 0},\n", @@ -8238,12 +14152,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12925100636965042,\n", " 'Micro-F1': 0.15648854961832062,\n", - " 'F1-0': 0.22033898305084745,\n", - " 'F1-1': 0.15384615384615385,\n", - " 'F1-2': 0.15384615384615385,\n", - " 'F1-3': 0.20202020202020202,\n", - " 'F1-4': 0.045454545454545456,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.22033898305084745,\n", + " 'F1-1_vs_rest': 0.15384615384615385,\n", + " 'F1-2_vs_rest': 0.15384615384615385,\n", + " 'F1-3_vs_rest': 0.20202020202020202,\n", + " 'F1-4_vs_rest': 0.045454545454545456,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7733990147783252,\n", + " 'Recall-0.5': 0.98125,\n", + " 'Precision-0.5': 0.6382113821138211,\n", + " 'F1-1.5': 0.6603174603174603,\n", + " 'Recall-1.5': 0.9629629629629629,\n", + " 'Precision-1.5': 0.5024154589371981,\n", + " 'F1-2.5': 0.494949494949495,\n", + " 'Recall-2.5': 0.8305084745762712,\n", + " 'Precision-2.5': 0.35251798561151076,\n", + " 'F1-3.5': 0.08080808080808081,\n", + " 'Recall-3.5': 0.5714285714285714,\n", + " 'Precision-3.5': 0.043478260869565216,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8580436634813599},\n", " 'CM': {'0': {'-1': 84, '0': 13, '1': 30, '2': 38, '3': 8, '4': 12, '5': 1},\n", " '1': {'-1': 48, '0': 1, '1': 7, '2': 12, '3': 13, '4': 18, '5': 1},\n", @@ -8251,6 +14180,53 @@ " '3': {'-1': 52, '0': 0, '1': 1, '2': 8, '3': 10, '4': 29, '5': 4},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 1, '3': 1, '4': 2, '5': 1},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.11104528207598441,\n", + " 'Cohen': 0.15127860821319483,\n", + " 'Spearman': 0.6726194436499735,\n", + " 'Kendall': 0.5748306464919687,\n", + " 'Krippendorff': 0.5818652066897299,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.7544204322200393,\n", + " 'TA-4.0': 0.962671905697446,\n", + " 'Acc': 0.33398821218074654,\n", + " 'MAE': 0.7901113294040598,\n", + " 'MSE': 1.0288692425234662,\n", + " 'CA-0': 0.22580645161290322,\n", + " 'CA-1': 0.34,\n", + " 'CA-2': 0.5943396226415094,\n", + " 'CA-3': 0.30392156862745096,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2257654002110132,\n", + " 'Micro-F1': 0.33398821218074654,\n", + " 'F1-0_vs_rest': 0.3652173913043478,\n", + " 'F1-1_vs_rest': 0.2537313432835821,\n", + " 'F1-2_vs_rest': 0.3949843260188088,\n", + " 'F1-3_vs_rest': 0.34065934065934067,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8147208121827412,\n", + " 'Recall-0.5': 0.9938080495356038,\n", + " 'Precision-0.5': 0.6903225806451613,\n", + " 'F1-1.5': 0.7807692307692308,\n", + " 'Recall-1.5': 0.9103139013452914,\n", + " 'Precision-1.5': 0.6835016835016835,\n", + " 'F1-2.5': 0.417910447761194,\n", + " 'Recall-2.5': 0.358974358974359,\n", + " 'Precision-2.5': 0.5,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8991635957819315},\n", + " 'CM': {'0': {'-1': 0, '0': 42, '1': 115, '2': 25, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 34, '2': 52, '3': 13, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 17, '2': 63, '3': 23, '4': 2, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 2, '2': 67, '3': 31, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 6, '3': 7, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.12969699074275035,\n", " 'Cohen': 0.15062612615156956,\n", " 'Spearman': 0.6856549344122829,\n", @@ -8270,12 +14246,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23883203830170552,\n", " 'Micro-F1': 0.31049250535331907,\n", - " 'F1-0': 0.4890829694323144,\n", - " 'F1-1': 0.17073170731707318,\n", - " 'F1-2': 0.3305084745762712,\n", - " 'F1-3': 0.3118279569892473,\n", - " 'F1-4': 0.1308411214953271,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4890829694323144,\n", + " 'F1-1_vs_rest': 0.17073170731707318,\n", + " 'F1-2_vs_rest': 0.3305084745762712,\n", + " 'F1-3_vs_rest': 0.3118279569892473,\n", + " 'F1-4_vs_rest': 0.1308411214953271,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8340425531914893,\n", + " 'Recall-0.5': 0.9576547231270358,\n", + " 'Precision-0.5': 0.7386934673366834,\n", + " 'F1-1.5': 0.7726432532347505,\n", + " 'Recall-1.5': 0.9587155963302753,\n", + " 'Precision-1.5': 0.6470588235294118,\n", + " 'F1-2.5': 0.6360655737704918,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.521505376344086,\n", + " 'F1-3.5': 0.16806722689075632,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.09615384615384616,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9102496793395825},\n", " 'CM': {'0': {'-1': 26, '0': 56, '1': 56, '2': 37, '3': 6, '4': 4, '5': 1},\n", " '1': {'-1': 11, '0': 9, '1': 14, '2': 39, '3': 16, '4': 10, '5': 1},\n", @@ -8302,12 +14293,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.13539964618933534,\n", " 'Micro-F1': 0.16829745596868884,\n", - " 'F1-0': 0.1116751269035533,\n", - " 'F1-1': 0.1256544502617801,\n", - " 'F1-2': 0.1693548387096774,\n", - " 'F1-3': 0.26778242677824265,\n", - " 'F1-4': 0.13793103448275862,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.1116751269035533,\n", + " 'F1-1_vs_rest': 0.1256544502617801,\n", + " 'F1-2_vs_rest': 0.1693548387096774,\n", + " 'F1-3_vs_rest': 0.26778242677824265,\n", + " 'F1-4_vs_rest': 0.13793103448275862,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7878787878787878,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.65,\n", + " 'F1-1.5': 0.6908517350157729,\n", + " 'Recall-1.5': 0.9733333333333334,\n", + " 'Precision-1.5': 0.5354523227383863,\n", + " 'F1-2.5': 0.5440414507772021,\n", + " 'Recall-2.5': 0.8823529411764706,\n", + " 'Precision-2.5': 0.39325842696629215,\n", + " 'F1-3.5': 0.16326530612244897,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.09090909090909091,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8980414748022626},\n", " 'CM': {'0': {'-1': 0, '0': 11, '1': 73, '2': 68, '3': 25, '4': 9, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 12, '2': 39, '3': 31, '4': 18, '5': 0},\n", @@ -8315,7 +14321,54 @@ " '3': {'-1': 0, '0': 0, '1': 0, '2': 14, '3': 32, '4': 58, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'lt': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09995821835040046,\n", + " 'lt': {'phi-4': {'metrics': {'Fleiss': 0.20412219178755234,\n", + " 'Cohen': 0.21567706542843446,\n", + " 'Spearman': 0.6338286183564478,\n", + " 'Kendall': 0.529572911832488,\n", + " 'Krippendorff': 0.5546154024926158,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7299412915851272,\n", + " 'TA-4.0': 0.8825831702544031,\n", + " 'Acc': 0.3796477495107632,\n", + " 'MAE': 0.8910632746249184,\n", + " 'MSE': 1.5569689062839747,\n", + " 'CA-0': 0.43010752688172044,\n", + " 'CA-1': 0.33,\n", + " 'CA-2': 0.29245283018867924,\n", + " 'CA-3': 0.4230769230769231,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.28375910835474744,\n", + " 'Micro-F1': 0.3796477495107632,\n", + " 'F1-0_vs_rest': 0.5714285714285714,\n", + " 'F1-1_vs_rest': 0.3113207547169811,\n", + " 'F1-2_vs_rest': 0.29107981220657275,\n", + " 'F1-3_vs_rest': 0.3728813559322034,\n", + " 'F1-4_vs_rest': 0.15584415584415584,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8382749326145552,\n", + " 'Recall-0.5': 0.9569230769230769,\n", + " 'Precision-0.5': 0.7458033573141487,\n", + " 'F1-1.5': 0.7547169811320755,\n", + " 'Recall-1.5': 0.8888888888888888,\n", + " 'Precision-1.5': 0.6557377049180327,\n", + " 'F1-2.5': 0.5741324921135647,\n", + " 'Recall-2.5': 0.7647058823529411,\n", + " 'Precision-2.5': 0.4595959595959596,\n", + " 'F1-3.5': 0.19753086419753085,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.12121212121212122,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8960655287569413},\n", + " 'CM': {'0': {'-1': 0, '0': 80, '1': 59, '2': 29, '3': 14, '4': 4, '5': 0},\n", + " '1': {'-1': 0, '0': 9, '1': 33, '2': 25, '3': 24, '4': 8, '5': 1},\n", + " '2': {'-1': 0, '0': 4, '1': 15, '2': 31, '3': 44, '4': 11, '5': 1},\n", + " '3': {'-1': 0, '0': 1, '1': 5, '2': 21, '3': 44, '4': 33, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 6, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09995821835040046,\n", " 'Cohen': 0.1342193042833696,\n", " 'Spearman': 0.5811897205351297,\n", " 'Kendall': 0.4911509980019675,\n", @@ -8334,12 +14387,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2337996313088223,\n", " 'Micro-F1': 0.3111545988258317,\n", - " 'F1-0': 0.30493273542600896,\n", - " 'F1-1': 0.2517482517482518,\n", - " 'F1-2': 0.33070866141732286,\n", - " 'F1-3': 0.41284403669724773,\n", - " 'F1-4': 0.10256410256410256,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.30493273542600896,\n", + " 'F1-1_vs_rest': 0.2517482517482518,\n", + " 'F1-2_vs_rest': 0.33070866141732286,\n", + " 'F1-3_vs_rest': 0.41284403669724773,\n", + " 'F1-4_vs_rest': 0.10256410256410256,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8060075093867334,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.679324894514768,\n", + " 'F1-1.5': 0.7251461988304093,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6458333333333334,\n", + " 'F1-2.5': 0.5328185328185329,\n", + " 'Recall-2.5': 0.5798319327731093,\n", + " 'Precision-2.5': 0.4928571428571429,\n", + " 'F1-3.5': 0.14634146341463414,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.11538461538461539,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8861634817796046},\n", " 'CM': {'0': {'-1': 0, '0': 34, '1': 111, '2': 32, '3': 6, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 36, '2': 39, '3': 15, '4': 7, '5': 0},\n", @@ -8366,12 +14434,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.30854440291966456,\n", " 'Micro-F1': 0.38551859099804303,\n", - " 'F1-0': 0.6505190311418685,\n", - " 'F1-1': 0.34309623430962344,\n", - " 'F1-2': 0.30927835051546393,\n", - " 'F1-3': 0.27710843373493976,\n", - " 'F1-4': 0.13333333333333333,\n", - " 'F1-5': 0.13793103448275862,\n", + " 'F1-0_vs_rest': 0.6505190311418685,\n", + " 'F1-1_vs_rest': 0.34309623430962344,\n", + " 'F1-2_vs_rest': 0.30927835051546393,\n", + " 'F1-3_vs_rest': 0.27710843373493976,\n", + " 'F1-4_vs_rest': 0.13333333333333333,\n", + " 'F1-5_vs_rest': 0.13793103448275862,\n", + " 'F1-0.5': 0.8622100954979536,\n", + " 'Recall-0.5': 0.9723076923076923,\n", + " 'Precision-0.5': 0.7745098039215687,\n", + " 'F1-1.5': 0.7854251012145749,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.7211895910780669,\n", + " 'F1-2.5': 0.62,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.5138121546961326,\n", + " 'F1-3.5': 0.14925373134328357,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08403361344537816,\n", + " 'F1-4.5': 0.13793103448275862,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.07407407407407407,\n", " 'NDCG@all': 0.8931184670401409},\n", " 'CM': {'0': {'-1': 0, '0': 94, '1': 68, '2': 13, '3': 4, '4': 4, '5': 3},\n", " '1': {'-1': 0, '0': 8, '1': 41, '2': 24, '3': 8, '4': 12, '5': 7},\n", @@ -8398,12 +14481,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.20558813172507864,\n", " 'Micro-F1': 0.2854330708661417,\n", - " 'F1-0': 0.05235602094240838,\n", - " 'F1-1': 0.24624624624624625,\n", - " 'F1-2': 0.37065637065637064,\n", - " 'F1-3': 0.49019607843137253,\n", - " 'F1-4': 0.07407407407407407,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.05235602094240838,\n", + " 'F1-1_vs_rest': 0.24624624624624625,\n", + " 'F1-2_vs_rest': 0.37065637065637064,\n", + " 'F1-3_vs_rest': 0.49019607843137253,\n", + " 'F1-4_vs_rest': 0.07407407407407407,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7806060606060606,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6401590457256461,\n", + " 'F1-1.5': 0.7601626016260162,\n", + " 'Recall-1.5': 0.8423423423423423,\n", + " 'Precision-1.5': 0.6925925925925925,\n", + " 'F1-2.5': 0.5579399141630901,\n", + " 'Recall-2.5': 0.5603448275862069,\n", + " 'Precision-2.5': 0.5555555555555556,\n", + " 'F1-3.5': 0.13793103448275862,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8981452608867684},\n", " 'CM': {'0': {'-1': 0, '0': 5, '1': 157, '2': 19, '3': 3, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 41, '2': 42, '3': 15, '4': 2, '5': 0},\n", @@ -8430,12 +14528,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2535674369770098,\n", " 'Micro-F1': 0.33463796477495106,\n", - " 'F1-0': 0.5173745173745173,\n", - " 'F1-1': 0.288135593220339,\n", - " 'F1-2': 0.24870466321243523,\n", - " 'F1-3': 0.35398230088495575,\n", - " 'F1-4': 0.11320754716981132,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5173745173745173,\n", + " 'F1-1_vs_rest': 0.288135593220339,\n", + " 'F1-2_vs_rest': 0.24870466321243523,\n", + " 'F1-3_vs_rest': 0.35398230088495575,\n", + " 'F1-4_vs_rest': 0.11320754716981132,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.836173001310616,\n", + " 'Recall-0.5': 0.9815384615384616,\n", + " 'Precision-0.5': 0.728310502283105,\n", + " 'F1-1.5': 0.7362428842504743,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6423841059602649,\n", + " 'F1-2.5': 0.592814371257485,\n", + " 'Recall-2.5': 0.8319327731092437,\n", + " 'Precision-2.5': 0.4604651162790698,\n", + " 'F1-3.5': 0.14814814814814814,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.08602150537634409,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9004884899333929},\n", " 'CM': {'0': {'-1': 0, '0': 67, '1': 74, '2': 28, '3': 11, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 34, '2': 29, '3': 20, '4': 14, '5': 0},\n", @@ -8462,12 +14575,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07408461852657429,\n", " 'Micro-F1': 0.09001956947162426,\n", - " 'F1-0': 0.0106951871657754,\n", - " 'F1-1': 0.07368421052631578,\n", - " 'F1-2': 0.11255411255411256,\n", - " 'F1-3': 0.15625,\n", - " 'F1-4': 0.091324200913242,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0106951871657754,\n", + " 'F1-1_vs_rest': 0.07368421052631578,\n", + " 'F1-2_vs_rest': 0.11255411255411256,\n", + " 'F1-3_vs_rest': 0.15625,\n", + " 'F1-4_vs_rest': 0.091324200913242,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7784431137724551,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6372549019607843,\n", + " 'F1-1.5': 0.6759689922480621,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5190476190476191,\n", + " 'F1-2.5': 0.5265700483091788,\n", + " 'Recall-2.5': 0.9159663865546218,\n", + " 'Precision-2.5': 0.3694915254237288,\n", + " 'F1-3.5': 0.10810810810810811,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.057971014492753624,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8788953871955031},\n", " 'CM': {'0': {'-1': 0, '0': 1, '1': 76, '2': 75, '3': 17, '4': 17, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 29, '3': 23, '4': 40, '5': 1},\n", @@ -8494,12 +14622,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08102245267493992,\n", " 'Micro-F1': 0.10567514677103718,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.05154639175257732,\n", - " 'F1-2': 0.10679611650485436,\n", - " 'F1-3': 0.2109090909090909,\n", - " 'F1-4': 0.11688311688311688,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.05154639175257732,\n", + " 'F1-2_vs_rest': 0.10679611650485436,\n", + " 'F1-3_vs_rest': 0.2109090909090909,\n", + " 'F1-4_vs_rest': 0.11688311688311688,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6978193146417445,\n", + " 'Recall-1.5': 0.9955555555555555,\n", + " 'Precision-1.5': 0.5371702637889688,\n", + " 'F1-2.5': 0.5275229357798165,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.3627760252365931,\n", + " 'F1-3.5': 0.13664596273291926,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07534246575342465,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9020748460084927},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 88, '2': 60, '3': 32, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 26, '3': 47, '4': 21, '5': 1},\n", @@ -8526,12 +14669,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2895170194141369,\n", " 'Micro-F1': 0.3816046966731898,\n", - " 'F1-0': 0.3684210526315789,\n", - " 'F1-1': 0.31226765799256506,\n", - " 'F1-2': 0.41007194244604317,\n", - " 'F1-3': 0.5,\n", - " 'F1-4': 0.14634146341463414,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3684210526315789,\n", + " 'F1-1_vs_rest': 0.31226765799256506,\n", + " 'F1-2_vs_rest': 0.41007194244604317,\n", + " 'F1-3_vs_rest': 0.5,\n", + " 'F1-4_vs_rest': 0.14634146341463414,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.818639798488665,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6929637526652452,\n", + " 'F1-1.5': 0.7847619047619048,\n", + " 'Recall-1.5': 0.9155555555555556,\n", + " 'Precision-1.5': 0.6866666666666666,\n", + " 'F1-2.5': 0.5991902834008097,\n", + " 'Recall-2.5': 0.6218487394957983,\n", + " 'Precision-2.5': 0.578125,\n", + " 'F1-3.5': 0.23255813953488372,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.17857142857142858,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9095731186603835},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 108, '2': 29, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 42, '2': 44, '3': 12, '4': 2, '5': 0},\n", @@ -8558,12 +14716,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.12908797916196046,\n", " 'Micro-F1': 0.14736842105263157,\n", - " 'F1-0': 0.11764705882352941,\n", - " 'F1-1': 0.06666666666666667,\n", - " 'F1-2': 0.14678899082568808,\n", - " 'F1-3': 0.2773722627737226,\n", - " 'F1-4': 0.0970873786407767,\n", - " 'F1-5': 0.06896551724137931,\n", + " 'F1-0_vs_rest': 0.11764705882352941,\n", + " 'F1-1_vs_rest': 0.06666666666666667,\n", + " 'F1-2_vs_rest': 0.14678899082568808,\n", + " 'F1-3_vs_rest': 0.2773722627737226,\n", + " 'F1-4_vs_rest': 0.0970873786407767,\n", + " 'F1-5_vs_rest': 0.06896551724137931,\n", + " 'F1-0.5': 0.8076923076923077,\n", + " 'Recall-0.5': 0.984375,\n", + " 'Precision-0.5': 0.6847826086956522,\n", + " 'F1-1.5': 0.6825396825396826,\n", + " 'Recall-1.5': 0.9699248120300752,\n", + " 'Precision-1.5': 0.5265306122448979,\n", + " 'F1-2.5': 0.5278810408921933,\n", + " 'Recall-2.5': 0.9466666666666667,\n", + " 'Precision-2.5': 0.36597938144329895,\n", + " 'F1-3.5': 0.12121212121212122,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.06557377049180328,\n", + " 'F1-4.5': 0.06896551724137931,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.03571428571428571,\n", " 'NDCG@all': 0.8748732893918199},\n", " 'CM': {'0': {'-1': 93, '0': 6, '1': 24, '2': 29, '3': 15, '4': 16, '5': 3},\n", " '1': {'-1': 41, '0': 3, '1': 3, '2': 11, '3': 18, '4': 21, '5': 3},\n", @@ -8571,6 +14744,53 @@ " '3': {'-1': 39, '0': 0, '1': 1, '2': 3, '3': 19, '4': 30, '5': 12},\n", " '4': {'-1': 4, '0': 0, '1': 0, '2': 0, '3': 2, '4': 5, '5': 2},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.07390489212060948,\n", + " 'Cohen': 0.12159081977521025,\n", + " 'Spearman': 0.681758944655894,\n", + " 'Kendall': 0.5854514568692673,\n", + " 'Krippendorff': 0.5631512640215335,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7362204724409449,\n", + " 'TA-4.0': 0.9625984251968503,\n", + " 'Acc': 0.30708661417322836,\n", + " 'MAE': 0.8241469816272965,\n", + " 'MSE': 1.0769903762029747,\n", + " 'CA-0': 0.1827956989247312,\n", + " 'CA-1': 0.24,\n", + " 'CA-2': 0.6037735849056604,\n", + " 'CA-3': 0.32673267326732675,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2224216701081664,\n", + " 'Micro-F1': 0.30708661417322836,\n", + " 'F1-0_vs_rest': 0.3090909090909091,\n", + " 'F1-1_vs_rest': 0.18972332015810275,\n", + " 'F1-2_vs_rest': 0.3798219584569733,\n", + " 'F1-3_vs_rest': 0.36065573770491804,\n", + " 'F1-4_vs_rest': 0.09523809523809523,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8090452261306532,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.679324894514768,\n", + " 'F1-1.5': 0.7734806629834254,\n", + " 'Recall-1.5': 0.9459459459459459,\n", + " 'Precision-1.5': 0.6542056074766355,\n", + " 'F1-2.5': 0.42718446601941745,\n", + " 'Recall-2.5': 0.3793103448275862,\n", + " 'Precision-2.5': 0.4888888888888889,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.25,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9103863493377554},\n", + " 'CM': {'0': {'-1': 0, '0': 34, '1': 117, '2': 31, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 0, '1': 24, '2': 65, '3': 10, '4': 1, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 11, '2': 64, '3': 30, '4': 1, '5': 0},\n", + " '3': {'-1': 3, '0': 0, '1': 1, '2': 63, '3': 33, '4': 4, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 8, '3': 4, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.11313747507970512,\n", " 'Cohen': 0.14348490442202,\n", " 'Spearman': 0.6567311460881612,\n", @@ -8590,12 +14810,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.26413894482324857,\n", " 'Micro-F1': 0.29568788501026694,\n", - " 'F1-0': 0.38181818181818183,\n", - " 'F1-1': 0.22105263157894736,\n", - " 'F1-2': 0.3492063492063492,\n", - " 'F1-3': 0.33519553072625696,\n", - " 'F1-4': 0.0975609756097561,\n", - " 'F1-5': 0.2,\n", + " 'F1-0_vs_rest': 0.38181818181818183,\n", + " 'F1-1_vs_rest': 0.22105263157894736,\n", + " 'F1-2_vs_rest': 0.3492063492063492,\n", + " 'F1-3_vs_rest': 0.33519553072625696,\n", + " 'F1-4_vs_rest': 0.0975609756097561,\n", + " 'F1-5_vs_rest': 0.2,\n", + " 'F1-0.5': 0.8196286472148541,\n", + " 'Recall-0.5': 0.9747634069400631,\n", + " 'Precision-0.5': 0.7070938215102975,\n", + " 'F1-1.5': 0.75177304964539,\n", + " 'Recall-1.5': 0.9592760180995475,\n", + " 'Precision-1.5': 0.6180758017492711,\n", + " 'F1-2.5': 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'F1-4_vs_rest': 0.12413793103448276,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7831325301204819,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6435643564356436,\n", + " 'F1-1.5': 0.6635802469135802,\n", + " 'Recall-1.5': 0.9555555555555556,\n", + " 'Precision-1.5': 0.508274231678487,\n", + " 'F1-2.5': 0.5614035087719298,\n", + " 'Recall-2.5': 0.9411764705882353,\n", + " 'Precision-2.5': 0.4,\n", + " 'F1-3.5': 0.14965986394557823,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9032752270312255},\n", " 'CM': {'0': {'-1': 0, '0': 6, '1': 65, '2': 84, '3': 24, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 37, '3': 38, '4': 18, '5': 0},\n", @@ -8635,1035 +14885,1844 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 5, '3': 34, '4': 63, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, 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0.3150684931506849,\n", - " 'F1-0': 0.2909090909090909,\n", - " 'F1-1': 0.2589928057553957,\n", - " 'F1-2': 0.31020408163265306,\n", - " 'F1-3': 0.4444444444444444,\n", - " 'F1-4': 0.13953488372093023,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.2909090909090909,\n", + " 'F1-1_vs_rest': 0.2589928057553957,\n", + " 'F1-2_vs_rest': 0.31020408163265306,\n", + " 'F1-3_vs_rest': 0.4444444444444444,\n", + " 'F1-4_vs_rest': 0.13953488372093023,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8054862842892768,\n", + " 'Recall-0.5': 0.9938461538461538,\n", + " 'Precision-0.5': 0.6771488469601677,\n", + " 'F1-1.5': 0.7480916030534351,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.6555183946488294,\n", + " 'F1-2.5': 0.5519713261648745,\n", + " 'Recall-2.5': 0.6470588235294118,\n", + " 'Precision-2.5': 0.48125,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.16666666666666666,\n", + " 'F1-4.5': 0.0,\n", + " 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0.8065173116089613,\n", + " 'Recall-1.5': 0.88,\n", + " 'Precision-1.5': 0.7443609022556391,\n", + " 'F1-2.5': 0.62,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.5138121546961326,\n", + " 'F1-3.5': 0.145985401459854,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08196721311475409,\n", + " 'F1-4.5': 0.06666666666666667,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.03571428571428571,\n", " 'NDCG@all': 0.8929777161857703},\n", " 'CM': {'0': {'-1': 0, '0': 97, '1': 64, '2': 12, '3': 4, '4': 5, '5': 4},\n", " '1': {'-1': 0, '0': 10, '1': 47, '2': 17, '3': 10, '4': 10, '5': 6},\n", @@ -9998,12 +17301,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2068102362258902,\n", " 'Micro-F1': 0.2901960784313726,\n", - " 'F1-0': 0.08247422680412371,\n", - " 'F1-1': 0.2682926829268293,\n", - " 'F1-2': 0.3745019920318725,\n", - " 'F1-3': 0.46153846153846156,\n", - " 'F1-4': 0.05405405405405406,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.08247422680412371,\n", + " 'F1-1_vs_rest': 0.2682926829268293,\n", + " 'F1-2_vs_rest': 0.3745019920318725,\n", + " 'F1-3_vs_rest': 0.46153846153846156,\n", + " 'F1-4_vs_rest': 0.05405405405405406,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.784503631961259,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6454183266932271,\n", + " 'F1-1.5': 0.7710843373493976,\n", + " 'Recall-1.5': 0.8571428571428571,\n", + " 'Precision-1.5': 0.7007299270072993,\n", + " 'F1-2.5': 0.5748987854251012,\n", + " 'Recall-2.5': 0.6016949152542372,\n", + " 'Precision-2.5': 0.5503875968992248,\n", + " 'F1-3.5': 0.10256410256410256,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.08333333333333333,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9032198555626133},\n", " 'CM': {'0': {'-1': 0, '0': 8, '1': 152, '2': 21, '3': 3, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 44, '2': 39, '3': 15, '4': 2, '5': 0},\n", @@ -10030,12 +17348,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23544358228152695,\n", " 'Micro-F1': 0.30919765166340507,\n", - " 'F1-0': 0.4980237154150198,\n", - " 'F1-1': 0.2975206611570248,\n", - " 'F1-2': 0.16666666666666666,\n", - " 'F1-3': 0.32432432432432434,\n", - " 'F1-4': 0.12612612612612611,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4980237154150198,\n", + " 'F1-1_vs_rest': 0.2975206611570248,\n", + " 'F1-2_vs_rest': 0.16666666666666666,\n", + " 'F1-3_vs_rest': 0.32432432432432434,\n", + " 'F1-4_vs_rest': 0.12612612612612611,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.834850455136541,\n", + " 'Recall-0.5': 0.9876923076923076,\n", + " 'Precision-0.5': 0.722972972972973,\n", + " 'F1-1.5': 0.7438330170777988,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.6490066225165563,\n", + " 'F1-2.5': 0.5791044776119403,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.44907407407407407,\n", + " 'F1-3.5': 0.1592920353982301,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.09183673469387756,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9031366419051541},\n", " 'CM': {'0': {'-1': 0, '0': 63, '1': 79, '2': 30, '3': 9, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 36, '2': 24, '3': 23, '4': 15, '5': 0},\n", @@ -10062,12 +17395,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07151759560630216,\n", " 'Micro-F1': 0.09001956947162426,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.031914893617021274,\n", - " 'F1-2': 0.16666666666666666,\n", - " 'F1-3': 0.11578947368421053,\n", - " 'F1-4': 0.09345794392523364,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.031914893617021274,\n", + " 'F1-2_vs_rest': 0.16666666666666666,\n", + " 'F1-3_vs_rest': 0.11578947368421053,\n", + " 'F1-4_vs_rest': 0.09345794392523364,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6718266253869969,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5154394299287411,\n", + " 'F1-2.5': 0.5369458128078818,\n", + " 'Recall-2.5': 0.9159663865546218,\n", + " 'Precision-2.5': 0.3797909407665505,\n", + " 'F1-3.5': 0.1111111111111111,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.05970149253731343,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8902926643450401},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 77, '2': 67, '3': 24, '4': 16, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 3, '2': 41, '3': 21, '4': 35, '5': 0},\n", @@ -10094,12 +17442,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.11561027488679225,\n", " 'Micro-F1': 0.10567514677103718,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.052083333333333336,\n", - " 'F1-2': 0.06666666666666667,\n", - " 'F1-3': 0.2318840579710145,\n", - " 'F1-4': 0.12080536912751678,\n", - " 'F1-5': 0.2222222222222222,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.052083333333333336,\n", + " 'F1-2_vs_rest': 0.06666666666666667,\n", + " 'F1-3_vs_rest': 0.2318840579710145,\n", + " 'F1-4_vs_rest': 0.12080536912751678,\n", + " 'F1-5_vs_rest': 0.2222222222222222,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6925465838509317,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5322195704057279,\n", + " 'F1-2.5': 0.5391705069124424,\n", + " 'Recall-2.5': 0.9831932773109243,\n", + " 'Precision-2.5': 0.37142857142857144,\n", + " 'F1-3.5': 0.13924050632911392,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07692307692307693,\n", + " 'F1-4.5': 0.2222222222222222,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.14285714285714285,\n", " 'NDCG@all': 0.9087804159225001},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 85, '2': 67, '3': 28, '4': 6, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 28, '3': 50, '4': 16, '5': 1},\n", @@ -10126,12 +17489,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2872552519258578,\n", " 'Micro-F1': 0.3776908023483366,\n", - " 'F1-0': 0.3739130434782609,\n", - " 'F1-1': 0.29411764705882354,\n", - " 'F1-2': 0.4,\n", - " 'F1-3': 0.5221674876847291,\n", - " 'F1-4': 0.13333333333333333,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3739130434782609,\n", + " 'F1-1_vs_rest': 0.29411764705882354,\n", + " 'F1-2_vs_rest': 0.4,\n", + " 'F1-3_vs_rest': 0.5221674876847291,\n", + " 'F1-4_vs_rest': 0.13333333333333333,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8181818181818182,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6937901498929336,\n", + " 'F1-1.5': 0.7730769230769231,\n", + " 'Recall-1.5': 0.8933333333333333,\n", + " 'Precision-1.5': 0.6813559322033899,\n", + " 'F1-2.5': 0.632,\n", + " 'Recall-2.5': 0.6638655462184874,\n", + " 'Precision-2.5': 0.6030534351145038,\n", + " 'F1-3.5': 0.1702127659574468,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.125,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9068743775636817},\n", " 'CM': {'0': {'-1': 0, '0': 43, '1': 109, '2': 27, '3': 4, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 40, '2': 47, '3': 9, '4': 4, '5': 0},\n", @@ -10158,12 +17536,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.06836739396659448,\n", " 'Micro-F1': 0.07553956834532374,\n", - " 'F1-0': 0.07920792079207921,\n", - " 'F1-1': 0.0975609756097561,\n", - " 'F1-2': 0.07407407407407407,\n", - " 'F1-3': 0.11320754716981132,\n", - " 'F1-4': 0.046153846153846156,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07920792079207921,\n", + " 'F1-1_vs_rest': 0.0975609756097561,\n", + " 'F1-2_vs_rest': 0.07407407407407407,\n", + " 'F1-3_vs_rest': 0.11320754716981132,\n", + " 'F1-4_vs_rest': 0.046153846153846156,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7956043956043956,\n", + " 'Recall-0.5': 0.9945054945054945,\n", + " 'Precision-0.5': 0.663003663003663,\n", + " 'F1-1.5': 0.6595174262734584,\n", + " 'Recall-1.5': 0.968503937007874,\n", + " 'Precision-1.5': 0.5,\n", + " 'F1-2.5': 0.4,\n", + " 'Recall-2.5': 0.8983050847457628,\n", + " 'Precision-2.5': 0.25728155339805825,\n", + " 'F1-3.5': 0.06289308176100629,\n", + " 'Recall-3.5': 0.7142857142857143,\n", + " 'Precision-3.5': 0.03289473684210526,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8786763352228465},\n", " 'CM': {'0': {'-1': 90, '0': 4, '1': 20, '2': 27, '3': 20, '4': 22, '5': 3},\n", " '1': {'-1': 45, '0': 0, '1': 4, '2': 7, '3': 11, '4': 29, '5': 4},\n", @@ -10171,6 +17564,53 @@ " '3': {'-1': 52, '0': 1, '1': 2, '2': 1, '3': 6, '4': 31, '5': 11},\n", " '4': {'-1': 6, '0': 0, '1': 1, '2': 1, '3': 0, '4': 3, '5': 2},\n", " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.06734694930913634,\n", + " 'Cohen': 0.11487800457513453,\n", + " 'Spearman': 0.681847078588012,\n", + " 'Kendall': 0.5850502855854306,\n", + " 'Krippendorff': 0.566868380957171,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.7347740667976425,\n", + " 'TA-4.0': 0.9587426326129665,\n", + " 'Acc': 0.3025540275049116,\n", + " 'MAE': 0.8238375900458412,\n", + " 'MSE': 1.0683256930801135,\n", + " 'CA-0': 0.1827956989247312,\n", + " 'CA-1': 0.25,\n", + " 'CA-2': 0.5849056603773585,\n", + " 'CA-3': 0.3235294117647059,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.20492918581153874,\n", + " 'Micro-F1': 0.3025540275049116,\n", + " 'F1-0_vs_rest': 0.3076923076923077,\n", + " 'F1-1_vs_rest': 0.19607843137254902,\n", + " 'F1-2_vs_rest': 0.36904761904761907,\n", + " 'F1-3_vs_rest': 0.3567567567567568,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8080301129234629,\n", + " 'Recall-0.5': 0.9969040247678018,\n", + " 'Precision-0.5': 0.679324894514768,\n", + " 'F1-1.5': 0.7712177121771218,\n", + " 'Recall-1.5': 0.9372197309417041,\n", + " 'Precision-1.5': 0.6551724137931034,\n", + " 'F1-2.5': 0.4368932038834951,\n", + " 'Recall-2.5': 0.38461538461538464,\n", + " 'Precision-2.5': 0.5056179775280899,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9029829628651325},\n", + " 'CM': {'0': {'-1': 0, '0': 34, '1': 116, '2': 33, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 25, '2': 63, '3': 10, '4': 1, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 14, '2': 62, '3': 29, '4': 1, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 0, '2': 65, '3': 33, '4': 4, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 6, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1445366568743685,\n", " 'Cohen': 0.16807710657246056,\n", " 'Spearman': 0.658244618960136,\n", @@ -10190,12 +17630,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2699101380499968,\n", " 'Micro-F1': 0.3225806451612903,\n", - " 'F1-0': 0.4549763033175355,\n", - " 'F1-1': 0.18072289156626506,\n", - " 'F1-2': 0.3764705882352941,\n", - " 'F1-3': 0.3463687150837989,\n", - " 'F1-4': 0.13592233009708737,\n", - " 'F1-5': 0.125,\n", + " 'F1-0_vs_rest': 0.4549763033175355,\n", + " 'F1-1_vs_rest': 0.18072289156626506,\n", + " 'F1-2_vs_rest': 0.3764705882352941,\n", + " 'F1-3_vs_rest': 0.3463687150837989,\n", + " 'F1-4_vs_rest': 0.13592233009708737,\n", + " 'F1-5_vs_rest': 0.125,\n", + " 'F1-0.5': 0.8400556328233658,\n", + " 'Recall-0.5': 0.9648562300319489,\n", + " 'Precision-0.5': 0.7438423645320197,\n", + " 'F1-1.5': 0.7486437613019892,\n", + " 'Recall-1.5': 0.9583333333333334,\n", + " 'Precision-1.5': 0.6142433234421365,\n", + " 'F1-2.5': 0.6308724832214765,\n", + " 'Recall-2.5': 0.8034188034188035,\n", + " 'Precision-2.5': 0.5193370165745856,\n", + " 'F1-3.5': 0.16806722689075632,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.09615384615384616,\n", + " 'F1-4.5': 0.125,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.07142857142857142,\n", " 'NDCG@all': 0.9124628443204231},\n", " 'CM': {'0': {'-1': 34, '0': 48, '1': 48, '2': 45, '3': 5, '4': 5, '5': 1},\n", " '1': {'-1': 3, '0': 8, '1': 15, '2': 42, '3': 21, '4': 10, '5': 1},\n", @@ -10222,12 +17677,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12017482556321735,\n", " 'Micro-F1': 0.1506849315068493,\n", - " 'F1-0': 0.052083333333333336,\n", - " 'F1-1': 0.09411764705882353,\n", - " 'F1-2': 0.11940298507462686,\n", - " 'F1-3': 0.30578512396694213,\n", - " 'F1-4': 0.14965986394557823,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.052083333333333336,\n", + " 'F1-1_vs_rest': 0.09411764705882353,\n", + " 'F1-2_vs_rest': 0.11940298507462686,\n", + " 'F1-3_vs_rest': 0.30578512396694213,\n", + " 'F1-4_vs_rest': 0.14965986394557823,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7807228915662651,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.6415841584158416,\n", + " 'F1-1.5': 0.6545454545454545,\n", + " 'Recall-1.5': 0.96,\n", + " 'Precision-1.5': 0.496551724137931,\n", + " 'F1-2.5': 0.5612244897959183,\n", + " 'Recall-2.5': 0.9243697478991597,\n", + " 'Precision-2.5': 0.40293040293040294,\n", + " 'F1-3.5': 0.17333333333333334,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.0962962962962963,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8936863687967181},\n", " 'CM': {'0': {'-1': 0, '0': 5, '1': 54, '2': 97, '3': 20, '4': 10, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 41, '3': 33, '4': 18, '5': 0},\n", @@ -10235,7 +17705,54 @@ " '3': {'-1': 0, '0': 0, '1': 1, '2': 8, '3': 37, '4': 58, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 11, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'lv': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12364814527782084,\n", + " 'lv': {'phi-4': {'metrics': {'Fleiss': 0.21530792968615847,\n", + " 'Cohen': 0.2279699959453979,\n", + " 'Spearman': 0.6605593148116243,\n", + " 'Kendall': 0.5506696575257908,\n", + " 'Krippendorff': 0.5705512305157412,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7514677103718199,\n", + " 'TA-4.0': 0.863013698630137,\n", + " 'Acc': 0.38747553816046965,\n", + " 'MAE': 0.8760600130463144,\n", + " 'MSE': 1.5129375951293758,\n", + " 'CA-0': 0.40860215053763443,\n", + " 'CA-1': 0.31,\n", + " 'CA-2': 0.33962264150943394,\n", + " 'CA-3': 0.4807692307692308,\n", + " 'CA-4': 0.3076923076923077,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3675390044021792,\n", + " 'Micro-F1': 0.38747553816046965,\n", + " 'F1-0_vs_rest': 0.5567765567765568,\n", + " 'F1-1_vs_rest': 0.2938388625592417,\n", + " 'F1-2_vs_rest': 0.32286995515695066,\n", + " 'F1-3_vs_rest': 0.4291845493562232,\n", + " 'F1-4_vs_rest': 0.10256410256410256,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8384512683578104,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7405660377358491,\n", + " 'F1-1.5': 0.7732342007434945,\n", + " 'Recall-1.5': 0.9244444444444444,\n", + " 'Precision-1.5': 0.6645367412140575,\n", + " 'F1-2.5': 0.5968253968253968,\n", + " 'Recall-2.5': 0.7899159663865546,\n", + " 'Precision-2.5': 0.47959183673469385,\n", + " 'F1-3.5': 0.12195121951219512,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.07462686567164178,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", + " 'NDCG@all': 0.905398204072337},\n", + " 'CM': {'0': {'-1': 0, '0': 76, '1': 66, '2': 30, '3': 9, '4': 5, '5': 0},\n", + " '1': {'-1': 0, '0': 8, '1': 31, '2': 30, '3': 22, '4': 9, '5': 0},\n", + " '2': {'-1': 0, '0': 3, '1': 10, '2': 36, '3': 41, '4': 15, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 4, '2': 18, '3': 50, '4': 32, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 3, '3': 6, '4': 4, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12364814527782084,\n", " 'Cohen': 0.15685086035626505,\n", " 'Spearman': 0.5817896446994788,\n", " 'Kendall': 0.4905216935658466,\n", @@ -10254,12 +17771,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2512455534039097,\n", " 'Micro-F1': 0.3287671232876712,\n", - " 'F1-0': 0.30357142857142855,\n", - " 'F1-1': 0.2837370242214533,\n", - " 'F1-2': 0.37751004016064255,\n", - " 'F1-3': 0.39631336405529954,\n", - " 'F1-4': 0.14634146341463414,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.30357142857142855,\n", + " 'F1-1_vs_rest': 0.2837370242214533,\n", + " 'F1-2_vs_rest': 0.37751004016064255,\n", + " 'F1-3_vs_rest': 0.39631336405529954,\n", + " 'F1-4_vs_rest': 0.14634146341463414,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8045112781954887,\n", + " 'Recall-0.5': 0.9876923076923076,\n", + " 'Precision-0.5': 0.678646934460888,\n", + " 'F1-1.5': 0.7387033398821218,\n", + " 'Recall-1.5': 0.8355555555555556,\n", + " 'Precision-1.5': 0.6619718309859155,\n", + " 'F1-2.5': 0.5230769230769231,\n", + " 'Recall-2.5': 0.5714285714285714,\n", + " 'Precision-2.5': 0.48226950354609927,\n", + " 'F1-3.5': 0.23255813953488372,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.17857142857142858,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8952944838100828},\n", " 'CM': {'0': {'-1': 0, '0': 34, '1': 113, '2': 29, '3': 8, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 41, '2': 30, '3': 21, '4': 6, '5': 0},\n", @@ -10286,12 +17818,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.33076771720727777,\n", " 'Micro-F1': 0.4070450097847358,\n", - " 'F1-0': 0.6385964912280702,\n", - " 'F1-1': 0.3786008230452675,\n", - " 'F1-2': 0.3756345177664975,\n", - " 'F1-3': 0.2926829268292683,\n", - " 'F1-4': 0.1509433962264151,\n", - " 'F1-5': 0.14814814814814814,\n", + " 'F1-0_vs_rest': 0.6385964912280702,\n", + " 'F1-1_vs_rest': 0.3786008230452675,\n", + " 'F1-2_vs_rest': 0.3756345177664975,\n", + " 'F1-3_vs_rest': 0.2926829268292683,\n", + " 'F1-4_vs_rest': 0.1509433962264151,\n", + " 'F1-5_vs_rest': 0.14814814814814814,\n", + " 'F1-0.5': 0.8602442333785617,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7694174757281553,\n", + " 'F1-1.5': 0.8016194331983806,\n", + " 'Recall-1.5': 0.88,\n", + " 'Precision-1.5': 0.7360594795539034,\n", + " 'F1-2.5': 0.6195286195286195,\n", + " 'Recall-2.5': 0.773109243697479,\n", + " 'Precision-2.5': 0.5168539325842697,\n", + " 'F1-3.5': 0.16541353383458646,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.09322033898305085,\n", + " 'F1-4.5': 0.14814814814814814,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.08,\n", " 'NDCG@all': 0.897780308311288},\n", " 'CM': {'0': {'-1': 0, '0': 91, '1': 71, '2': 10, '3': 6, '4': 5, '5': 3},\n", " '1': {'-1': 0, '0': 7, '1': 46, '2': 20, '3': 11, '4': 11, '5': 5},\n", @@ -10318,12 +17865,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.18448786095545322,\n", " 'Micro-F1': 0.2720156555772994,\n", - " 'F1-0': 0.042105263157894736,\n", - " 'F1-1': 0.22629969418960244,\n", - " 'F1-2': 0.36363636363636365,\n", - " 'F1-3': 0.4748858447488584,\n", - " 'F1-4': 0.0,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.042105263157894736,\n", + " 'F1-1_vs_rest': 0.22629969418960244,\n", + " 'F1-2_vs_rest': 0.36363636363636365,\n", + " 'F1-3_vs_rest': 0.4748858447488584,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78125,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6410256410256411,\n", + " 'F1-1.5': 0.7445544554455445,\n", + " 'Recall-1.5': 0.8355555555555556,\n", + " 'Precision-1.5': 0.6714285714285714,\n", + " 'F1-2.5': 0.5634920634920635,\n", + " 'Recall-2.5': 0.5966386554621849,\n", + " 'Precision-2.5': 0.5338345864661654,\n", + " 'F1-3.5': 0.06060606060606061,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.05555555555555555,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8931680502030834},\n", " 'CM': {'0': {'-1': 0, '0': 4, '1': 153, '2': 24, '3': 3, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 37, '2': 40, '3': 20, '4': 3, '5': 0},\n", @@ -10350,12 +17912,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2578595267192039,\n", " 'Micro-F1': 0.33268101761252444,\n", - " 'F1-0': 0.5173745173745173,\n", - " 'F1-1': 0.29310344827586204,\n", - " 'F1-2': 0.24761904761904763,\n", - " 'F1-3': 0.3192488262910798,\n", - " 'F1-4': 0.16981132075471697,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5173745173745173,\n", + " 'F1-1_vs_rest': 0.29310344827586204,\n", + " 'F1-2_vs_rest': 0.24761904761904763,\n", + " 'F1-3_vs_rest': 0.3192488262910798,\n", + " 'F1-4_vs_rest': 0.16981132075471697,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.836173001310616,\n", + " 'Recall-0.5': 0.9815384615384616,\n", + " 'Precision-0.5': 0.728310502283105,\n", + " 'F1-1.5': 0.7495291902071564,\n", + " 'Recall-1.5': 0.8844444444444445,\n", + " 'Precision-1.5': 0.6503267973856209,\n", + " 'F1-2.5': 0.573208722741433,\n", + " 'Recall-2.5': 0.773109243697479,\n", + " 'Precision-2.5': 0.45544554455445546,\n", + " 'F1-3.5': 0.2037037037037037,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.11827956989247312,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9070533802148367},\n", " 'CM': {'0': {'-1': 0, '0': 67, '1': 75, '2': 31, '3': 8, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 3, '1': 34, '2': 30, '3': 21, '4': 12, '5': 0},\n", @@ -10382,12 +17959,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08234861459894245,\n", " 'Micro-F1': 0.10176125244618395,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.05154639175257732,\n", - " 'F1-2': 0.14096916299559473,\n", - " 'F1-3': 0.20588235294117646,\n", - " 'F1-4': 0.09569377990430622,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.05154639175257732,\n", + " 'F1-2_vs_rest': 0.14096916299559473,\n", + " 'F1-3_vs_rest': 0.20588235294117646,\n", + " 'F1-4_vs_rest': 0.09569377990430622,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.6791277258566978,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5227817745803357,\n", + " 'F1-2.5': 0.5301204819277109,\n", + " 'Recall-2.5': 0.9243697478991597,\n", + " 'Precision-2.5': 0.3716216216216216,\n", + " 'F1-3.5': 0.11374407582938388,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.061224489795918366,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8902497426166835},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 82, '2': 68, '3': 24, '4': 12, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 30, '3': 28, '4': 37, '5': 0},\n", @@ -10414,12 +18006,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.14955538972877083,\n", " 'Micro-F1': 0.12573673870333987,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.06091370558375635,\n", - " 'F1-2': 0.12440191387559808,\n", - " 'F1-3': 0.2545454545454545,\n", - " 'F1-4': 0.12413793103448276,\n", - " 'F1-5': 0.3333333333333333,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.06091370558375635,\n", + " 'F1-2_vs_rest': 0.12440191387559808,\n", + " 'F1-3_vs_rest': 0.2545454545454545,\n", + " 'F1-4_vs_rest': 0.12413793103448276,\n", + " 'F1-5_vs_rest': 0.3333333333333333,\n", + " 'F1-0.5': 0.7764423076923077,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6345776031434185,\n", + " 'F1-1.5': 0.6992125984251969,\n", + " 'Recall-1.5': 0.9955156950672646,\n", + " 'Precision-1.5': 0.5388349514563107,\n", + " 'F1-2.5': 0.5446009389671361,\n", + " 'Recall-2.5': 0.9747899159663865,\n", + " 'Precision-2.5': 0.3778501628664495,\n", + " 'F1-3.5': 0.1456953642384106,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08088235294117647,\n", + " 'F1-4.5': 0.3333333333333333,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.25,\n", " 'NDCG@all': 0.9160994488516837},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 90, '2': 65, '3': 24, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 24, '3': 54, '4': 16, '5': 0},\n", @@ -10446,12 +18053,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.27250633937708263,\n", " 'Micro-F1': 0.3542074363992172,\n", - " 'F1-0': 0.3076923076923077,\n", - " 'F1-1': 0.2888086642599278,\n", - " 'F1-2': 0.42857142857142855,\n", - " 'F1-3': 0.44329896907216493,\n", - " 'F1-4': 0.16666666666666666,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3076923076923077,\n", + " 'F1-1_vs_rest': 0.2888086642599278,\n", + " 'F1-2_vs_rest': 0.42857142857142855,\n", + " 'F1-3_vs_rest': 0.44329896907216493,\n", + " 'F1-4_vs_rest': 0.16666666666666666,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8089887640449438,\n", + " 'Recall-0.5': 0.9969230769230769,\n", + " 'Precision-0.5': 0.680672268907563,\n", + " 'F1-1.5': 0.7824427480916031,\n", + " 'Recall-1.5': 0.9111111111111111,\n", + " 'Precision-1.5': 0.68561872909699,\n", + " 'F1-2.5': 0.5655737704918032,\n", + " 'Recall-2.5': 0.5798319327731093,\n", + " 'Precision-2.5': 0.552,\n", + " 'F1-3.5': 0.2,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9033688892976336},\n", " 'CM': {'0': {'-1': 0, '0': 34, '1': 118, '2': 26, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 40, '2': 42, '3': 14, '4': 4, '5': 0},\n", @@ -10478,12 +18100,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08438482536467534,\n", " 'Micro-F1': 0.09727626459143969,\n", - " 'F1-0': 0.09195402298850575,\n", - " 'F1-1': 0.08823529411764706,\n", - " 'F1-2': 0.11320754716981132,\n", - " 'F1-3': 0.08791208791208792,\n", - " 'F1-4': 0.125,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09195402298850575,\n", + " 'F1-1_vs_rest': 0.08823529411764706,\n", + " 'F1-2_vs_rest': 0.11320754716981132,\n", + " 'F1-3_vs_rest': 0.08791208791208792,\n", + " 'F1-4_vs_rest': 0.125,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8149882903981265,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6877470355731226,\n", + " 'F1-1.5': 0.6740947075208914,\n", + " 'Recall-1.5': 0.9918032786885246,\n", + " 'Precision-1.5': 0.510548523206751,\n", + " 'F1-2.5': 0.45849802371541504,\n", + " 'Recall-2.5': 0.9206349206349206,\n", + " 'Precision-2.5': 0.30526315789473685,\n", + " 'F1-3.5': 0.09876543209876543,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.05263157894736842,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8713201665910568},\n", " 'CM': {'0': {'-1': 103, '0': 4, '1': 12, '2': 32, '3': 15, '4': 19, '5': 1},\n", " '1': {'-1': 48, '0': 0, '1': 3, '2': 5, '3': 9, '4': 28, '5': 7},\n", @@ -10491,6 +18128,53 @@ " '3': {'-1': 51, '0': 0, '1': 1, '2': 4, '3': 4, '4': 33, '5': 11},\n", " '4': {'-1': 3, '0': 0, '1': 0, '2': 0, '3': 2, '4': 8, '5': 0},\n", " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.08097432521395662,\n", + " 'Cohen': 0.1287862407862408,\n", + " 'Spearman': 0.679076755966462,\n", + " 'Kendall': 0.5845637926908267,\n", + " 'Krippendorff': 0.5534179055404889,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7362204724409449,\n", + " 'TA-4.0': 0.9665354330708661,\n", + " 'Acc': 0.31299212598425197,\n", + " 'MAE': 0.8274278215223095,\n", + " 'MSE': 1.0855205599300084,\n", + " 'CA-0': 0.15053763440860216,\n", + " 'CA-1': 0.24,\n", + " 'CA-2': 0.6415094339622641,\n", + " 'CA-3': 0.38613861386138615,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2095646268062484,\n", + " 'Micro-F1': 0.31299212598425197,\n", + " 'F1-0_vs_rest': 0.26046511627906976,\n", + " 'F1-1_vs_rest': 0.18604651162790697,\n", + " 'F1-2_vs_rest': 0.4108761329305136,\n", + " 'F1-3_vs_rest': 0.4,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8014981273408239,\n", + " 'Recall-0.5': 0.9968944099378882,\n", + " 'Precision-0.5': 0.6701461377870563,\n", + " 'F1-1.5': 0.7734806629834254,\n", + " 'Recall-1.5': 0.9459459459459459,\n", + " 'Precision-1.5': 0.6542056074766355,\n", + " 'F1-2.5': 0.46226415094339623,\n", + " 'Recall-2.5': 0.4224137931034483,\n", + " 'Precision-2.5': 0.5104166666666666,\n", + " 'F1-3.5': 0.0,\n", + " 'Recall-3.5': 0.0,\n", + " 'Precision-3.5': 0.0,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8968895752270242},\n", + " 'CM': {'0': {'-1': 0, '0': 28, '1': 122, '2': 32, '3': 4, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 24, '2': 59, '3': 16, '4': 0, '5': 0},\n", + " '2': {'-1': 0, '0': 0, '1': 11, '2': 68, '3': 25, '4': 2, '5': 0},\n", + " '3': {'-1': 3, '0': 0, '1': 1, '2': 61, '3': 39, '4': 0, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08535765130539082,\n", " 'Cohen': 0.11497681481682354,\n", " 'Spearman': 0.6776898952634417,\n", @@ -10510,12 +18194,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.23837714779297592,\n", " 'Micro-F1': 0.27061310782241016,\n", - " 'F1-0': 0.4055299539170507,\n", - " 'F1-1': 0.17543859649122806,\n", - " 'F1-2': 0.2832618025751073,\n", - " 'F1-3': 0.3010752688172043,\n", - " 'F1-4': 0.1111111111111111,\n", - " 'F1-5': 0.15384615384615385,\n", + " 'F1-0_vs_rest': 0.4055299539170507,\n", + " 'F1-1_vs_rest': 0.17543859649122806,\n", + " 'F1-2_vs_rest': 0.2832618025751073,\n", + " 'F1-3_vs_rest': 0.3010752688172043,\n", + " 'F1-4_vs_rest': 0.1111111111111111,\n", + " 'F1-5_vs_rest': 0.15384615384615385,\n", + " 'F1-0.5': 0.823045267489712,\n", + " 'Recall-0.5': 0.974025974025974,\n", + " 'Precision-0.5': 0.7125890736342043,\n", + " 'F1-1.5': 0.7491039426523297,\n", + " 'Recall-1.5': 0.954337899543379,\n", + " 'Precision-1.5': 0.616519174041298,\n", + " 'F1-2.5': 0.6338461538461538,\n", + " 'Recall-2.5': 0.8879310344827587,\n", + " 'Precision-2.5': 0.49282296650717705,\n", + " 'F1-3.5': 0.14388489208633093,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08064516129032258,\n", + " 'F1-4.5': 0.15384615384615385,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.09090909090909091,\n", " 'NDCG@all': 0.9241520199673287},\n", " 'CM': {'0': {'-1': 21, '0': 44, '1': 60, '2': 45, '3': 7, '4': 8, '5': 1},\n", " '1': {'-1': 11, '0': 5, '1': 15, '2': 39, '3': 18, '4': 10, '5': 2},\n", @@ -10542,12 +18241,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11649725843161596,\n", " 'Micro-F1': 0.1487279843444227,\n", - " 'F1-0': 0.0625,\n", - " 'F1-1': 0.0670391061452514,\n", - " 'F1-2': 0.1803921568627451,\n", - " 'F1-3': 0.25833333333333336,\n", - " 'F1-4': 0.13071895424836602,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0625,\n", + " 'F1-1_vs_rest': 0.0670391061452514,\n", + " 'F1-2_vs_rest': 0.1803921568627451,\n", + " 'F1-3_vs_rest': 0.25833333333333336,\n", + " 'F1-4_vs_rest': 0.13071895424836602,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7831325301204819,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6435643564356436,\n", + " 'F1-1.5': 0.6697388632872504,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5117370892018779,\n", + " 'F1-2.5': 0.5505050505050505,\n", + " 'Recall-2.5': 0.9159663865546218,\n", + " 'Precision-2.5': 0.3935018050541516,\n", + " 'F1-3.5': 0.15384615384615385,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.0851063829787234,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8951227656363437},\n", " 'CM': {'0': {'-1': 0, '0': 6, '1': 66, '2': 77, '3': 29, '4': 8, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 41, '3': 34, '4': 19, '5': 0},\n", @@ -10555,7 +18269,54 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 8, '3': 31, '4': 63, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'hu': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12755629545255412,\n", + " 'hu': {'phi-4': {'metrics': {'Fleiss': 0.21657438369629106,\n", + " 'Cohen': 0.23120919388689887,\n", + " 'Spearman': 0.6468113833003012,\n", + " 'Kendall': 0.5407778162009823,\n", + " 'Krippendorff': 0.5392635339166326,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7196078431372549,\n", + " 'TA-4.0': 0.8921568627450981,\n", + " 'Acc': 0.39019607843137255,\n", + " 'MAE': 0.891503267973856,\n", + " 'MSE': 1.5989106753812639,\n", + " 'CA-0': 0.40860215053763443,\n", + " 'CA-1': 0.26262626262626265,\n", + " 'CA-2': 0.3018867924528302,\n", + " 'CA-3': 0.5576923076923077,\n", + " 'CA-4': 0.46153846153846156,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3460834455038851,\n", + " 'Micro-F1': 0.39019607843137255,\n", + " 'F1-0_vs_rest': 0.5692883895131086,\n", + " 'F1-1_vs_rest': 0.2561576354679803,\n", + " 'F1-2_vs_rest': 0.29493087557603687,\n", + " 'F1-3_vs_rest': 0.45136186770428016,\n", + " 'F1-4_vs_rest': 0.17142857142857143,\n", + " 'F1-5_vs_rest': 0.3333333333333333,\n", + " 'F1-0.5': 0.8472775564409031,\n", + " 'Recall-0.5': 0.9845679012345679,\n", + " 'Precision-0.5': 0.7435897435897436,\n", + " 'F1-1.5': 0.7527272727272727,\n", + " 'Recall-1.5': 0.92,\n", + " 'Precision-1.5': 0.6369230769230769,\n", + " 'F1-2.5': 0.5825825825825826,\n", + " 'Recall-2.5': 0.8151260504201681,\n", + " 'Precision-2.5': 0.4532710280373832,\n", + " 'F1-3.5': 0.21052631578947367,\n", + " 'Recall-3.5': 0.5333333333333333,\n", + " 'Precision-3.5': 0.13114754098360656,\n", + " 'F1-4.5': 0.3333333333333333,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.25,\n", + " 'NDCG@all': 0.892707184986355},\n", + " 'CM': {'0': {'-1': 0, '0': 76, '1': 60, '2': 30, '3': 16, '4': 3, '5': 1},\n", + " '1': {'-1': 1, '0': 5, '1': 26, '2': 33, '3': 27, '4': 7, '5': 1},\n", + " '2': {'-1': 0, '0': 0, '1': 12, '2': 32, '3': 46, '4': 15, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 6, '2': 15, '3': 58, '4': 25, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 6, '4': 6, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12755629545255412,\n", " 'Cohen': 0.16182766217399247,\n", " 'Spearman': 0.5636475010853697,\n", " 'Kendall': 0.47764109519110004,\n", @@ -10574,12 +18335,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2617014744116037,\n", " 'Micro-F1': 0.33268101761252444,\n", - " 'F1-0': 0.29333333333333333,\n", - " 'F1-1': 0.2857142857142857,\n", - " 'F1-2': 0.3671875,\n", - " 'F1-3': 0.43349753694581283,\n", - " 'F1-4': 0.19047619047619047,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.29333333333333333,\n", + " 'F1-1_vs_rest': 0.2857142857142857,\n", + " 'F1-2_vs_rest': 0.3671875,\n", + " 'F1-3_vs_rest': 0.43349753694581283,\n", + " 'F1-4_vs_rest': 0.19047619047619047,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8005018820577164,\n", + " 'Recall-0.5': 0.9815384615384616,\n", + " 'Precision-0.5': 0.6758474576271186,\n", + " 'F1-1.5': 0.7236580516898609,\n", + " 'Recall-1.5': 0.8088888888888889,\n", + " 'Precision-1.5': 0.6546762589928058,\n", + " 'F1-2.5': 0.5425101214574899,\n", + " 'Recall-2.5': 0.5630252100840336,\n", + " 'Precision-2.5': 0.5234375,\n", + " 'F1-3.5': 0.22727272727272727,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.1724137931034483,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.888959762255007},\n", " 'CM': {'0': {'-1': 0, '0': 33, '1': 111, '2': 33, '3': 6, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 42, '2': 36, '3': 10, '4': 8, '5': 0},\n", @@ -10606,12 +18382,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.30711776900518944,\n", " 'Micro-F1': 0.3913894324853229,\n", - " 'F1-0': 0.6712328767123288,\n", - " 'F1-1': 0.3111111111111111,\n", - " 'F1-2': 0.38497652582159625,\n", - " 'F1-3': 0.24324324324324326,\n", - " 'F1-4': 0.10714285714285714,\n", - " 'F1-5': 0.125,\n", + " 'F1-0_vs_rest': 0.6712328767123288,\n", + " 'F1-1_vs_rest': 0.3111111111111111,\n", + " 'F1-2_vs_rest': 0.38497652582159625,\n", + " 'F1-3_vs_rest': 0.24324324324324326,\n", + " 'F1-4_vs_rest': 0.10714285714285714,\n", + " 'F1-5_vs_rest': 0.125,\n", + " 'F1-0.5': 0.8684931506849315,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.782716049382716,\n", + " 'F1-1.5': 0.7762376237623763,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.7,\n", + " 'F1-2.5': 0.636986301369863,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.5375722543352601,\n", + " 'F1-3.5': 0.1527777777777778,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08527131782945736,\n", + " 'F1-4.5': 0.125,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.06666666666666667,\n", " 'NDCG@all': 0.8905951027249435},\n", " 'CM': {'0': {'-1': 0, '0': 98, '1': 61, '2': 15, '3': 4, '4': 3, '5': 5},\n", " '1': {'-1': 0, '0': 8, '1': 35, '2': 31, '3': 3, '4': 16, '5': 7},\n", @@ -10638,12 +18429,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22119314743038232,\n", " 'Micro-F1': 0.30844793713163066,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.2857142857142857,\n", - " 'F1-2': 0.4048582995951417,\n", - " 'F1-3': 0.47761194029850745,\n", - " 'F1-4': 0.06666666666666667,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.2857142857142857,\n", + " 'F1-2_vs_rest': 0.4048582995951417,\n", + " 'F1-3_vs_rest': 0.47761194029850745,\n", + " 'F1-4_vs_rest': 0.06666666666666667,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7849331713244229,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.646,\n", + " 'F1-1.5': 0.7625,\n", + " 'Recall-1.5': 0.820627802690583,\n", + " 'Precision-1.5': 0.7120622568093385,\n", + " 'F1-2.5': 0.5579399141630901,\n", + " 'Recall-2.5': 0.5555555555555556,\n", + " 'Precision-2.5': 0.5603448275862069,\n", + " 'F1-3.5': 0.125,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.11764705882352941,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8975707836309588},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 154, '2': 16, '3': 6, '4': 1, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 49, '2': 35, '3': 12, '4': 4, '5': 0},\n", @@ -10670,12 +18476,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.3202771620004218,\n", " 'Micro-F1': 0.30724070450097846,\n", - " 'F1-0': 0.49230769230769234,\n", - " 'F1-1': 0.2661290322580645,\n", - " 'F1-2': 0.21428571428571427,\n", - " 'F1-3': 0.27751196172248804,\n", - " 'F1-4': 0.17142857142857143,\n", - " 'F1-5': 0.5,\n", + " 'F1-0_vs_rest': 0.49230769230769234,\n", + " 'F1-1_vs_rest': 0.2661290322580645,\n", + " 'F1-2_vs_rest': 0.21428571428571427,\n", + " 'F1-3_vs_rest': 0.27751196172248804,\n", + " 'F1-4_vs_rest': 0.17142857142857143,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8267716535433071,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7208237986270023,\n", + " 'F1-1.5': 0.7276264591439688,\n", + " 'Recall-1.5': 0.8311111111111111,\n", + " 'Precision-1.5': 0.6470588235294118,\n", + " 'F1-2.5': 0.559748427672956,\n", + " 'Recall-2.5': 0.7478991596638656,\n", + " 'Precision-2.5': 0.4472361809045226,\n", + " 'F1-3.5': 0.2018348623853211,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.11702127659574468,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", " 'NDCG@all': 0.9146346250909738},\n", " 'CM': {'0': {'-1': 0, '0': 64, '1': 80, '2': 28, '3': 10, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 7, '1': 33, '2': 25, '3': 22, '4': 13, '5': 0},\n", @@ -10702,12 +18523,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.10595906213376094,\n", " 'Micro-F1': 0.13111545988258316,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.10256410256410256,\n", - " 'F1-2': 0.20080321285140562,\n", - " 'F1-3': 0.20833333333333334,\n", - " 'F1-4': 0.09230769230769231,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.10256410256410256,\n", + " 'F1-2_vs_rest': 0.20080321285140562,\n", + " 'F1-3_vs_rest': 0.20833333333333334,\n", + " 'F1-4_vs_rest': 0.09230769230769231,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78031212484994,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.639763779527559,\n", + " 'F1-1.5': 0.6865203761755486,\n", + " 'Recall-1.5': 0.9733333333333334,\n", + " 'Precision-1.5': 0.5302663438256658,\n", + " 'F1-2.5': 0.5501285347043702,\n", + " 'Recall-2.5': 0.8991596638655462,\n", + " 'Precision-2.5': 0.3962962962962963,\n", + " 'F1-3.5': 0.1116751269035533,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.06043956043956044,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8866072382281535},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 79, '2': 71, '3': 16, '4': 17, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 10, '2': 38, '3': 21, '4': 31, '5': 0},\n", @@ -10734,12 +18570,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.09143760259663325,\n", " 'Micro-F1': 0.11787819253438114,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.0594059405940594,\n", - " 'F1-2': 0.13793103448275862,\n", - " 'F1-3': 0.23048327137546468,\n", - " 'F1-4': 0.12080536912751678,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.0594059405940594,\n", + " 'F1-2_vs_rest': 0.13793103448275862,\n", + " 'F1-3_vs_rest': 0.23048327137546468,\n", + " 'F1-4_vs_rest': 0.12080536912751678,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7764423076923077,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6345776031434185,\n", + " 'F1-1.5': 0.707936507936508,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.547911547911548,\n", + " 'F1-2.5': 0.5292740046838408,\n", + " 'Recall-2.5': 0.9658119658119658,\n", + " 'Precision-2.5': 0.36451612903225805,\n", + " 'F1-3.5': 0.13924050632911392,\n", + " 'Recall-3.5': 0.7857142857142857,\n", + " 'Precision-3.5': 0.0763888888888889,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8926916357304051},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 96, '2': 51, '3': 34, '4': 4, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 6, '2': 28, '3': 45, '4': 20, '5': 1},\n", @@ -10766,12 +18617,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.28192934448561013,\n", " 'Micro-F1': 0.3796477495107632,\n", - " 'F1-0': 0.36123348017621143,\n", - " 'F1-1': 0.28776978417266186,\n", - " 'F1-2': 0.45,\n", - " 'F1-3': 0.4873096446700508,\n", - " 'F1-4': 0.10526315789473684,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.36123348017621143,\n", + " 'F1-1_vs_rest': 0.28776978417266186,\n", + " 'F1-2_vs_rest': 0.45,\n", + " 'F1-3_vs_rest': 0.4873096446700508,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8176100628930818,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6914893617021277,\n", + " 'F1-1.5': 0.781431334622824,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.6917808219178082,\n", + " 'F1-2.5': 0.5907172995780591,\n", + " 'Recall-2.5': 0.5882352941176471,\n", + " 'Precision-2.5': 0.5932203389830508,\n", + " 'F1-3.5': 0.15,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.12,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.898176708232311},\n", " 'CM': {'0': {'-1': 0, '0': 41, '1': 115, '2': 24, '3': 2, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 40, '2': 43, '3': 13, '4': 4, '5': 0},\n", @@ -10798,12 +18664,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11501825807140464,\n", " 'Micro-F1': 0.14233576642335766,\n", - " 'F1-0': 0.10989010989010989,\n", - " 'F1-1': 0.0759493670886076,\n", - " 'F1-2': 0.14516129032258066,\n", - " 'F1-3': 0.2857142857142857,\n", - " 'F1-4': 0.07339449541284404,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.10989010989010989,\n", + " 'F1-1_vs_rest': 0.0759493670886076,\n", + " 'F1-2_vs_rest': 0.14516129032258066,\n", + " 'F1-3_vs_rest': 0.2857142857142857,\n", + " 'F1-4_vs_rest': 0.07339449541284404,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8227571115973742,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6988847583643123,\n", + " 'F1-1.5': 0.7037037037037037,\n", + " 'Recall-1.5': 0.9851851851851852,\n", + " 'Precision-1.5': 0.5473251028806584,\n", + " 'F1-2.5': 0.5275590551181102,\n", + " 'Recall-2.5': 0.9305555555555556,\n", + " 'Precision-2.5': 0.36813186813186816,\n", + " 'F1-3.5': 0.09375,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.05084745762711865,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8561176100292405},\n", " 'CM': {'0': {'-1': 100, '0': 5, '1': 21, '2': 33, '3': 12, '4': 12, '5': 3},\n", " '1': {'-1': 47, '0': 0, '1': 3, '2': 15, '3': 13, '4': 19, '5': 3},\n", @@ -10811,6 +18692,53 @@ " '3': {'-1': 42, '0': 0, '1': 0, '2': 3, '3': 18, '4': 36, '5': 5},\n", " '4': {'-1': 4, '0': 0, '1': 1, '2': 1, '3': 2, '4': 4, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1330923939101788,\n", + " 'Cohen': 0.17221891291826452,\n", + " 'Spearman': 0.6918260974807484,\n", + " 'Kendall': 0.5956201310825481,\n", + " 'Krippendorff': 0.5988176763026796,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7480314960629921,\n", + " 'TA-4.0': 0.968503937007874,\n", + " 'Acc': 0.3484251968503937,\n", + " 'MAE': 0.7709973753280837,\n", + " 'MSE': 0.9878608923884511,\n", + " 'CA-0': 0.22580645161290322,\n", + " 'CA-1': 0.31,\n", + " 'CA-2': 0.6,\n", + " 'CA-3': 0.38235294117647056,\n", + " 'CA-4': 0.15384615384615385,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2685013733761174,\n", + " 'Micro-F1': 0.3484251968503937,\n", + " 'F1-0_vs_rest': 0.36681222707423583,\n", + " 'F1-1_vs_rest': 0.2339622641509434,\n", + " 'F1-2_vs_rest': 0.39747634069400634,\n", + " 'F1-3_vs_rest': 0.430939226519337,\n", + " 'F1-4_vs_rest': 0.18181818181818182,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8157560355781448,\n", + " 'Recall-0.5': 0.9968944099378882,\n", + " 'Precision-0.5': 0.6903225806451613,\n", + " 'F1-1.5': 0.7739463601532567,\n", + " 'Recall-1.5': 0.9099099099099099,\n", + " 'Precision-1.5': 0.6733333333333333,\n", + " 'F1-2.5': 0.47804878048780486,\n", + " 'Recall-2.5': 0.4188034188034188,\n", + " 'Precision-2.5': 0.5568181818181818,\n", + " 'F1-3.5': 0.3333333333333333,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.4444444444444444,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9250655497221427},\n", + " 'CM': {'0': {'-1': 0, '0': 42, '1': 114, '2': 28, '3': 2, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 1, '1': 31, '2': 57, '3': 11, '4': 0, '5': 0},\n", + " '2': {'-1': 1, '0': 0, '1': 16, '2': 63, '3': 23, '4': 3, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 4, '2': 57, '3': 39, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 4, '4': 2, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.13125775079955615,\n", " 'Cohen': 0.15458962768491358,\n", " 'Spearman': 0.6646846101784928,\n", @@ -10830,12 +18758,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.23897131560377952,\n", " 'Micro-F1': 0.3181818181818182,\n", - " 'F1-0': 0.44635193133047213,\n", - " 'F1-1': 0.17989417989417988,\n", - " 'F1-2': 0.3643410852713178,\n", - " 'F1-3': 0.35233160621761656,\n", - " 'F1-4': 0.09090909090909091,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.44635193133047213,\n", + " 'F1-1_vs_rest': 0.17989417989417988,\n", + " 'F1-2_vs_rest': 0.3643410852713178,\n", + " 'F1-3_vs_rest': 0.35233160621761656,\n", + " 'F1-4_vs_rest': 0.09090909090909091,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8244897959183674,\n", + " 'Recall-0.5': 0.9805825242718447,\n", + " 'Precision-0.5': 0.7112676056338029,\n", + " 'F1-1.5': 0.7619047619047619,\n", + " 'Recall-1.5': 0.9585253456221198,\n", + " 'Precision-1.5': 0.6322188449848024,\n", + " 'F1-2.5': 0.5902777777777778,\n", + " 'Recall-2.5': 0.7456140350877193,\n", + " 'Precision-2.5': 0.4885057471264368,\n", + " 'F1-3.5': 0.12631578947368421,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.075,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8995136691627227},\n", " 'CM': {'0': {'-1': 11, '0': 52, '1': 72, '2': 38, '3': 7, '4': 5, '5': 1},\n", " '1': {'-1': 8, '0': 5, '1': 17, '2': 43, '3': 21, '4': 6, '5': 0},\n", @@ -10862,12 +18805,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1262100757994081,\n", " 'Micro-F1': 0.15851272015655576,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.07567567567567568,\n", - " 'F1-2': 0.16793893129770993,\n", - " 'F1-3': 0.27848101265822783,\n", - " 'F1-4': 0.14285714285714285,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.07567567567567568,\n", + " 'F1-2_vs_rest': 0.16793893129770993,\n", + " 'F1-3_vs_rest': 0.27848101265822783,\n", + " 'F1-4_vs_rest': 0.14285714285714285,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 0.6791277258566978,\n", + " 'Recall-1.5': 0.9688888888888889,\n", + " 'Precision-1.5': 0.5227817745803357,\n", + " 'F1-2.5': 0.5368421052631579,\n", + " 'Recall-2.5': 0.8571428571428571,\n", + " 'Precision-2.5': 0.39080459770114945,\n", + " 'F1-3.5': 0.16783216783216784,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.09375,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8815936325236656},\n", " 'CM': {'0': {'-1': 0, '0': 9, '1': 71, '2': 74, '3': 25, '4': 6, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 45, '3': 28, '4': 20, '5': 0},\n", @@ -10875,7 +18833,54 @@ " '3': {'-1': 0, '0': 0, '1': 2, '2': 15, '3': 33, '4': 54, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 3, '4': 10, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'uk': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.1442178532177311,\n", + " 'uk': {'phi-4': {'metrics': {'Fleiss': 0.2693842313962089,\n", + " 'Cohen': 0.277344438137368,\n", + " 'Spearman': 0.6363538283772251,\n", + " 'Kendall': 0.5303844808642745,\n", + " 'Krippendorff': 0.6028395079188598,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7553816046966731,\n", + " 'TA-4.0': 0.8904109589041096,\n", + " 'Acc': 0.4344422700587084,\n", + " 'MAE': 0.796477495107632,\n", + " 'MSE': 1.3613829093281142,\n", + " 'CA-0': 0.478494623655914,\n", + " 'CA-1': 0.36,\n", + " 'CA-2': 0.4056603773584906,\n", + " 'CA-3': 0.47115384615384615,\n", + " 'CA-4': 0.3076923076923077,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.40075664711923803,\n", + " 'Micro-F1': 0.4344422700587084,\n", + " 'F1-0_vs_rest': 0.6075085324232082,\n", + " 'F1-1_vs_rest': 0.3076923076923077,\n", + " 'F1-2_vs_rest': 0.39090909090909093,\n", + " 'F1-3_vs_rest': 0.47342995169082125,\n", + " 'F1-4_vs_rest': 0.125,\n", + " 'F1-5_vs_rest': 0.5,\n", + " 'F1-0.5': 0.8422496570644719,\n", + " 'Recall-0.5': 0.9446153846153846,\n", + " 'Precision-0.5': 0.7599009900990099,\n", + " 'F1-1.5': 0.7676767676767676,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.7037037037037037,\n", + " 'F1-2.5': 0.5890909090909091,\n", + " 'Recall-2.5': 0.680672268907563,\n", + " 'Precision-2.5': 0.5192307692307693,\n", + " 'F1-3.5': 0.17647058823529413,\n", + " 'Recall-3.5': 0.4,\n", + " 'Precision-3.5': 0.11320754716981132,\n", + " 'F1-4.5': 0.5,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.5,\n", + " 'NDCG@all': 0.8964684901544908},\n", + " 'CM': {'0': {'-1': 0, '0': 89, '1': 66, '2': 20, '3': 6, '4': 4, '5': 1},\n", + " '1': {'-1': 0, '0': 15, '1': 36, '2': 25, '3': 14, '4': 10, '5': 0},\n", + " '2': {'-1': 0, '0': 2, '1': 21, '2': 43, '3': 27, '4': 13, '5': 0},\n", + " '3': {'-1': 0, '0': 1, '1': 11, '2': 24, '3': 49, '4': 19, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 2, '3': 7, '4': 4, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.1442178532177311,\n", " 'Cohen': 0.16939108223558497,\n", " 'Spearman': 0.6023196539198984,\n", " 'Kendall': 0.506251854177832,\n", @@ -10894,12 +18899,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2596754153730898,\n", " 'Micro-F1': 0.3424657534246575,\n", - " 'F1-0': 0.4083333333333333,\n", - " 'F1-1': 0.3054545454545455,\n", - " 'F1-2': 0.30833333333333335,\n", - " 'F1-3': 0.3963963963963964,\n", - " 'F1-4': 0.13953488372093023,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4083333333333333,\n", + " 'F1-1_vs_rest': 0.3054545454545455,\n", + " 'F1-2_vs_rest': 0.30833333333333335,\n", + " 'F1-3_vs_rest': 0.3963963963963964,\n", + " 'F1-4_vs_rest': 0.13953488372093023,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8184143222506394,\n", + " 'Recall-0.5': 0.9846153846153847,\n", + " 'Precision-0.5': 0.700218818380744,\n", + " 'F1-1.5': 0.7455621301775148,\n", + " 'Recall-1.5': 0.84,\n", + " 'Precision-1.5': 0.6702127659574468,\n", + " 'F1-2.5': 0.5168539325842697,\n", + " 'Recall-2.5': 0.5798319327731093,\n", + " 'Precision-2.5': 0.46621621621621623,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.3333333333333333,\n", + " 'Precision-3.5': 0.16666666666666666,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9004855921341497},\n", " 'CM': {'0': {'-1': 0, '0': 49, '1': 98, '2': 29, '3': 8, '4': 2, '5': 0},\n", " '1': {'-1': 0, '0': 4, '1': 42, '2': 31, '3': 18, '4': 5, '5': 0},\n", @@ -10926,12 +18946,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.2862939502603148,\n", " 'Micro-F1': 0.3561643835616438,\n", - " 'F1-0': 0.6064981949458483,\n", - " 'F1-1': 0.3445378151260504,\n", - " 'F1-2': 0.31746031746031744,\n", - " 'F1-3': 0.21951219512195122,\n", - " 'F1-4': 0.11864406779661017,\n", - " 'F1-5': 0.1111111111111111,\n", + " 'F1-0_vs_rest': 0.6064981949458483,\n", + " 'F1-1_vs_rest': 0.3445378151260504,\n", + " 'F1-2_vs_rest': 0.31746031746031744,\n", + " 'F1-3_vs_rest': 0.21951219512195122,\n", + " 'F1-4_vs_rest': 0.11864406779661017,\n", + " 'F1-5_vs_rest': 0.1111111111111111,\n", + " 'F1-0.5': 0.8536912751677852,\n", + " 'Recall-0.5': 0.9784615384615385,\n", + " 'Precision-0.5': 0.7571428571428571,\n", + " 'F1-1.5': 0.796844181459566,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.7163120567375887,\n", + " 'F1-2.5': 0.6037735849056604,\n", + " 'Recall-2.5': 0.8067226890756303,\n", + " 'Precision-2.5': 0.4824120603015075,\n", + " 'F1-3.5': 0.14285714285714285,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07913669064748201,\n", + " 'F1-4.5': 0.1111111111111111,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.058823529411764705,\n", " 'NDCG@all': 0.8919731406869117},\n", " 'CM': {'0': {'-1': 0, '0': 84, '1': 74, '2': 13, '3': 4, '4': 6, '5': 5},\n", " '1': {'-1': 0, '0': 7, '1': 41, '2': 21, '3': 9, '4': 15, '5': 7},\n", @@ -10958,12 +18993,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.213788237056911,\n", " 'Micro-F1': 0.2868369351669941,\n", - " 'F1-0': 0.10204081632653061,\n", - " 'F1-1': 0.26112759643916916,\n", - " 'F1-2': 0.33766233766233766,\n", - " 'F1-3': 0.4766355140186916,\n", - " 'F1-4': 0.10526315789473684,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.10204081632653061,\n", + " 'F1-1_vs_rest': 0.26112759643916916,\n", + " 'F1-2_vs_rest': 0.33766233766233766,\n", + " 'F1-3_vs_rest': 0.4766355140186916,\n", + " 'F1-4_vs_rest': 0.10526315789473684,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7858880778588808,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6472945891783567,\n", + " 'F1-1.5': 0.7628865979381443,\n", + " 'Recall-1.5': 0.8295964125560538,\n", + " 'Precision-1.5': 0.7061068702290076,\n", + " 'F1-2.5': 0.5748031496062992,\n", + " 'Recall-2.5': 0.6186440677966102,\n", + " 'Precision-2.5': 0.5367647058823529,\n", + " 'F1-3.5': 0.15,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.12,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9061872586542914},\n", " 'CM': {'0': {'-1': 0, '0': 10, '1': 155, '2': 15, '3': 5, '4': 1, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 44, '2': 36, '3': 17, '4': 3, '5': 0},\n", @@ -10990,12 +19040,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2723719937469937,\n", " 'Micro-F1': 0.35812133072407043,\n", - " 'F1-0': 0.5672727272727273,\n", - " 'F1-1': 0.288,\n", - " 'F1-2': 0.2828282828282828,\n", - " 'F1-3': 0.34375,\n", - " 'F1-4': 0.1523809523809524,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5672727272727273,\n", + " 'F1-1_vs_rest': 0.288,\n", + " 'F1-2_vs_rest': 0.2828282828282828,\n", + " 'F1-3_vs_rest': 0.34375,\n", + " 'F1-4_vs_rest': 0.1523809523809524,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8406961178045516,\n", + " 'Recall-0.5': 0.9661538461538461,\n", + " 'Precision-0.5': 0.7440758293838863,\n", + " 'F1-1.5': 0.7364185110663984,\n", + " 'Recall-1.5': 0.8133333333333334,\n", + " 'Precision-1.5': 0.6727941176470589,\n", + " 'F1-2.5': 0.5953177257525084,\n", + " 'Recall-2.5': 0.7478991596638656,\n", + " 'Precision-2.5': 0.49444444444444446,\n", + " 'F1-3.5': 0.18691588785046728,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.10869565217391304,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9008371614503143},\n", " 'CM': {'0': {'-1': 0, '0': 78, '1': 74, '2': 20, '3': 7, '4': 7, '5': 0},\n", " '1': {'-1': 0, '0': 9, '1': 36, '2': 30, '3': 13, '4': 12, '5': 0},\n", @@ -11022,12 +19087,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.1137304954689291,\n", " 'Micro-F1': 0.14090019569471623,\n", - " 'F1-0': 0.031746031746031744,\n", - " 'F1-1': 0.08648648648648649,\n", - " 'F1-2': 0.16793893129770993,\n", - " 'F1-3': 0.2857142857142857,\n", - " 'F1-4': 0.11049723756906077,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.031746031746031744,\n", + " 'F1-1_vs_rest': 0.08648648648648649,\n", + " 'F1-2_vs_rest': 0.16793893129770993,\n", + " 'F1-3_vs_rest': 0.2857142857142857,\n", + " 'F1-4_vs_rest': 0.11049723756906077,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.78031212484994,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.639763779527559,\n", + " 'F1-1.5': 0.6790123456790124,\n", + " 'Recall-1.5': 0.9777777777777777,\n", + " 'Precision-1.5': 0.5200945626477541,\n", + " 'F1-2.5': 0.5492227979274611,\n", + " 'Recall-2.5': 0.8907563025210085,\n", + " 'Precision-2.5': 0.3970037453183521,\n", + " 'F1-3.5': 0.13114754098360656,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.07142857142857142,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8912214409857525},\n", " 'CM': {'0': {'-1': 0, '0': 3, '1': 72, '2': 84, '3': 15, '4': 12, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 39, '3': 25, '4': 28, '5': 0},\n", @@ -11054,12 +19134,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.0822726721530147,\n", " 'Micro-F1': 0.10588235294117647,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.04950495049504951,\n", - " 'F1-2': 0.10526315789473684,\n", - " 'F1-3': 0.2188679245283019,\n", - " 'F1-4': 0.12,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.04950495049504951,\n", + " 'F1-2_vs_rest': 0.10526315789473684,\n", + " 'F1-3_vs_rest': 0.2188679245283019,\n", + " 'F1-4_vs_rest': 0.12,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.7025316455696202,\n", + " 'Recall-1.5': 0.9910714285714286,\n", + " 'Precision-1.5': 0.5441176470588235,\n", + " 'F1-2.5': 0.5437352245862884,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.3782894736842105,\n", + " 'F1-3.5': 0.13924050632911392,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07692307692307693,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8912986367420203},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 95, '2': 58, '3': 26, '4': 6, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 5, '2': 32, '3': 45, '4': 17, '5': 1},\n", @@ -11086,12 +19181,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.28182006195947723,\n", " 'Micro-F1': 0.3796477495107632,\n", - " 'F1-0': 0.3684210526315789,\n", - " 'F1-1': 0.27205882352941174,\n", - " 'F1-2': 0.43609022556390975,\n", - " 'F1-3': 0.5213270142180095,\n", - " 'F1-4': 0.09302325581395349,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3684210526315789,\n", + " 'F1-1_vs_rest': 0.27205882352941174,\n", + " 'F1-2_vs_rest': 0.43609022556390975,\n", + " 'F1-3_vs_rest': 0.5213270142180095,\n", + " 'F1-4_vs_rest': 0.09302325581395349,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.818639798488665,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6929637526652452,\n", + " 'F1-1.5': 0.7701149425287356,\n", + " 'Recall-1.5': 0.8933333333333333,\n", + " 'Precision-1.5': 0.6767676767676768,\n", + " 'F1-2.5': 0.609375,\n", + " 'Recall-2.5': 0.6554621848739496,\n", + " 'Precision-2.5': 0.5693430656934306,\n", + " 'F1-3.5': 0.13333333333333333,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8967804977530014},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 111, '2': 23, '3': 7, '4': 3, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 37, '2': 44, '3': 14, '4': 5, '5': 0},\n", @@ -11118,12 +19228,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.07264884873580525,\n", " 'Micro-F1': 0.0860655737704918,\n", - " 'F1-0': 0.1,\n", - " 'F1-1': 0.057971014492753624,\n", - " 'F1-2': 0.12727272727272726,\n", - " 'F1-3': 0.07792207792207792,\n", - " 'F1-4': 0.07272727272727272,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.1,\n", + " 'F1-1_vs_rest': 0.057971014492753624,\n", + " 'F1-2_vs_rest': 0.12727272727272726,\n", + " 'F1-3_vs_rest': 0.07792207792207792,\n", + " 'F1-4_vs_rest': 0.07272727272727272,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7680412371134021,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6234309623430963,\n", + " 'F1-1.5': 0.6206896551724138,\n", + " 'Recall-1.5': 0.9801980198019802,\n", + " 'Precision-1.5': 0.4541284403669725,\n", + " 'F1-2.5': 0.4688995215311005,\n", + " 'Recall-2.5': 0.9607843137254902,\n", + " 'Precision-2.5': 0.310126582278481,\n", + " 'F1-3.5': 0.09090909090909091,\n", + " 'Recall-3.5': 1.0,\n", + " 'Precision-3.5': 0.047619047619047616,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8642741315063062},\n", " 'CM': {'0': {'-1': 91, '0': 5, '1': 17, '2': 41, '3': 13, '4': 17, '5': 2},\n", " '1': {'-1': 52, '0': 0, '1': 2, '2': 10, '3': 9, '4': 26, '5': 1},\n", @@ -11131,6 +19256,53 @@ " '3': {'-1': 59, '0': 0, '1': 0, '2': 2, '3': 3, '4': 31, '5': 9},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 0, '3': 0, '4': 4, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10862978776161722,\n", + " 'Cohen': 0.15055160904432086,\n", + " 'Spearman': 0.6886876667953257,\n", + " 'Kendall': 0.591076332649804,\n", + " 'Krippendorff': 0.5861321111679656,\n", + " 'Invalid': 2,\n", + " 'TA-2.0': 0.7485265225933202,\n", + " 'TA-4.0': 0.9666011787819253,\n", + " 'Acc': 0.33398821218074654,\n", + " 'MAE': 0.7897838899803533,\n", + " 'MSE': 1.0106963545077492,\n", + " 'CA-0': 0.22043010752688172,\n", + " 'CA-1': 0.3,\n", + " 'CA-2': 0.6132075471698113,\n", + " 'CA-3': 0.3333333333333333,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.22524278966178923,\n", + " 'Micro-F1': 0.33398821218074654,\n", + " 'F1-0_vs_rest': 0.35807860262008734,\n", + " 'F1-1_vs_rest': 0.23622047244094488,\n", + " 'F1-2_vs_rest': 0.39156626506024095,\n", + " 'F1-3_vs_rest': 0.3655913978494624,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8136882129277566,\n", + " 'Recall-0.5': 0.9938080495356038,\n", + " 'Precision-0.5': 0.6888412017167382,\n", + " 'F1-1.5': 0.7850467289719626,\n", + " 'Recall-1.5': 0.9417040358744395,\n", + " 'Precision-1.5': 0.6730769230769231,\n", + " 'F1-2.5': 0.43349753694581283,\n", + " 'Recall-2.5': 0.37606837606837606,\n", 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0.2222222222222222,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.14285714285714285,\n", " 'NDCG@all': 0.9116342301934282},\n", " 'CM': {'0': {'-1': 27, '0': 59, '1': 45, '2': 37, '3': 8, '4': 10, '5': 0},\n", " '1': {'-1': 5, '0': 9, '1': 13, '2': 46, '3': 14, '4': 12, '5': 1},\n", @@ -11182,12 +19369,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11700931332082935,\n", " 'Micro-F1': 0.14481409001956946,\n", - " 'F1-0': 0.09230769230769231,\n", - " 'F1-1': 0.0782122905027933,\n", - " 'F1-2': 0.14007782101167315,\n", - " 'F1-3': 0.2457627118644068,\n", - " 'F1-4': 0.1456953642384106,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.09230769230769231,\n", + " 'F1-1_vs_rest': 0.0782122905027933,\n", + " 'F1-2_vs_rest': 0.14007782101167315,\n", + " 'F1-3_vs_rest': 0.2457627118644068,\n", + " 'F1-4_vs_rest': 0.1456953642384106,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7859733978234583,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.647410358565737,\n", + " 'F1-1.5': 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'CA-2': 0.22641509433962265,\n", + " 'CA-3': 0.5096153846153846,\n", + " 'CA-4': 0.38461538461538464,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.3210747970945087,\n", + " 'Micro-F1': 0.3561643835616438,\n", + " 'F1-0_vs_rest': 0.5815602836879432,\n", + " 'F1-1_vs_rest': 0.18681318681318682,\n", + " 'F1-2_vs_rest': 0.22535211267605634,\n", + " 'F1-3_vs_rest': 0.4092664092664093,\n", + " 'F1-4_vs_rest': 0.12345679012345678,\n", + " 'F1-5_vs_rest': 0.4,\n", + " 'F1-0.5': 0.8405405405405405,\n", + " 'Recall-0.5': 0.9569230769230769,\n", + " 'Precision-0.5': 0.7493975903614458,\n", + " 'F1-1.5': 0.7491039426523297,\n", + " 'Recall-1.5': 0.9288888888888889,\n", + " 'Precision-1.5': 0.6276276276276276,\n", + " 'F1-2.5': 0.5507246376811594,\n", + " 'Recall-2.5': 0.7983193277310925,\n", + " 'Precision-2.5': 0.42035398230088494,\n", + " 'F1-3.5': 0.16279069767441862,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.09859154929577464,\n", + " 'F1-4.5': 0.4,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.3333333333333333,\n", + " 'NDCG@all': 0.8951987826784893},\n", + " 'CM': {'0': {'-1': 0, '0': 82, '1': 51, '2': 33, '3': 16, '4': 3, '5': 1},\n", + " '1': {'-1': 0, '0': 12, '1': 17, '2': 28, '3': 30, '4': 13, '5': 0},\n", + " '2': {'-1': 0, '0': 2, '1': 12, '2': 24, '3': 50, '4': 17, '5': 1},\n", + " '3': {'-1': 0, '0': 0, '1': 2, '2': 20, '3': 53, '4': 29, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 2, '3': 6, '4': 5, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.07412981139986374,\n", " 'Cohen': 0.1107121283307605,\n", " 'Spearman': 0.6146627719369416,\n", " 'Kendall': 0.5222468702918995,\n", @@ -11534,12 +20027,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.21724404386460908,\n", " 'Micro-F1': 0.2896281800391389,\n", - " 'F1-0': 0.273972602739726,\n", - " 'F1-1': 0.2413793103448276,\n", - " 'F1-2': 0.27615062761506276,\n", - " 'F1-3': 0.42105263157894735,\n", - " 'F1-4': 0.09090909090909091,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.273972602739726,\n", + " 'F1-1_vs_rest': 0.2413793103448276,\n", + " 'F1-2_vs_rest': 0.27615062761506276,\n", + " 'F1-3_vs_rest': 0.42105263157894735,\n", + " 'F1-4_vs_rest': 0.09090909090909091,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8019925280199253,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.6736401673640168,\n", + " 'F1-1.5': 0.7368421052631579,\n", + " 'Recall-1.5': 0.84,\n", + " 'Precision-1.5': 0.65625,\n", + " 'F1-2.5': 0.5474452554744526,\n", + " 'Recall-2.5': 0.6302521008403361,\n", + " 'Precision-2.5': 0.4838709677419355,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.12903225806451613,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8932327053771766},\n", " 'CM': {'0': {'-1': 0, '0': 30, '1': 120, '2': 26, '3': 6, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 35, '2': 41, '3': 15, '4': 7, '5': 0},\n", @@ -11566,12 +20074,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.2989483724314266,\n", " 'Micro-F1': 0.3835616438356164,\n", - " 'F1-0': 0.6232876712328768,\n", - " 'F1-1': 0.34146341463414637,\n", - " 'F1-2': 0.3626943005181347,\n", - " 'F1-3': 0.2484472049689441,\n", - " 'F1-4': 0.1308411214953271,\n", - " 'F1-5': 0.08695652173913043,\n", + " 'F1-0_vs_rest': 0.6232876712328768,\n", + " 'F1-1_vs_rest': 0.34146341463414637,\n", + " 'F1-2_vs_rest': 0.3626943005181347,\n", + " 'F1-3_vs_rest': 0.2484472049689441,\n", + " 'F1-4_vs_rest': 0.1308411214953271,\n", + " 'F1-5_vs_rest': 0.08695652173913043,\n", + " 'F1-0.5': 0.8493150684931506,\n", + " 'Recall-0.5': 0.9538461538461539,\n", + " 'Precision-0.5': 0.7654320987654321,\n", + " 'F1-1.5': 0.7851239669421488,\n", + " 'Recall-1.5': 0.8444444444444444,\n", + " 'Precision-1.5': 0.7335907335907336,\n", + " 'F1-2.5': 0.5979381443298969,\n", + " 'Recall-2.5': 0.7310924369747899,\n", + " 'Precision-2.5': 0.5058139534883721,\n", + " 'F1-3.5': 0.15384615384615385,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.08695652173913043,\n", + " 'F1-4.5': 0.08695652173913043,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.047619047619047616,\n", " 'NDCG@all': 0.8860287784968621},\n", " 'CM': {'0': {'-1': 0, '0': 91, '1': 72, '2': 10, '3': 4, '4': 6, '5': 3},\n", " '1': {'-1': 0, '0': 12, '1': 42, '2': 20, '3': 10, '4': 10, '5': 6},\n", @@ -11598,12 +20121,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2188292286399598,\n", " 'Micro-F1': 0.28180039138943247,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.24550898203592814,\n", - " 'F1-2': 0.3665338645418327,\n", - " 'F1-3': 0.4519230769230769,\n", - " 'F1-4': 0.17647058823529413,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.24550898203592814,\n", + " 'F1-2_vs_rest': 0.3665338645418327,\n", + " 'F1-3_vs_rest': 0.4519230769230769,\n", + " 'F1-4_vs_rest': 0.17647058823529413,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7555555555555555,\n", + " 'Recall-1.5': 0.8311111111111111,\n", + " 'Precision-1.5': 0.6925925925925925,\n", + " 'F1-2.5': 0.5409836065573771,\n", + " 'Recall-2.5': 0.5546218487394958,\n", + " 'Precision-2.5': 0.528,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.26666666666666666,\n", + " 'Precision-3.5': 0.19047619047619047,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9057903747202993},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 155, '2': 18, '3': 5, '4': 1, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 41, '2': 41, '3': 15, '4': 3, '5': 0},\n", @@ -11630,12 +20168,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2680990553709974,\n", " 'Micro-F1': 0.350293542074364,\n", - " 'F1-0': 0.5535055350553506,\n", - " 'F1-1': 0.288135593220339,\n", - " 'F1-2': 0.23115577889447236,\n", - " 'F1-3': 0.35023041474654376,\n", - " 'F1-4': 0.18556701030927836,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.5535055350553506,\n", + " 'F1-1_vs_rest': 0.288135593220339,\n", + " 'F1-2_vs_rest': 0.23115577889447236,\n", + " 'F1-3_vs_rest': 0.35023041474654376,\n", + " 'F1-4_vs_rest': 0.18556701030927836,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8388814913448736,\n", + " 'Recall-0.5': 0.9692307692307692,\n", + " 'Precision-0.5': 0.7394366197183099,\n", + " 'F1-1.5': 0.7533980582524272,\n", + " 'Recall-1.5': 0.8622222222222222,\n", + " 'Precision-1.5': 0.6689655172413793,\n", + " 'F1-2.5': 0.5886075949367089,\n", + " 'Recall-2.5': 0.7815126050420168,\n", + " 'Precision-2.5': 0.4720812182741117,\n", + " 'F1-3.5': 0.2222222222222222,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.13095238095238096,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9100456931352507},\n", " 'CM': {'0': {'-1': 0, '0': 75, '1': 76, '2': 23, '3': 8, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 5, '1': 34, '2': 30, '3': 21, '4': 10, '5': 0},\n", @@ -11662,12 +20215,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.08070138096448777,\n", " 'Micro-F1': 0.09784735812133072,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.09424083769633508,\n", - " 'F1-2': 0.12669683257918551,\n", - " 'F1-3': 0.14507772020725387,\n", - " 'F1-4': 0.09691629955947137,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.09424083769633508,\n", + " 'F1-2_vs_rest': 0.12669683257918551,\n", + " 'F1-3_vs_rest': 0.14507772020725387,\n", + " 'F1-4_vs_rest': 0.09691629955947137,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.6905132192846034,\n", + " 'Recall-1.5': 0.9866666666666667,\n", + " 'Precision-1.5': 0.5311004784688995,\n", + " 'F1-2.5': 0.5402843601895735,\n", + " 'Recall-2.5': 0.957983193277311,\n", + " 'Precision-2.5': 0.37623762376237624,\n", + " 'F1-3.5': 0.11353711790393013,\n", + " 'Recall-3.5': 0.8666666666666667,\n", + " 'Precision-3.5': 0.06074766355140187,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8924098522247583},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 79, '2': 65, '3': 26, '4': 14, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 9, '2': 32, '3': 20, '4': 39, '5': 0},\n", @@ -11694,12 +20262,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.13065054792377798,\n", " 'Micro-F1': 0.12915851272015655,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.07881773399014778,\n", - " 'F1-2': 0.11650485436893204,\n", - " 'F1-3': 0.25622775800711745,\n", - " 'F1-4': 0.1323529411764706,\n", - " 'F1-5': 0.2,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.07881773399014778,\n", + " 'F1-2_vs_rest': 0.11650485436893204,\n", + " 'F1-3_vs_rest': 0.25622775800711745,\n", + " 'F1-4_vs_rest': 0.1323529411764706,\n", + " 'F1-5_vs_rest': 0.2,\n", + " 'F1-0.5': 0.777511961722488,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6360078277886497,\n", + " 'F1-1.5': 0.7109004739336493,\n", + " 'Recall-1.5': 1.0,\n", + " 'Precision-1.5': 0.5514705882352942,\n", + " 'F1-2.5': 0.5386416861826698,\n", + " 'Recall-2.5': 0.9663865546218487,\n", + " 'Precision-2.5': 0.37337662337662336,\n", + " 'F1-3.5': 0.1506849315068493,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.08396946564885496,\n", + " 'F1-4.5': 0.2,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.125,\n", " 'NDCG@all': 0.9007962551338049},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 95, '2': 59, '3': 27, '4': 4, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 8, '2': 25, '3': 48, '4': 18, '5': 1},\n", @@ -11726,12 +20309,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2737334517644544,\n", " 'Micro-F1': 0.3679060665362035,\n", - " 'F1-0': 0.3684210526315789,\n", - " 'F1-1': 0.2753623188405797,\n", - " 'F1-2': 0.42066420664206644,\n", - " 'F1-3': 0.4803921568627451,\n", - " 'F1-4': 0.0975609756097561,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.3684210526315789,\n", + " 'F1-1_vs_rest': 0.2753623188405797,\n", + " 'F1-2_vs_rest': 0.42066420664206644,\n", + " 'F1-3_vs_rest': 0.4803921568627451,\n", + " 'F1-4_vs_rest': 0.0975609756097561,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.818639798488665,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6929637526652452,\n", + " 'F1-1.5': 0.7799227799227799,\n", + " 'Recall-1.5': 0.8977777777777778,\n", + " 'Precision-1.5': 0.689419795221843,\n", + " 'F1-2.5': 0.5991902834008097,\n", + " 'Recall-2.5': 0.6218487394957983,\n", + " 'Precision-2.5': 0.578125,\n", + " 'F1-3.5': 0.13953488372093023,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.10714285714285714,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9011334500371152},\n", " 'CM': {'0': {'-1': 0, '0': 42, '1': 115, '2': 20, '3': 5, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 38, '2': 47, '3': 12, '4': 3, '5': 0},\n", @@ -11758,12 +20356,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.1149243929848674,\n", " 'Micro-F1': 0.12101910828025478,\n", - " 'F1-0': 0.16363636363636364,\n", - " 'F1-1': 0.08421052631578947,\n", - " 'F1-2': 0.17054263565891473,\n", - " 'F1-3': 0.15625,\n", - " 'F1-4': 0.043478260869565216,\n", - " 'F1-5': 0.07142857142857142,\n", + " 'F1-0_vs_rest': 0.16363636363636364,\n", + " 'F1-1_vs_rest': 0.08421052631578947,\n", + " 'F1-2_vs_rest': 0.17054263565891473,\n", + " 'F1-3_vs_rest': 0.15625,\n", + " 'F1-4_vs_rest': 0.043478260869565216,\n", + " 'F1-5_vs_rest': 0.07142857142857142,\n", + " 'F1-0.5': 0.8223938223938224,\n", + " 'Recall-0.5': 0.9953271028037384,\n", + " 'Precision-0.5': 0.7006578947368421,\n", + " 'F1-1.5': 0.6761229314420804,\n", + " 'Recall-1.5': 0.9862068965517241,\n", + " 'Precision-1.5': 0.5143884892086331,\n", + " 'F1-2.5': 0.4557823129251701,\n", + " 'Recall-2.5': 0.9571428571428572,\n", + " 'Precision-2.5': 0.29910714285714285,\n", + " 'F1-3.5': 0.060240963855421686,\n", + " 'Recall-3.5': 0.625,\n", + " 'Precision-3.5': 0.03164556962025317,\n", + " 'F1-4.5': 0.07142857142857142,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.037037037037037035,\n", " 'NDCG@all': 0.8614673163399486},\n", " 'CM': {'0': {'-1': 86, '0': 9, '1': 21, '2': 29, '3': 18, '4': 20, '5': 3},\n", " '1': {'-1': 31, '0': 0, '1': 4, '2': 11, '3': 22, '4': 26, '5': 6},\n", @@ -11771,6 +20384,53 @@ " '3': {'-1': 42, '0': 0, '1': 0, '2': 3, '3': 10, '4': 44, '5': 5},\n", " '4': {'-1': 6, '0': 0, '1': 0, '2': 0, '3': 3, '4': 3, '5': 1},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10977857155780481,\n", + " 'Cohen': 0.14976770823561936,\n", + " 'Spearman': 0.6917277973997606,\n", + " 'Kendall': 0.5933981676558868,\n", + " 'Krippendorff': 0.5894470335935262,\n", + " 'Invalid': 3,\n", + " 'TA-2.0': 0.7460629921259843,\n", + " 'TA-4.0': 0.9645669291338582,\n", + " 'Acc': 0.33267716535433073,\n", + " 'MAE': 0.7867454068241466,\n", + " 'MSE': 1.0137795275590546,\n", + " 'CA-0': 0.23118279569892472,\n", + " 'CA-1': 0.27,\n", + " 'CA-2': 0.6095238095238096,\n", + " 'CA-3': 0.3431372549019608,\n", + " 'CA-4': 0.0,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.22534535111579812,\n", + " 'Micro-F1': 0.33267716535433073,\n", + " 'F1-0_vs_rest': 0.3722943722943723,\n", + " 'F1-1_vs_rest': 0.216,\n", + " 'F1-2_vs_rest': 0.39143730886850153,\n", + " 'F1-3_vs_rest': 0.3723404255319149,\n", + " 'F1-4_vs_rest': 0.0,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8152866242038217,\n", + " 'Recall-0.5': 0.9937888198757764,\n", + " 'Precision-0.5': 0.6911447084233261,\n", + " 'F1-1.5': 0.7813084112149533,\n", + " 'Recall-1.5': 0.9414414414414415,\n", + " 'Precision-1.5': 0.6677316293929713,\n", + " 'F1-2.5': 0.4519230769230769,\n", + " 'Recall-2.5': 0.4017094017094017,\n", + " 'Precision-2.5': 0.5164835164835165,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9131902355492657},\n", + " 'CM': {'0': {'-1': 0, '0': 43, '1': 110, '2': 30, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 2, '1': 27, '2': 59, '3': 12, '4': 0, '5': 0},\n", + " '2': {'-1': 1, '0': 0, '1': 12, '2': 64, '3': 27, '4': 2, '5': 0},\n", + " '3': {'-1': 2, '0': 0, '1': 1, '2': 64, '3': 35, '4': 2, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 5, '3': 8, '4': 0, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1582030460954228,\n", " 'Cohen': 0.17821285706236967,\n", " 'Spearman': 0.6440885184672338,\n", @@ -11790,12 +20450,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.3217082847716728,\n", " 'Micro-F1': 0.3368869936034115,\n", - " 'F1-0': 0.45414847161572053,\n", - " 'F1-1': 0.21839080459770116,\n", - " 'F1-2': 0.3967611336032389,\n", - " 'F1-3': 0.34444444444444444,\n", - " 'F1-4': 0.11650485436893204,\n", - " 'F1-5': 0.4,\n", + " 'F1-0_vs_rest': 0.45414847161572053,\n", + " 'F1-1_vs_rest': 0.21839080459770116,\n", + " 'F1-2_vs_rest': 0.3967611336032389,\n", + " 'F1-3_vs_rest': 0.34444444444444444,\n", + " 'F1-4_vs_rest': 0.11650485436893204,\n", + " 'F1-5_vs_rest': 0.4,\n", + " 'F1-0.5': 0.8236953455571228,\n", + " 'Recall-0.5': 0.9449838187702265,\n", + " 'Precision-0.5': 0.73,\n", + " 'F1-1.5': 0.7775700934579439,\n", + " 'Recall-1.5': 0.9541284403669725,\n", + " 'Precision-1.5': 0.6561514195583596,\n", + " 'F1-2.5': 0.6180555555555556,\n", + " 'Recall-2.5': 0.7606837606837606,\n", + " 'Precision-2.5': 0.52046783625731,\n", + " 'F1-3.5': 0.12962962962962962,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.07526881720430108,\n", + " 'F1-4.5': 0.4,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.3333333333333333,\n", " 'NDCG@all': 0.9131082016629367},\n", " 'CM': {'0': {'-1': 26, '0': 52, '1': 60, '2': 34, '3': 8, '4': 6, '5': 0},\n", " '1': {'-1': 9, '0': 11, '1': 19, '2': 37, '3': 14, '4': 10, '5': 0},\n", @@ -11822,12 +20497,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.11453604568914773,\n", " 'Micro-F1': 0.14481409001956946,\n", - " 'F1-0': 0.0625,\n", - " 'F1-1': 0.07526881720430108,\n", - " 'F1-2': 0.17120622568093385,\n", - " 'F1-3': 0.2643171806167401,\n", - " 'F1-4': 0.11392405063291139,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.0625,\n", + " 'F1-1_vs_rest': 0.07526881720430108,\n", + " 'F1-2_vs_rest': 0.17120622568093385,\n", + " 'F1-3_vs_rest': 0.2643171806167401,\n", + " 'F1-4_vs_rest': 0.11392405063291139,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7831325301204819,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6435643564356436,\n", + " 'F1-1.5': 0.6739130434782609,\n", + " 'Recall-1.5': 0.9644444444444444,\n", + " 'Precision-1.5': 0.5178997613365155,\n", + " 'F1-2.5': 0.5529715762273901,\n", + " 'Recall-2.5': 0.8991596638655462,\n", + " 'Precision-2.5': 0.39925373134328357,\n", + " 'F1-3.5': 0.1375,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07586206896551724,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8963811434793678},\n", " 'CM': {'0': {'-1': 0, '0': 6, '1': 71, '2': 77, '3': 23, '4': 9, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 7, '2': 41, '3': 31, '4': 21, '5': 0},\n", @@ -11835,327 +20525,618 @@ " '3': {'-1': 0, '0': 0, '1': 1, '2': 11, '3': 30, '4': 62, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'is': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.11094581305630496,\n", - " 'Cohen': 0.1429758976403216,\n", - " 'Spearman': 0.5462078623379812,\n", - " 'Kendall': 0.4656506138764044,\n", - " 'Krippendorff': 0.4812136451032175,\n", - " 'Invalid': 0,\n", - " 'TA-2.0': 0.684931506849315,\n", - " 'TA-4.0': 0.9530332681017613,\n", - " 'Acc': 0.324853228962818,\n", - " 'MAE': 0.878016960208741,\n", - " 'MSE': 1.3385518590998042,\n", - " 'CA-0': 0.22043010752688172,\n", + " 'is': {'phi-4': {'metrics': {'Fleiss': 0.24829906467303545,\n", + " 'Cohen': 0.25738329942118876,\n", + " 'Spearman': 0.6390398881697575,\n", + " 'Kendall': 0.5363582347296141,\n", + " 'Krippendorff': 0.5615008315951123,\n", + " 'Invalid': 0,\n", + " 'TA-2.0': 0.7244094488188977,\n", + " 'TA-4.0': 0.8917322834645669,\n", + " 'Acc': 0.41732283464566927,\n", + " 'MAE': 0.8618766404199475,\n", + " 'MSE': 1.5495953630796149,\n", + " 'CA-0': 0.4838709677419355,\n", + " 'CA-1': 0.26,\n", + " 'CA-2': 0.34285714285714286,\n", + " 'CA-3': 0.5392156862745098,\n", + " 'CA-4': 0.3076923076923077,\n", + " 'CA-5': 0.5,\n", + " 'Macro-F1': 0.35451096013680927,\n", + " 'Micro-F1': 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'1': 2, '2': 14, '3': 34, '4': 52, '5': 0},\n", " '4': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 4, '4': 9, '5': 0},\n", " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", - " 'en': {'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0717828968755195,\n", + " 'en': {'phi-4': {'metrics': {'Fleiss': 0.23993094797501208,\n", + " 'Cohen': 0.24896917337522073,\n", + " 'Spearman': 0.6342027470822779,\n", + " 'Kendall': 0.5249793452885182,\n", + " 'Krippendorff': 0.567784125276659,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7352941176470589,\n", + " 'TA-4.0': 0.8764705882352941,\n", + " 'Acc': 0.4117647058823529,\n", + " 'MAE': 0.8722222222222223,\n", + " 'MSE': 1.5833877995642702,\n", + " 'CA-0': 0.532258064516129,\n", + " 'CA-1': 0.26,\n", + " 'CA-2': 0.25471698113207547,\n", + " 'CA-3': 0.5192307692307693,\n", + " 'CA-4': 0.3333333333333333,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2899209842806652,\n", + " 'Micro-F1': 0.4117647058823529,\n", + " 'F1-0_vs_rest': 0.66,\n", + " 'F1-1_vs_rest': 0.2653061224489796,\n", + " 'F1-2_vs_rest': 0.27411167512690354,\n", + " 'F1-3_vs_rest': 0.432,\n", + " 'F1-4_vs_rest': 0.10810810810810811,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8583333333333333,\n", + " 'Recall-0.5': 0.9537037037037037,\n", + " 'Precision-0.5': 0.7803030303030303,\n", + " 'F1-1.5': 0.7557251908396947,\n", + " 'Recall-1.5': 0.8839285714285714,\n", + " 'Precision-1.5': 0.66,\n", + " 'F1-2.5': 0.5565749235474006,\n", + " 'Recall-2.5': 0.7711864406779662,\n", + " 'Precision-2.5': 0.4354066985645933,\n", + " 'F1-3.5': 0.15584415584415584,\n", + " 'Recall-3.5': 0.42857142857142855,\n", + " 'Precision-3.5': 0.09523809523809523,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.8839212119112304},\n", + " 'CM': {'0': {'-1': 0, '0': 99, '1': 48, '2': 23, '3': 10, '4': 6, '5': 0},\n", + " '1': {'-1': 0, '0': 11, '1': 26, '2': 21, '3': 29, '4': 12, '5': 1},\n", + " '2': {'-1': 0, '0': 4, '1': 15, '2': 27, '3': 47, '4': 13, '5': 0},\n", + " '3': {'-1': 0, '0': 0, '1': 7, '2': 18, '3': 54, '4': 25, '5': 0},\n", + " '4': {'-1': 1, '0': 0, '1': 0, '2': 2, '3': 6, '4': 4, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", + " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0717828968755195,\n", " 'Cohen': 0.11337713684330297,\n", " 'Spearman': 0.5936233242208634,\n", " 'Kendall': 0.5067679635083551,\n", @@ -12174,12 +21155,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.22438372816765248,\n", " 'Micro-F1': 0.2837573385518591,\n", - " 'F1-0': 0.20853080568720378,\n", - " 'F1-1': 0.23920265780730898,\n", - " 'F1-2': 0.3391304347826087,\n", - " 'F1-3': 0.39814814814814814,\n", - " 'F1-4': 0.16129032258064516,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.20853080568720378,\n", + " 'F1-1_vs_rest': 0.23920265780730898,\n", + " 'F1-2_vs_rest': 0.3391304347826087,\n", + " 'F1-3_vs_rest': 0.39814814814814814,\n", + " 'F1-4_vs_rest': 0.16129032258064516,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7940813810110974,\n", + " 'Recall-0.5': 0.9907692307692307,\n", + " 'Precision-0.5': 0.6625514403292181,\n", + " 'F1-1.5': 0.7294117647058823,\n", + " 'Recall-1.5': 0.8266666666666667,\n", + " 'Precision-1.5': 0.6526315789473685,\n", + " 'F1-2.5': 0.5785714285714286,\n", + " 'Recall-2.5': 0.680672268907563,\n", + " 'Precision-2.5': 0.5031055900621118,\n", + " 'F1-3.5': 0.21875,\n", + " 'Recall-3.5': 0.4666666666666667,\n", + " 'Precision-3.5': 0.14285714285714285,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.9022943820962006},\n", " 'CM': {'0': {'-1': 0, '0': 22, '1': 127, '2': 22, '3': 11, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 2, '1': 36, '2': 39, '3': 16, '4': 7, '5': 0},\n", @@ -12206,12 +21202,27 @@ " 'CA-5': 1.0,\n", " 'Macro-F1': 0.2864863922307459,\n", " 'Micro-F1': 0.3659491193737769,\n", - " 'F1-0': 0.6527777777777778,\n", - " 'F1-1': 0.34934497816593885,\n", - " 'F1-2': 0.328042328042328,\n", - " 'F1-3': 0.16774193548387098,\n", - " 'F1-4': 0.11290322580645161,\n", - " 'F1-5': 0.10810810810810811,\n", + " 'F1-0_vs_rest': 0.6527777777777778,\n", + " 'F1-1_vs_rest': 0.34934497816593885,\n", + " 'F1-2_vs_rest': 0.328042328042328,\n", + " 'F1-3_vs_rest': 0.16774193548387098,\n", + " 'F1-4_vs_rest': 0.11290322580645161,\n", + " 'F1-5_vs_rest': 0.10810810810810811,\n", + " 'F1-0.5': 0.8637602179836512,\n", + " 'Recall-0.5': 0.9753846153846154,\n", + " 'Precision-0.5': 0.7750611246943765,\n", + " 'F1-1.5': 0.7762376237623763,\n", + " 'Recall-1.5': 0.8711111111111111,\n", + " 'Precision-1.5': 0.7,\n", + " 'F1-2.5': 0.6329113924050633,\n", + " 'Recall-2.5': 0.8403361344537815,\n", + " 'Precision-2.5': 0.5076142131979695,\n", + " 'F1-3.5': 0.13664596273291926,\n", + " 'Recall-3.5': 0.7333333333333333,\n", + " 'Precision-3.5': 0.07534246575342465,\n", + " 'F1-4.5': 0.10810810810810811,\n", + " 'Recall-4.5': 1.0,\n", + " 'Precision-4.5': 0.05714285714285714,\n", " 'NDCG@all': 0.8974923026344537},\n", " 'CM': {'0': {'-1': 0, '0': 94, '1': 62, '2': 16, '3': 6, '4': 4, '5': 4},\n", " '1': {'-1': 0, '0': 6, '1': 40, '2': 25, '3': 7, '4': 15, '5': 7},\n", @@ -12238,12 +21249,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.20176038827083523,\n", " 'Micro-F1': 0.2876712328767123,\n", - " 'F1-0': 0.07253886010362694,\n", - " 'F1-1': 0.2445141065830721,\n", - " 'F1-2': 0.30837004405286345,\n", - " 'F1-3': 0.5263157894736842,\n", - " 'F1-4': 0.058823529411764705,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.07253886010362694,\n", + " 'F1-1_vs_rest': 0.2445141065830721,\n", + " 'F1-2_vs_rest': 0.30837004405286345,\n", + " 'F1-3_vs_rest': 0.5263157894736842,\n", + " 'F1-4_vs_rest': 0.058823529411764705,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7840772014475271,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6448412698412699,\n", + " 'F1-1.5': 0.7647058823529411,\n", + " 'Recall-1.5': 0.8666666666666667,\n", + " 'Precision-1.5': 0.6842105263157895,\n", + " 'F1-2.5': 0.6148409893992933,\n", + " 'Recall-2.5': 0.7310924369747899,\n", + " 'Precision-2.5': 0.5304878048780488,\n", + " 'F1-3.5': 0.1111111111111111,\n", + " 'Recall-3.5': 0.13333333333333333,\n", + " 'Precision-3.5': 0.09523809523809523,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8960171839458505},\n", " 'CM': {'0': {'-1': 0, '0': 7, '1': 150, '2': 21, '3': 4, '4': 4, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 39, '2': 38, '3': 21, '4': 2, '5': 0},\n", @@ -12270,12 +21296,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.27362861265717014,\n", " 'Micro-F1': 0.37377690802348335,\n", - " 'F1-0': 0.6262626262626263,\n", - " 'F1-1': 0.34024896265560167,\n", - " 'F1-2': 0.26737967914438504,\n", - " 'F1-3': 0.26373626373626374,\n", - " 'F1-4': 0.14414414414414414,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.6262626262626263,\n", + " 'F1-1_vs_rest': 0.34024896265560167,\n", + " 'F1-2_vs_rest': 0.26737967914438504,\n", + " 'F1-3_vs_rest': 0.26373626373626374,\n", + " 'F1-4_vs_rest': 0.14414414414414414,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8468965517241379,\n", + " 'Recall-0.5': 0.9446153846153846,\n", + " 'Precision-0.5': 0.7675,\n", + " 'F1-1.5': 0.7396694214876033,\n", + " 'Recall-1.5': 0.7955555555555556,\n", + " 'Precision-1.5': 0.6911196911196911,\n", + " 'F1-2.5': 0.6060606060606061,\n", + " 'Recall-2.5': 0.7563025210084033,\n", + " 'Precision-2.5': 0.5056179775280899,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.1,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8869894075669653},\n", " 'CM': {'0': {'-1': 0, '0': 93, '1': 64, '2': 18, '3': 6, '4': 4, '5': 1},\n", " '1': {'-1': 0, '0': 8, '1': 41, '2': 23, '3': 15, '4': 12, '5': 1},\n", @@ -12302,12 +21343,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.12015691254373674,\n", " 'Micro-F1': 0.1506849315068493,\n", - " 'F1-0': 0.02127659574468085,\n", - " 'F1-1': 0.11607142857142858,\n", - " 'F1-2': 0.2591093117408907,\n", - " 'F1-3': 0.23036649214659685,\n", - " 'F1-4': 0.09411764705882353,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.02127659574468085,\n", + " 'F1-1_vs_rest': 0.11607142857142858,\n", + " 'F1-2_vs_rest': 0.2591093117408907,\n", + " 'F1-3_vs_rest': 0.23036649214659685,\n", + " 'F1-4_vs_rest': 0.09411764705882353,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7793764988009593,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6385068762278978,\n", + " 'F1-1.5': 0.7180327868852459,\n", + " 'Recall-1.5': 0.9733333333333334,\n", + " 'Precision-1.5': 0.5688311688311688,\n", + " 'F1-2.5': 0.5785123966942148,\n", + " 'Recall-2.5': 0.8823529411764706,\n", + " 'Precision-2.5': 0.430327868852459,\n", + " 'F1-3.5': 0.11627906976744186,\n", + " 'Recall-3.5': 0.6666666666666666,\n", + " 'Precision-3.5': 0.06369426751592357,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.897278426639461},\n", " 'CM': {'0': {'-1': 0, '0': 2, '1': 105, '2': 54, '3': 15, '4': 10, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 13, '2': 42, '3': 21, '4': 24, '5': 0},\n", @@ -12334,12 +21390,27 @@ " 'CA-5': 0.5,\n", " 'Macro-F1': 0.12763890893645932,\n", " 'Micro-F1': 0.13333333333333333,\n", - " 'F1-0': 0.0,\n", - " 'F1-1': 0.08121827411167512,\n", - " 'F1-2': 0.12807881773399016,\n", - " 'F1-3': 0.27177700348432055,\n", - " 'F1-4': 0.10294117647058823,\n", - " 'F1-5': 0.18181818181818182,\n", + " 'F1-0_vs_rest': 0.0,\n", + " 'F1-1_vs_rest': 0.08121827411167512,\n", + " 'F1-2_vs_rest': 0.12807881773399016,\n", + " 'F1-3_vs_rest': 0.27177700348432055,\n", + " 'F1-4_vs_rest': 0.10294117647058823,\n", + " 'F1-5_vs_rest': 0.18181818181818182,\n", + " 'F1-0.5': 0.7769784172661871,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6352941176470588,\n", + " 'F1-1.5': 0.7001569858712716,\n", + " 'Recall-1.5': 0.9911111111111112,\n", + " 'Precision-1.5': 0.5412621359223301,\n", + " 'F1-2.5': 0.543778801843318,\n", + " 'Recall-2.5': 0.9915966386554622,\n", + " 'Precision-2.5': 0.3746031746031746,\n", + " 'F1-3.5': 0.12244897959183673,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.06818181818181818,\n", + " 'F1-4.5': 0.18181818181818182,\n", + " 'Recall-4.5': 0.5,\n", + " 'Precision-4.5': 0.1111111111111111,\n", " 'NDCG@all': 0.8964794133440245},\n", " 'CM': {'0': {'-1': 0, '0': 0, '1': 88, '2': 62, '3': 31, '4': 4, '5': 1},\n", " '1': {'-1': 1, '0': 0, '1': 8, '2': 22, '3': 50, '4': 17, '5': 2},\n", @@ -12366,12 +21437,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.2863413518106297,\n", " 'Micro-F1': 0.38747553816046965,\n", - " 'F1-0': 0.41025641025641024,\n", - " 'F1-1': 0.30711610486891383,\n", - " 'F1-2': 0.4253731343283582,\n", - " 'F1-3': 0.49019607843137253,\n", - " 'F1-4': 0.0851063829787234,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.41025641025641024,\n", + " 'F1-1_vs_rest': 0.30711610486891383,\n", + " 'F1-2_vs_rest': 0.4253731343283582,\n", + " 'F1-3_vs_rest': 0.49019607843137253,\n", + " 'F1-4_vs_rest': 0.0851063829787234,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8248730964467005,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.7019438444924406,\n", + " 'F1-1.5': 0.7869481765834933,\n", + " 'Recall-1.5': 0.9111111111111111,\n", + " 'Precision-1.5': 0.6925675675675675,\n", + " 'F1-2.5': 0.5928853754940712,\n", + " 'Recall-2.5': 0.6302521008403361,\n", + " 'Precision-2.5': 0.5597014925373134,\n", + " 'F1-3.5': 0.12244897959183673,\n", + " 'Recall-3.5': 0.2,\n", + " 'Precision-3.5': 0.08823529411764706,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8963016134450722},\n", " 'CM': {'0': {'-1': 0, '0': 48, '1': 106, '2': 26, '3': 1, '4': 5, '5': 0},\n", " '1': {'-1': 0, '0': 0, '1': 41, '2': 39, '3': 15, '4': 5, '5': 0},\n", @@ -12398,12 +21484,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.15272123502026536,\n", " 'Micro-F1': 0.1939799331103679,\n", - " 'F1-0': 0.28776978417266186,\n", - " 'F1-1': 0.14285714285714285,\n", - " 'F1-2': 0.2222222222222222,\n", - " 'F1-3': 0.22,\n", - " 'F1-4': 0.043478260869565216,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.28776978417266186,\n", + " 'F1-1_vs_rest': 0.14285714285714285,\n", + " 'F1-2_vs_rest': 0.2222222222222222,\n", + " 'F1-3_vs_rest': 0.22,\n", + " 'F1-4_vs_rest': 0.043478260869565216,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7843137254901961,\n", + " 'Recall-0.5': 0.989010989010989,\n", + " 'Precision-0.5': 0.6498194945848376,\n", + " 'F1-1.5': 0.6537396121883656,\n", + " 'Recall-1.5': 0.9672131147540983,\n", + " 'Precision-1.5': 0.49372384937238495,\n", + " 'F1-2.5': 0.4723618090452261,\n", + " 'Recall-2.5': 0.7966101694915254,\n", + " 'Precision-2.5': 0.3357142857142857,\n", + " 'F1-3.5': 0.06060606060606061,\n", + " 'Recall-3.5': 0.5,\n", + " 'Precision-3.5': 0.03225806451612903,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8499529631689791},\n", " 'CM': {'0': {'-1': 69, '0': 20, '1': 29, '2': 46, '3': 9, '4': 12, '5': 1},\n", " '1': {'-1': 40, '0': 0, '1': 7, '2': 23, '3': 9, '4': 19, '5': 2},\n", @@ -12411,6 +21512,53 @@ " '3': {'-1': 51, '0': 0, '1': 0, '2': 10, '3': 11, '4': 29, '5': 3},\n", " '4': {'-1': 8, '0': 0, '1': 0, '2': 2, '3': 1, '4': 2, '5': 0},\n", " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", + " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.16980417350263502,\n", + " 'Cohen': 0.20283123202831232,\n", + " 'Spearman': 0.6927573544729271,\n", + " 'Kendall': 0.59414305625388,\n", + " 'Krippendorff': 0.6197253239511314,\n", + " 'Invalid': 1,\n", + " 'TA-2.0': 0.7725490196078432,\n", + " 'TA-4.0': 0.9647058823529412,\n", + " 'Acc': 0.3764705882352941,\n", + " 'MAE': 0.7424836601307186,\n", + " 'MSE': 0.9577342047930282,\n", + " 'CA-0': 0.26881720430107525,\n", + " 'CA-1': 0.39,\n", + " 'CA-2': 0.5943396226415094,\n", + " 'CA-3': 0.3786407766990291,\n", + " 'CA-4': 0.07692307692307693,\n", + " 'CA-5': 0.0,\n", + " 'Macro-F1': 0.2759384652694677,\n", + " 'Micro-F1': 0.3764705882352941,\n", + " 'F1-0_vs_rest': 0.4166666666666667,\n", + " 'F1-1_vs_rest': 0.2878228782287823,\n", + " 'F1-2_vs_rest': 0.4090909090909091,\n", + " 'F1-3_vs_rest': 0.430939226519337,\n", + " 'F1-4_vs_rest': 0.1111111111111111,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8205128205128205,\n", + " 'Recall-0.5': 0.9876543209876543,\n", + " 'Precision-0.5': 0.7017543859649122,\n", + " 'F1-1.5': 0.7897838899803536,\n", + " 'Recall-1.5': 0.8973214285714286,\n", + " 'Precision-1.5': 0.7052631578947368,\n", + " 'F1-2.5': 0.47761194029850745,\n", + " 'Recall-2.5': 0.4067796610169492,\n", + " 'Precision-2.5': 0.5783132530120482,\n", + " 'F1-3.5': 0.1,\n", + " 'Recall-3.5': 0.06666666666666667,\n", + " 'Precision-3.5': 0.2,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", + " 'NDCG@all': 0.9045518572460287},\n", + " 'CM': {'0': {'-1': 0, '0': 50, '1': 110, '2': 23, '3': 3, '4': 0, '5': 0},\n", + " '1': {'-1': 0, '0': 3, '1': 39, '2': 49, '3': 8, '4': 1, '5': 0},\n", + " '2': {'-1': 0, '0': 1, '1': 19, '2': 63, '3': 21, '4': 2, '5': 0},\n", + " '3': {'-1': 1, '0': 0, '1': 3, '2': 60, '3': 39, '4': 1, '5': 0},\n", + " '4': {'-1': 0, '0': 0, '1': 0, '2': 7, '3': 5, '4': 1, '5': 0},\n", + " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.14013325530803808,\n", " 'Cohen': 0.16073642259264187,\n", " 'Spearman': 0.6592540559697546,\n", @@ -12430,12 +21578,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.24914790780184184,\n", " 'Micro-F1': 0.3231707317073171,\n", - " 'F1-0': 0.4819277108433735,\n", - " 'F1-1': 0.22,\n", - " 'F1-2': 0.32231404958677684,\n", - " 'F1-3': 0.3263157894736842,\n", - " 'F1-4': 0.14432989690721648,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.4819277108433735,\n", + " 'F1-1_vs_rest': 0.22,\n", + " 'F1-2_vs_rest': 0.32231404958677684,\n", + " 'F1-3_vs_rest': 0.3263157894736842,\n", + " 'F1-4_vs_rest': 0.14432989690721648,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.8244897959183674,\n", + " 'Recall-0.5': 0.9680511182108626,\n", + " 'Precision-0.5': 0.7180094786729858,\n", + " 'F1-1.5': 0.7476635514018691,\n", + " 'Recall-1.5': 0.91324200913242,\n", + " 'Precision-1.5': 0.6329113924050633,\n", + " 'F1-2.5': 0.621160409556314,\n", + " 'Recall-2.5': 0.7777777777777778,\n", + " 'Precision-2.5': 0.5170454545454546,\n", + " 'F1-3.5': 0.17475728155339806,\n", + " 'Recall-3.5': 0.6,\n", + " 'Precision-3.5': 0.10227272727272728,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8989956000238616},\n", " 'CM': {'0': {'-1': 7, '0': 60, '1': 67, '2': 38, '3': 9, '4': 4, '5': 1},\n", " '1': {'-1': 6, '0': 8, '1': 22, '2': 43, '3': 11, '4': 9, '5': 1},\n", @@ -12462,12 +21625,27 @@ " 'CA-5': 0.0,\n", " 'Macro-F1': 0.14251999089643083,\n", " 'Micro-F1': 0.17416829745596868,\n", - " 'F1-0': 0.12121212121212122,\n", - " 'F1-1': 0.12149532710280374,\n", - " 'F1-2': 0.18181818181818182,\n", - " 'F1-3': 0.27555555555555555,\n", - " 'F1-4': 0.15503875968992248,\n", - " 'F1-5': 0.0,\n", + " 'F1-0_vs_rest': 0.12121212121212122,\n", + " 'F1-1_vs_rest': 0.12149532710280374,\n", + " 'F1-2_vs_rest': 0.18181818181818182,\n", + " 'F1-3_vs_rest': 0.27555555555555555,\n", + " 'F1-4_vs_rest': 0.15503875968992248,\n", + " 'F1-5_vs_rest': 0.0,\n", + " 'F1-0.5': 0.7888349514563107,\n", + " 'Recall-0.5': 1.0,\n", + " 'Precision-0.5': 0.6513026052104208,\n", + " 'F1-1.5': 0.6885245901639344,\n", + " 'Recall-1.5': 0.9333333333333333,\n", + " 'Precision-1.5': 0.5454545454545454,\n", + " 'F1-2.5': 0.5602240896358543,\n", + " 'Recall-2.5': 0.8403361344537815,\n", + " 'Precision-2.5': 0.42016806722689076,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'Recall-3.5': 0.8,\n", + " 'Precision-3.5': 0.10256410256410256,\n", + " 'F1-4.5': 0.0,\n", + " 'Recall-4.5': 0.0,\n", + " 'Precision-4.5': 0.0,\n", " 'NDCG@all': 0.8871628544616091},\n", " 'CM': {'0': {'-1': 0, '0': 12, '1': 86, '2': 62, '3': 20, '4': 5, '5': 1},\n", " '1': {'-1': 0, '0': 0, '1': 13, '2': 47, '3': 26, '4': 14, '5': 0},\n", @@ -12477,7 +21655,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}}}" ] }, - "execution_count": 78, + "execution_count": 93, "metadata": {}, "output_type": "execute_result" } @@ -12498,137 +21676,505 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 107, "id": "773163e1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'fi': {'Qwen2.5-14B-Instruct': 0.8868469034419542,\n", - " 'Llama-3.3-70B-Instruct': 0.8822406658180483,\n", - " 'gemma-2-27b-it': 0.8924107902654057,\n", - " 'Qwen2.5-32B-Instruct': 0.9113634731999892,\n", - " 'Qwen2.5-7B-Instruct': 0.89194524734931,\n", - " 'gemma-3-27b-it': 0.901604515831509,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8987635078006797,\n", - " 'Llama-3.2-3B-Instruct': 0.8257871100756643,\n", - " 'Llama-3.1-8B-Instruct': 0.9127026234342277,\n", - " 'Qwen2.5-72B-Instruct': 0.8849307457920452},\n", - " 'el': {'Qwen2.5-14B-Instruct': 0.8785970432710287,\n", - " 'Llama-3.3-70B-Instruct': 0.8917784896472812,\n", - " 'gemma-2-27b-it': 0.8975557679616587,\n", - " 'Qwen2.5-32B-Instruct': 0.9145076761966459,\n", - " 'Qwen2.5-7B-Instruct': 0.8884000858698269,\n", - " 'gemma-3-27b-it': 0.9090243751659209,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.9027732523608726,\n", - " 'Llama-3.2-3B-Instruct': 0.8384485864026487,\n", - " 'Llama-3.1-8B-Instruct': 0.9027368881716582,\n", - " 'Qwen2.5-72B-Instruct': 0.876186125820189},\n", - " 'pl': {'Qwen2.5-14B-Instruct': 0.8915379457181469,\n", - " 'Llama-3.3-70B-Instruct': 0.893028125368284,\n", - " 'gemma-2-27b-it': 0.9062881539149782,\n", - " 'Qwen2.5-32B-Instruct': 0.8845149553825653,\n", - " 'Qwen2.5-7B-Instruct': 0.885901770953761,\n", - " 'gemma-3-27b-it': 0.9018338533995509,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.9026522574185668,\n", - " 'Llama-3.2-3B-Instruct': 0.8339288289090923,\n", - " 'Llama-3.1-8B-Instruct': 0.914083301360287,\n", - " 'Qwen2.5-72B-Instruct': 0.8816677522551835},\n", - " 'es': {'Qwen2.5-14B-Instruct': 0.890918266071231,\n", - " 'Llama-3.3-70B-Instruct': 0.892492436917667,\n", - " 'gemma-2-27b-it': 0.9034092500125896,\n", - " 'Qwen2.5-32B-Instruct': 0.9027848177718728,\n", - " 'Qwen2.5-7B-Instruct': 0.8902914405546271,\n", - " 'gemma-3-27b-it': 0.8939431282681429,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8998704265053911,\n", - " 'Llama-3.2-3B-Instruct': 0.8523634509050897,\n", - " 'Llama-3.1-8B-Instruct': 0.9074997802988962,\n", - " 'Qwen2.5-72B-Instruct': 0.8957959135574456},\n", - " 'fr': {'Qwen2.5-14B-Instruct': 0.898344917756121,\n", - " 'Llama-3.3-70B-Instruct': 0.8934492839155558,\n", - " 'gemma-2-27b-it': 0.9001173990478823,\n", - " 'Qwen2.5-32B-Instruct': 0.9048978448480057,\n", - " 'Qwen2.5-7B-Instruct': 0.8841606882232718,\n", - " 'gemma-3-27b-it': 0.8943926676385515,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8965302081569092,\n", - " 'Llama-3.2-3B-Instruct': 0.8356932100976866,\n", - " 'Llama-3.1-8B-Instruct': 0.8985141342922355,\n", - " 'Qwen2.5-72B-Instruct': 0.8955451032568394},\n", - " 'it': {'Qwen2.5-14B-Instruct': 0.8913863623277738,\n", - " 'Llama-3.3-70B-Instruct': 0.8892769479381065,\n", - " 'gemma-2-27b-it': 0.8918213317029476,\n", - " 'Qwen2.5-32B-Instruct': 0.8949908435847219,\n", - " 'Qwen2.5-7B-Instruct': 0.8876000718308812,\n", - " 'gemma-3-27b-it': 0.9095851845950752,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.8911118391489357,\n", - " 'Llama-3.2-3B-Instruct': 0.8822217327335828,\n", - " 'Llama-3.1-8B-Instruct': 0.9122718348963341,\n", - " 'Qwen2.5-72B-Instruct': 0.8963504900865995},\n", - " 'lt': {'Qwen2.5-14B-Instruct': 0.8861634817796046,\n", - " 'Llama-3.3-70B-Instruct': 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0.12154148607725428},\n", + " 'gl': {'phi-4': 0.28001121090705494,\n", + " 'Qwen2.5-14B-Instruct': 0.22422030795855083,\n", + " 'Llama-3.3-70B-Instruct': 0.293054814961604,\n", + " 'gemma-2-27b-it': 0.201051725712472,\n", + " 'Qwen2.5-32B-Instruct': 0.2361273666408513,\n", + " 'Qwen2.5-7B-Instruct': 0.1139626201433619,\n", + " 'gemma-3-27b-it': 0.14477607535212306,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2879230737406883,\n", + " 'Llama-3.2-3B-Instruct': 0.10864236292948688,\n", + " 'gemma-2-9b-it': 0.2604056542601576,\n", + " 'Llama-3.1-8B-Instruct': 0.25760201939910604,\n", + " 'Qwen2.5-72B-Instruct': 0.09639161209854308},\n", + " 'sl': {'phi-4': 0.27171296050675764,\n", + " 'Qwen2.5-14B-Instruct': 0.24068088441041904,\n", + " 'Llama-3.3-70B-Instruct': 0.30844814607058546,\n", + " 'gemma-2-27b-it': 0.2068102362258902,\n", + " 'Qwen2.5-32B-Instruct': 0.23544358228152695,\n", + " 'Qwen2.5-7B-Instruct': 0.07151759560630216,\n", + " 'gemma-3-27b-it': 0.11561027488679225,\n", + " 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'gemma-2-9b-it': 0.22524278966178923,\n", + " 'Llama-3.1-8B-Instruct': 0.26828996963942003,\n", + " 'Qwen2.5-72B-Instruct': 0.11700931332082935},\n", + " 'ca': {'phi-4': 0.26092045960680554,\n", + " 'Qwen2.5-14B-Instruct': 0.22435865342074449,\n", + " 'Llama-3.3-70B-Instruct': 0.2832578382292304,\n", + " 'gemma-2-27b-it': 0.20572658286122855,\n", + " 'Qwen2.5-32B-Instruct': 0.2230007386483753,\n", + " 'Qwen2.5-7B-Instruct': 0.09107473464631959,\n", + " 'gemma-3-27b-it': 0.0931241427397906,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2702389053218473,\n", + " 'Llama-3.2-3B-Instruct': 0.13516406766369643,\n", + " 'gemma-2-9b-it': 0.2402508453816865,\n", + " 'Llama-3.1-8B-Instruct': 0.289310681638192,\n", + " 'Qwen2.5-72B-Instruct': 0.11399243010591316},\n", + " 'sk': {'phi-4': 0.3210747970945087,\n", + " 'Qwen2.5-14B-Instruct': 0.21724404386460908,\n", + " 'Llama-3.3-70B-Instruct': 0.2989483724314266,\n", + " 'gemma-2-27b-it': 0.2188292286399598,\n", + " 'Qwen2.5-32B-Instruct': 0.2680990553709974,\n", + " 'Qwen2.5-7B-Instruct': 0.08070138096448777,\n", + " 'gemma-3-27b-it': 0.13065054792377798,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2737334517644544,\n", + " 'Llama-3.2-3B-Instruct': 0.1149243929848674,\n", + " 'gemma-2-9b-it': 0.22534535111579812,\n", + " 'Llama-3.1-8B-Instruct': 0.3217082847716728,\n", + " 'Qwen2.5-72B-Instruct': 0.11453604568914773},\n", + " 'is': {'phi-4': 0.35451096013680927,\n", + " 'Qwen2.5-14B-Instruct': 0.24205096762628395,\n", + " 'Llama-3.3-70B-Instruct': 0.3151442381112823,\n", + " 'gemma-2-27b-it': 0.1987732386552065,\n", + " 'Qwen2.5-32B-Instruct': 0.2750495164280974,\n", + " 'Qwen2.5-7B-Instruct': 0.09419616026329813,\n", + " 'gemma-3-27b-it': 0.10163175772242682,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.276280251981111,\n", + " 'Llama-3.2-3B-Instruct': 0.06862619745162082,\n", + " 'gemma-2-9b-it': 0.2317110093557769,\n", + " 'Llama-3.1-8B-Instruct': 0.21963916205612297,\n", + " 'Qwen2.5-72B-Instruct': 0.13227197060848417},\n", + " 'en': {'phi-4': 0.2899209842806652,\n", + " 'Qwen2.5-14B-Instruct': 0.22438372816765248,\n", + " 'Llama-3.3-70B-Instruct': 0.2864863922307459,\n", + " 'gemma-2-27b-it': 0.20176038827083523,\n", + " 'Qwen2.5-32B-Instruct': 0.27362861265717014,\n", + " 'Qwen2.5-7B-Instruct': 0.12015691254373674,\n", + " 'gemma-3-27b-it': 0.12763890893645932,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2863413518106297,\n", + " 'Llama-3.2-3B-Instruct': 0.15272123502026536,\n", + " 'gemma-2-9b-it': 0.2759384652694677,\n", + " 'Llama-3.1-8B-Instruct': 0.24914790780184184,\n", + " 'Qwen2.5-72B-Instruct': 0.14251999089643083}}" ] }, - "execution_count": 79, + "execution_count": 107, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "metric_name = \"NDCG@all\"\n", + "metric_name = \"Macro-F1\" # \"Macro-F1\" # \"Spearman\" # \"Macro-F1\" # \"Spearman\" # \"NDCG@all\"\n", "\n", - "metric_results = {lang: {model: subsubresult[\"metrics\"][metric_name] for model, subsubresult in subresult.items()} for lang,subresult in results_complete.items() if lang in language_codes.keys()}\n", + "metric_results = {lang: {model: subsubresult[\"metrics\"][metric_name] for model, subsubresult in subresult.items()} for lang,subresult in results_complete.items()}\n", "metric_results" ] }, { "cell_type": "code", - "execution_count": 80, + "execution_count": null, "id": "60f8ea85", "metadata": {}, "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 108, + "id": "6ce47470", + "metadata": {}, + "outputs": [], "source": [ "metric_df = pd.DataFrame.from_dict(metric_results)\n", - "metric_df[\"avg\"] = metric_df.mean(axis=1)" + "num_languages = len(metric_df.columns)\n", + "\n", + "\n", + "avg_37 = metric_df.mean(axis=1)\n", + "metric_df = metric_df[list(language_codes.keys())]\n", + "metric_df[\"avg-10\"] = metric_df.mean(axis=1)\n", + "metric_df[\"avg-37\"] = avg_37" ] }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 109, "id": "e9caf110", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -12641,7 +22187,7 @@ "\n", "plt.figure(figsize=(12, 6))\n", "metric_df = metric_df.sort_index() \n", - "ax = sns.heatmap(metric_df, annot=False, fmt=\".3f\", cmap=\"viridis\", linewidths=0.5, cbar=True)\n", + "ax = sns.heatmap(metric_df, annot=False, fmt=\".3f\", cmap=\"Blues_r\", linewidths=0.5, cbar=True)\n", "\n", "# Add text annotations with bold max values\n", "for i, model in enumerate(metric_df.index):\n", @@ -12653,30 +22199,1189 @@ " ha='center', va='center', color='black', fontsize=9, fontweight=weight)\n", "\n", "# Final touches\n", - "plt.title(f\"{metric_name}\")\n", + "# plt.title(f\"{metric_name}\")\n", "# plt.ylabel(\"Model\")\n", "# plt.xlabel(\"Language\")\n", "plt.xticks(ticks=np.arange(len(metric_df.columns)) + 0.5, labels=metric_df.columns, rotation=45)\n", "plt.yticks(ticks=np.arange(len(metric_df.index)) + 0.5, labels=metric_df.index, rotation=0)\n", "plt.tight_layout()\n", + "\n", + "plt.savefig(plot_path / f\"llm_annotator_performance_{metric_name}.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", + "\n", + "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, + "id": "bea96db3", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 21, "id": "6d7739ea", "metadata": {}, "outputs": [], + "source": [ + "# TODO add avg column for 37 languages" + ] + }, + { + "cell_type": "markdown", + "id": "e594db53", + "metadata": {}, + "source": [ + "### {F1, Recall, Precision}@threshold" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "a7766cf9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'fi': {'phi-4': {'F1-0.5': 0.8406961178045516,\n", + " 'F1-1.5': 0.7518248175182481,\n", + " 'F1-2.5': 0.5722543352601156,\n", + " 'F1-3.5': 0.15053763440860216,\n", + " 'F1-4.5': 0.2857142857142857},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': 0.7985074626865671,\n", + " 'F1-1.5': 0.7368421052631579,\n", + " 'F1-2.5': 0.4980544747081712,\n", + " 'F1-3.5': 0.13636363636363635,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': 0.860655737704918,\n", + " 'F1-1.5': 0.7895791583166333,\n", + " 'F1-2.5': 0.6163934426229508,\n", + " 'F1-3.5': 0.16923076923076924,\n", + " 'F1-4.5': 0.08},\n", + " 'gemma-2-27b-it': {'F1-0.5': 0.7840772014475271,\n", + " 'F1-1.5': 0.7428571428571429,\n", + " 'F1-2.5': 0.5523012552301255,\n", + " 'F1-3.5': 0.12121212121212122,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-32B-Instruct': {'F1-0.5': 0.8284960422163589,\n", + " 'F1-1.5': 0.7265625,\n", + " 'F1-2.5': 0.5893416927899686,\n", + " 'F1-3.5': 0.1864406779661017,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-7B-Instruct': {'F1-0.5': 0.7784431137724551,\n", + " 'F1-1.5': 0.6748466257668712,\n", + " 'F1-2.5': 0.5503685503685504,\n", + " 'F1-3.5': 0.10377358490566038,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-3-27b-it': {'F1-0.5': 0.7764423076923077,\n", + " 'F1-1.5': 0.7012578616352201,\n", + " 'F1-2.5': 0.5463182897862233,\n", + " 'F1-3.5': 0.136986301369863,\n", + " 'F1-4.5': 0.25},\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': {'F1-0.5': 0.8155583437892095,\n", + " 'F1-1.5': 0.7775628626692457,\n", + " 'F1-2.5': 0.6050420168067226,\n", + " 'F1-3.5': 0.0851063829787234,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.2-3B-Instruct': {'F1-0.5': 0.7835616438356164,\n", + " 'F1-1.5': 0.6319218241042345,\n", + " 'F1-2.5': 0.47572815533980584,\n", + " 'F1-3.5': 0.06382978723404255,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-2-9b-it': {'F1-0.5': 0.8055207026348808,\n", + " 'F1-1.5': 0.7741935483870968,\n", + " 'F1-2.5': 0.4433497536945813,\n", + " 'F1-3.5': 0.14814814814814814,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': 0.8107344632768362,\n", + " 'F1-1.5': 0.7537878787878788,\n", + " 'F1-2.5': 0.6148409893992933,\n", + " 'F1-3.5': 0.11428571428571428,\n", + " 'F1-4.5': 0.25},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': 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'Llama-3.2-3B-Instruct': {'F1-0.5': 0.8076923076923077,\n", + " 'F1-1.5': 0.6825396825396826,\n", + " 'F1-2.5': 0.5278810408921933,\n", + " 'F1-3.5': 0.12121212121212122,\n", + " 'F1-4.5': 0.06896551724137931},\n", + " 'gemma-2-9b-it': {'F1-0.5': 0.8090452261306532,\n", + " 'F1-1.5': 0.7734806629834254,\n", + " 'F1-2.5': 0.42718446601941745,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': 0.8196286472148541,\n", + " 'F1-1.5': 0.75177304964539,\n", + " 'F1-2.5': 0.6410256410256411,\n", + " 'F1-3.5': 0.12030075187969924,\n", + " 'F1-4.5': 0.2},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': 0.7831325301204819,\n", + " 'F1-1.5': 0.6635802469135802,\n", + " 'F1-2.5': 0.5614035087719298,\n", + " 'F1-3.5': 0.14965986394557823,\n", + " 'F1-4.5': 0.0}},\n", + " 'hu': {'phi-4': {'F1-0.5': 0.8472775564409031,\n", + " 'F1-1.5': 0.7527272727272727,\n", + " 'F1-2.5': 0.5825825825825826,\n", + " 'F1-3.5': 0.21052631578947367,\n", + " 'F1-4.5': 0.3333333333333333},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': 0.8005018820577164,\n", + " 'F1-1.5': 0.7236580516898609,\n", + " 'F1-2.5': 0.5425101214574899,\n", + " 'F1-3.5': 0.22727272727272727,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': 0.8684931506849315,\n", + " 'F1-1.5': 0.7762376237623763,\n", + " 'F1-2.5': 0.636986301369863,\n", + " 'F1-3.5': 0.1527777777777778,\n", + " 'F1-4.5': 0.125},\n", + " 'gemma-2-27b-it': {'F1-0.5': 0.7849331713244229,\n", + " 'F1-1.5': 0.7625,\n", + " 'F1-2.5': 0.5579399141630901,\n", + " 'F1-3.5': 0.125,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-32B-Instruct': {'F1-0.5': 0.8267716535433071,\n", + " 'F1-1.5': 0.7276264591439688,\n", + " 'F1-2.5': 0.559748427672956,\n", + " 'F1-3.5': 0.2018348623853211,\n", + " 'F1-4.5': 0.5},\n", + " 'Qwen2.5-7B-Instruct': {'F1-0.5': 0.78031212484994,\n", + " 'F1-1.5': 0.6865203761755486,\n", + " 'F1-2.5': 0.5501285347043702,\n", + " 'F1-3.5': 0.1116751269035533,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-3-27b-it': {'F1-0.5': 0.7764423076923077,\n", + " 'F1-1.5': 0.707936507936508,\n", + " 'F1-2.5': 0.5292740046838408,\n", + " 'F1-3.5': 0.13924050632911392,\n", + " 'F1-4.5': 0.0},\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': {'F1-0.5': 0.8176100628930818,\n", + " 'F1-1.5': 0.781431334622824,\n", + " 'F1-2.5': 0.5907172995780591,\n", + " 'F1-3.5': 0.15,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.2-3B-Instruct': {'F1-0.5': 0.8227571115973742,\n", + " 'F1-1.5': 0.7037037037037037,\n", + " 'F1-2.5': 0.5275590551181102,\n", + " 'F1-3.5': 0.09375,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-2-9b-it': {'F1-0.5': 0.8157560355781448,\n", + " 'F1-1.5': 0.7739463601532567,\n", + " 'F1-2.5': 0.47804878048780486,\n", + " 'F1-3.5': 0.3333333333333333,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': 0.8244897959183674,\n", + " 'F1-1.5': 0.7619047619047619,\n", + " 'F1-2.5': 0.5902777777777778,\n", + " 'F1-3.5': 0.12631578947368421,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': 0.7859733978234583,\n", + " 'F1-1.5': 0.6791277258566978,\n", + " 'F1-2.5': 0.5368421052631579,\n", + " 'F1-3.5': 0.16783216783216784,\n", + " 'F1-4.5': 0.0}},\n", + " 'en': {'phi-4': {'F1-0.5': 0.8583333333333333,\n", + " 'F1-1.5': 0.7557251908396947,\n", + " 'F1-2.5': 0.5565749235474006,\n", + " 'F1-3.5': 0.15584415584415584,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': 0.7940813810110974,\n", + " 'F1-1.5': 0.7294117647058823,\n", + " 'F1-2.5': 0.5785714285714286,\n", + " 'F1-3.5': 0.21875,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': 0.8637602179836512,\n", + " 'F1-1.5': 0.7762376237623763,\n", + " 'F1-2.5': 0.6329113924050633,\n", + " 'F1-3.5': 0.13664596273291926,\n", + " 'F1-4.5': 0.10810810810810811},\n", + " 'gemma-2-27b-it': {'F1-0.5': 0.7840772014475271,\n", + " 'F1-1.5': 0.7647058823529411,\n", + " 'F1-2.5': 0.6148409893992933,\n", + " 'F1-3.5': 0.1111111111111111,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-32B-Instruct': {'F1-0.5': 0.8468965517241379,\n", + " 'F1-1.5': 0.7396694214876033,\n", + " 'F1-2.5': 0.6060606060606061,\n", + " 'F1-3.5': 0.17391304347826086,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-7B-Instruct': {'F1-0.5': 0.7793764988009593,\n", + " 'F1-1.5': 0.7180327868852459,\n", + " 'F1-2.5': 0.5785123966942148,\n", + " 'F1-3.5': 0.11627906976744186,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-3-27b-it': {'F1-0.5': 0.7769784172661871,\n", + " 'F1-1.5': 0.7001569858712716,\n", + " 'F1-2.5': 0.543778801843318,\n", + " 'F1-3.5': 0.12244897959183673,\n", + " 'F1-4.5': 0.18181818181818182},\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': {'F1-0.5': 0.8248730964467005,\n", + " 'F1-1.5': 0.7869481765834933,\n", + " 'F1-2.5': 0.5928853754940712,\n", + " 'F1-3.5': 0.12244897959183673,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.2-3B-Instruct': {'F1-0.5': 0.7843137254901961,\n", + " 'F1-1.5': 0.6537396121883656,\n", + " 'F1-2.5': 0.4723618090452261,\n", + " 'F1-3.5': 0.06060606060606061,\n", + " 'F1-4.5': 0.0},\n", + " 'gemma-2-9b-it': {'F1-0.5': 0.8205128205128205,\n", + " 'F1-1.5': 0.7897838899803536,\n", + " 'F1-2.5': 0.47761194029850745,\n", + " 'F1-3.5': 0.1,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': 0.8244897959183674,\n", + " 'F1-1.5': 0.7476635514018691,\n", + " 'F1-2.5': 0.621160409556314,\n", + " 'F1-3.5': 0.17475728155339806,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': 0.7888349514563107,\n", + " 'F1-1.5': 0.6885245901639344,\n", + " 'F1-2.5': 0.5602240896358543,\n", + " 'F1-3.5': 0.18181818181818182,\n", + " 'F1-4.5': 0.0}}}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metric_regex = \"F1-\\w+\\.\\w+$\"\n", + "# metric_regex = \"Recall-\\w+\\.\\w+$\"\n", + "# metric_regex = \"Precision-\\w+\\.\\w+$\"\n", + "\n", + "metric_results = {\n", + " lang: {\n", + " model: {metric_name: score for metric_name, score in subsubresult[\"metrics\"].items() if re.match(metric_regex, metric_name)}\n", + " for model, subsubresult in subresult.items()\n", + " }\n", + " for lang, subresult in results_complete.items()\n", + " if lang in language_codes.keys()\n", + "}\n", + "metric_results" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "b7dfa539", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'phi-4': {'F1-0.5': np.float64(0.847274907527922),\n", + " 'F1-1.5': np.float64(0.7510695256897097),\n", + " 'F1-2.5': np.float64(0.571604906053786),\n", + " 'F1-3.5': np.float64(0.17936122689966869),\n", + " 'F1-4.5': np.float64(0.1490299823633157)},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': np.float64(0.8003834392456585),\n", + " 'F1-1.5': np.float64(0.7296782946778414),\n", + " 'F1-2.5': np.float64(0.5430671451547378),\n", + " 'F1-3.5': np.float64(0.18648266978872874),\n", + " 'F1-4.5': np.float64(0.0)},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': np.float64(0.8581688937262477),\n", + " 'F1-1.5': np.float64(0.7892528724679936),\n", + " 'F1-2.5': np.float64(0.6178853512142768),\n", + " 'F1-3.5': np.float64(0.14842852327853853),\n", + " 'F1-4.5': np.float64(0.11143962483784509)},\n", + " 'gemma-2-27b-it': {'F1-0.5': np.float64(0.7825637109275099),\n", + " 'F1-1.5': np.float64(0.7576358996167376),\n", + " 'F1-2.5': np.float64(0.5661145846182845),\n", + " 'F1-3.5': np.float64(0.1447119447768317),\n", + " 'F1-4.5': np.float64(0.0)},\n", + " 'Qwen2.5-32B-Instruct': {'F1-0.5': np.float64(0.8332919761866082),\n", + " 'F1-1.5': np.float64(0.7382679148378952),\n", + " 'F1-2.5': np.float64(0.5874564372969799),\n", + " 'F1-3.5': np.float64(0.18075875644630227),\n", + " 'F1-4.5': np.float64(0.1111111111111111)},\n", + " 'Qwen2.5-7B-Instruct': {'F1-0.5': np.float64(0.7791102234294924),\n", + " 'F1-1.5': np.float64(0.6839982183660622),\n", + " 'F1-2.5': np.float64(0.5365887890519843),\n", + " 'F1-3.5': np.float64(0.11365123222568246),\n", + " 'F1-4.5': np.float64(0.0)},\n", + " 'gemma-3-27b-it': {'F1-0.5': np.float64(0.7770964126747921),\n", + " 'F1-1.5': np.float64(0.7025684847858245),\n", + " 'F1-2.5': np.float64(0.537278648254013),\n", + " 'F1-3.5': np.float64(0.13774528084068177),\n", + " 'F1-4.5': np.float64(0.10750360750360749)},\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': {'F1-0.5': np.float64(0.8187822349096482),\n", + " 'F1-1.5': np.float64(0.7801634850999061),\n", + " 'F1-2.5': np.float64(0.5977161428034777),\n", + " 'F1-3.5': np.float64(0.15987016120259917),\n", + " 'F1-4.5': np.float64(0.0)},\n", + " 'Llama-3.2-3B-Instruct': {'F1-0.5': np.float64(0.7990367837260537),\n", + " 'F1-1.5': np.float64(0.6648229954490312),\n", + " 'F1-2.5': np.float64(0.5027143407149636),\n", + " 'F1-3.5': np.float64(0.0868393239730137),\n", + " 'F1-4.5': np.float64(0.007662835249042145)},\n", + " 'gemma-2-9b-it': {'F1-0.5': np.float64(0.8172066827369434),\n", + " 'F1-1.5': np.float64(0.778996918671368),\n", + " 'F1-2.5': np.float64(0.4621499180956074),\n", + " 'F1-3.5': np.float64(0.12959414576351205),\n", + " 'F1-4.5': np.float64(0.0)},\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': np.float64(0.8295528541963014),\n", + " 'F1-1.5': np.float64(0.7614422792261674),\n", + " 'F1-2.5': np.float64(0.6230111832308236),\n", + " 'F1-3.5': np.float64(0.14456943280818038),\n", + " 'F1-4.5': np.float64(0.11507381507381506)},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': np.float64(0.7850647229253985),\n", + " 'F1-1.5': np.float64(0.6750876463030314),\n", + " 'F1-2.5': np.float64(0.5509999191472642),\n", + " 'F1-3.5': np.float64(0.16135963146573704),\n", + " 'F1-4.5': np.float64(0.0)}}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lang_averaged_metric_results = {}\n", + "for lang, subresult in metric_results.items():\n", + " for model, metrics in subresult.items():\n", + " if model not in lang_averaged_metric_results:\n", + " lang_averaged_metric_results[model] = {}\n", + " for metric_name, score in metrics.items():\n", + " if metric_name not in lang_averaged_metric_results[model]:\n", + " lang_averaged_metric_results[model][metric_name] = []\n", + " lang_averaged_metric_results[model][metric_name].append(score)\n", + "\n", + "for model, metrics in lang_averaged_metric_results.items():\n", + " for metric_name, scores in metrics.items():\n", + " lang_averaged_metric_results[model][metric_name] = np.mean(scores)\n", + "lang_averaged_metric_results" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "a049a58e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import copy\n", + "\n", + "lang = \"avg\"\n", + "if lang == \"avg\": \n", + " threshold_results = copy.deepcopy(lang_averaged_metric_results)\n", + "else:\n", + " threshold_results = metric_results[lang]\n", + "\n", + "# Sort threshold labels\n", + "threshold_labels = sorted(next(iter(threshold_results.values())).keys(), key=lambda x: float(x.split('-')[1]))\n", + "x = [float(label.split('-')[1]) for label in threshold_labels]\n", + "\n", + "# Plot\n", + "plt.figure(figsize=(10, 6))\n", + "for model, metrics in threshold_results.items():\n", + " y = [metrics[threshold] for threshold in threshold_labels]\n", + " plt.plot(x, y, marker='o', label=model)\n", + "\n", + "plt.xlabel(\"Threshold\")\n", + "plt.ylabel(\"F1 Score\")\n", + "plt.title(f\"{lang} F1 Scores (threshold binarization)\")\n", + "plt.legend(title=\"Model\")\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "13ca1ac3", + "metadata": {}, + "outputs": [], + "source": [ + "# TODO check how class imbalance impacts the f1 score " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f4a68a3", + "metadata": {}, + "outputs": [], "source": [] }, + { + "cell_type": "markdown", + "id": "b1948eb3", + "metadata": {}, + "source": [ + "# Sourced LLM-as-a-judge Training Data" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "d37c12bb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'pol': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/pol_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'ita': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ita_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'fin': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fin_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'ell': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ell_Grek_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'nob': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/nob_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'lit': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/lit_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'fra': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fra_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'spa': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/spa_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'hun': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/hun_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl')}" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "language_codes_500k_docs = {\n", + " \"spa\": \"Spanish\",\n", + " \"fra\": \"French\",\n", + " \"ita\": \"Italian\",\n", + " \"pol\": \"Polish\",\n", + " \"ell\": \"Greek\", # Modern Greek\n", + " \"nob\": \"Norwegian\", # Norwegian Bokmål (dominant variety)\n", + " \"hun\": \"Hungarian\",\n", + " \"fin\": \"Finnish\",\n", + " \"lit\": \"Lithuanian\",\n", + "}\n", + "model = ablated_models[2]\n", + "model_annotations_paths = list((annotated_500k_samples_path / f\"{model}_aggregated\").glob(\"**/*.jsonl\"))\n", + "# filter only the languages that we want to check\n", + "model_annotations_paths = {path.stem.split(\"_\")[0]: path for path in model_annotations_paths if path.stem.split(\"_\")[0] in language_codes_500k_docs.keys()}\n", + "model_annotations_paths" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "57d3b39d", + "metadata": {}, + "outputs": [], + "source": [ + "lang_to_scores = {lang: list() for lang in model_annotations_paths.keys()}\n", + "\n", + "for lang, model_annotations_path in model_annotations_paths.items():\n", + " with open(model_annotations_path, 'r') as f:\n", + " for line in f:\n", + " json_line = json.loads(line)\n", + " try:\n", + " score = float(json_line[\"score\"])\n", + " except: \n", + " continue\n", + " lang_to_scores[lang].append(score)" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "id": "dc8466ca", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for lang, scores in lang_to_scores.items():\n", + " num_scores = len(scores)\n", + " counts = Counter(scores)\n", + " x = sorted(counts.keys())\n", + " y = [counts[val]/num_scores for val in x]\n", + " plt.plot(x, y, label=lang)\n", + "\n", + "plt.xlabel(\"Score\")\n", + "plt.ylabel(\"Number of Scores\")\n", + "plt.title(\"Score Distribution per Language\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "id": "7cd98dd1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for lang, scores in lang_to_scores.items():\n", + " num_scores = len(scores)\n", + " counts = Counter(scores)\n", + " all_scores = sorted(set(scores))\n", + " \n", + " # Ensure all relevant score levels are included\n", + " all_scores_sorted = sorted(all_scores)\n", + "\n", + " # Compute cumulative counts from the right\n", + " y_cumulative = []\n", + " for i, score in enumerate(all_scores_sorted):\n", + " count = sum(counts[s]/num_scores for s in all_scores_sorted[i:])\n", + " y_cumulative.append(count)\n", + "\n", + " plt.plot(all_scores_sorted, y_cumulative, label=lang)\n", + "\n", + "plt.xlabel(\"Score\")\n", + "plt.ylabel(\"Number of Scores ≥ Score\")\n", + "plt.title(\"Right-Cumulative Score Distribution per Language\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.savefig(plot_path / f\"llm_annotator_cummulative_score_dist_{model}.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", + "\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "a7766cf9", + "id": "e393e456", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cecd2c02", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 139, + "id": "22168b01", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'pol': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/pol_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'ita': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ita_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'fin': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fin_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'ell': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ell_Grek_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'nob': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/nob_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'lit': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/lit_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'fra': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fra_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'spa': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/spa_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'hun': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/hun_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl')}" + ] + }, + "execution_count": 139, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "language_codes_500k_docs = {\n", + " \"spa\": \"Spanish\",\n", + " \"fra\": \"French\",\n", + " \"ita\": \"Italian\",\n", + " \"pol\": \"Polish\",\n", + " \"ell\": \"Greek\", # Modern Greek\n", + " \"nob\": \"Norwegian\", # Norwegian Bokmål (dominant variety)\n", + " \"hun\": \"Hungarian\",\n", + " \"fin\": \"Finnish\",\n", + " \"lit\": \"Lithuanian\",\n", + "}\n", + "model = ablated_models[2]\n", + "model_annotations_paths = list((annotated_500k_samples_path / f\"{model}_aggregated\").glob(\"**/*.jsonl\"))\n", + "# filter only the languages that we want to check\n", + "model_annotations_paths = {path.stem.split(\"_\")[0]: path for path in model_annotations_paths if path.stem.split(\"_\")[0] in language_codes_500k_docs.keys()}\n", + "model_annotations_paths" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "id": "3cf84acb", + "metadata": {}, + "outputs": [], + "source": [ + "lang_to_scores = {lang: list() for lang in model_annotations_paths.keys()}\n", + "\n", + "for lang, model_annotations_path in model_annotations_paths.items():\n", + " with open(model_annotations_path, 'r') as f:\n", + " for line in f:\n", + " json_line = json.loads(line)\n", + " try:\n", + " score = float(json_line[\"score\"])\n", + " except: \n", + " continue\n", + " lang_to_scores[lang].append(score)" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "id": "06bad9bb", + "metadata": {}, + "outputs": [], + "source": [ + "series_list = []\n", + "\n", + "for lang, scores in lang_to_scores.items():\n", + " num_scores = len(scores)\n", + " counts = Counter(scores)\n", + " all_scores = sorted(set(scores))\n", + " \n", + " # Ensure all relevant score levels are included\n", + " all_scores_sorted = sorted(all_scores)\n", + "\n", + " # Compute cumulative counts from the right\n", + " y_cumulative = []\n", + " for i, score in enumerate(all_scores_sorted):\n", + " count = sum(counts[s]/num_scores for s in all_scores_sorted[i:])\n", + " y_cumulative.append(count)\n", + " \n", + " series_list.append((all_scores_sorted, y_cumulative))" + ] + }, + { + "cell_type": "code", + "execution_count": 142, + "id": "bcaa53ba", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy.interpolate import interp1d\n", + "\n", + "# Example: All share same min/max x (0 to 4), but vary inside\n", + "# series_list = [\n", + "\n", + "# (np.array([0.0, 1.0, 2.5, 4.0]), np.array([1.0, 2.0, 1.5, 3.0])),\n", + "# (np.array([0.0, 1.5, 3.0, 4.0]), np.array([1.2, 1.9, 2.0, 2.8])),\n", + "# (np.array([0.0, 0.8, 2.0, 4.0]), np.array([0.8, 1.9, 1.4, 3.2])),\n", + "# ]\n", + "\n", + "# Step 1: Define common grid\n", + "x_min = series_list[0][0][0]\n", + "x_max = series_list[0][0][-1]\n", + "common_x = np.linspace(x_min, x_max, 200)\n", + "\n", + "# Step 2: Interpolate each series onto the grid\n", + "interpolated_ys = []\n", + "for x, y in series_list:\n", + " f = interp1d(x, y, kind='linear', bounds_error=False, fill_value=np.nan)\n", + " interpolated_ys.append(f(common_x))\n", + "\n", + "Y = np.vstack(interpolated_ys)\n", + "\n", + "# Step 3: Compute mean and 95% CI, ignoring NaNs\n", + "mean_y = np.nanmean(Y, axis=0)\n", + "std_y = np.nanstd(Y, axis=0)\n", + "n = np.sum(~np.isnan(Y), axis=0)\n", + "ci = 2.575 * std_y / np.sqrt(n)\n", + "\n", + "# Step 4: Plot\n", + "plt.plot(common_x, mean_y, label='Mean')\n", + "plt.fill_between(common_x, mean_y - ci, mean_y + ci, alpha=0.3, label='95% CI')\n", + "plt.xlabel(\"X\")\n", + "plt.ylabel(\"Y\")\n", + "plt.legend()\n", + "plt.title(\"Mean + 95% CI from Series with Shared Range\")\n", + "plt.grid(True)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "id": "dee2de32", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(all_scores_sorted, y_cumulative, label=lang)\n", + "\n", + "plt.xlabel(\"Score\")\n", + "plt.ylabel(\"Number of Scores ≥ Score\")\n", + "plt.title(\"Right-Cumulative Score Distribution per Language\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.savefig(plot_path / f\"llm_annotator_cummulative_score_dist_{model}.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "id": "5b50d0e9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[1.0000000000000002,\n", + " 0.6353215582720513,\n", + " 0.6353175298556016,\n", + " 0.13247044652982135,\n", + " 0.1323314661623089,\n", + " 0.13232139512118482,\n", + " 0.13228916778958774,\n", + " 0.012359181667482417,\n", + " 0.012240343382218164,\n", + " 0.012232286549318893,\n", + " 0.012169846094349538,\n", + " 0.0015448977084353025,\n", + " 0.0015328124590863954,\n", + " 0.0015287840426367596,\n", + " 0.0015247556261871239,\n", + " 4.229837272117517e-05]" + ] + }, + "execution_count": 110, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_cumulative" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b0ba49e8", "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12321a47", + "metadata": {}, + "outputs": [], + "source": [ + "series_list = []\n", + "\n", + "for lang, scores in lang_to_scores.items():\n", + " num_scores = len(scores)\n", + " counts = Counter(scores)\n", + " all_scores = sorted(set(scores))\n", + " \n", + " # Ensure all relevant score levels are included\n", + " all_scores_sorted = sorted(all_scores)\n", + "\n", + " # Compute cumulative counts from the right\n", + " y_cumulative = []\n", + " for i, score in enumerate(all_scores_sorted):\n", + " count = sum(counts[s]/num_scores for s in all_scores_sorted[i:])\n", + " y_cumulative.append(count)\n", + " \n", + " series_list.append((all_scores_sorted, y_cumulative))" + ] } ], "metadata": { From d04d4722a51cc196294966a2b1fb9a6e1b65d80b Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Mon, 12 May 2025 21:21:26 +0200 Subject: [PATCH 5/7] feat: added f1 @k metric --- .../analysis/interrater_reliability.py | 27 +++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) diff --git a/src/ml_filter/analysis/interrater_reliability.py b/src/ml_filter/analysis/interrater_reliability.py index 9943f9d4..725755fa 100644 --- a/src/ml_filter/analysis/interrater_reliability.py +++ b/src/ml_filter/analysis/interrater_reliability.py @@ -10,7 +10,7 @@ import numpy as np import pandas as pd from scipy.stats import kendalltau, spearmanr -from sklearn.metrics import cohen_kappa_score, f1_score, ndcg_score +from sklearn.metrics import cohen_kappa_score, f1_score, ndcg_score, precision_score, recall_score from statsmodels.stats.inter_rater import fleiss_kappa from ml_filter.analysis.plot_score_distributions import plot_confusion_matrix @@ -189,7 +189,30 @@ def compute_gt_metrics( # Othwerwise, zipping will will proive the wrong results class_f1_scores = f1_score(ground_truth_rounded, predictions_rounded, average=None, labels=valid_labels) for valid_label, f1 in zip(valid_labels, class_f1_scores): - gt_metrics[f"F1-{valid_label}"] = f1 + gt_metrics[f"F1-{valid_label}_vs_rest"] = f1 + + # f1 score at threshold + for t in np.array(list(range(5))) + 0.5: + ground_truth_rounded_bin = (np.array(ground_truth_rounded) >= t).astype(int) + predictions_rounded_bin = (np.array(predictions_rounded) >= t).astype(int) + gt_metrics[f"F1-{t}"] = f1_score( + ground_truth_rounded_bin, + predictions_rounded_bin, + labels=[int(valid_label) for valid_label in valid_labels], + zero_division=0, + ) + gt_metrics[f"Recall-{t}"] = recall_score( + ground_truth_rounded_bin, + predictions_rounded_bin, + labels=[int(valid_label) for valid_label in valid_labels], + zero_division=0, + ) + gt_metrics[f"Precision-{t}"] = precision_score( + ground_truth_rounded_bin, + predictions_rounded_bin, + labels=[int(valid_label) for valid_label in valid_labels], + zero_division=0, + ) # NDCG@all gt_metrics["NDCG@all"] = ndcg_score(y_true=[ground_truth_scores], y_score=[predicted_scores], k=None) From d0268133babca2813857dd7ec9a4069840dd212c Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Mon, 12 May 2025 21:22:45 +0200 Subject: [PATCH 6/7] feat: more work on plots --- notebooks/edu_content_human_as_a_judge.ipynb | 5107 ++++++++++++++---- 1 file changed, 4046 insertions(+), 1061 deletions(-) diff --git a/notebooks/edu_content_human_as_a_judge.ipynb b/notebooks/edu_content_human_as_a_judge.ipynb index 0002db1e..d3a7b872 100644 --- a/notebooks/edu_content_human_as_a_judge.ipynb +++ b/notebooks/edu_content_human_as_a_judge.ipynb @@ -28,22 +28,26 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 2, "id": "efba794a", "metadata": {}, "outputs": [], "source": [ "language_codes = {\n", - " \"en\": \"English\", # TODO: Remove English from the list?\n", + " # \"en\": \"English\", # TODO: Remove English from the list?\n", + " \"bg\": \"Bulgarian\",\n", + " \"pl\": \"Polish\",\n", + " \"uk\": \"Ukrainian\",\n", + " \"de\": \"German\",\n", + " \"nb\": \"Norwegian\", # Bokmal\n", " \"es\": \"Spanish\",\n", " \"fr\": \"French\",\n", " \"it\": \"Italian\",\n", - " \"pl\": \"Polish\",\n", - " \"el\": \"Greek\",\n", - " \"nb\": \"Norwegian\", # Bokmal\n", " \"hu\": \"Hungarian\",\n", " \"fi\": \"Finnish\",\n", " \"lt\": \"Lithuanian\",\n", + " \"el\": \"Greek\",\n", + " \"tr\": \"Turkish\",\n", "}\n", "\n", "ablated_models = [\"gemma-3-27b-it\", \"Llama-3.3-70B-Instruct\", \"Mistral-Small-3.1-24B-Instruct-2503\"]" @@ -59,16 +63,18 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": null, "id": "e976311c", "metadata": {}, "outputs": [], "source": [ "gt_annotations_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_raw_scores/annotations__educational_content__en__gt.jsonl\")\n", "en_documents_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_en.jsonl\")\n", - "llm_as_a_judge_metrics_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/output/llm_as_a_judge_metrics\")\n", + "llm_as_a_judge_metrics_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/output/llm_as_a_judge_metrics_continuous_spearman\")\n", "annotated_500k_samples_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content\")\n", - "plot_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/output/plots\")\n", + "\n", + "# must be set!\n", + "# plot_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/output/plots\")\n", "\n", "if not plot_path.exists():\n", " plot_path.mkdir(parents=True)" @@ -84,7 +90,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 4, "id": "3467ff65", "metadata": {}, "outputs": [], @@ -119,7 +125,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 5, "id": "57a95718", "metadata": {}, "outputs": [], @@ -133,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 6, "id": "142a4b26", "metadata": {}, "outputs": [ @@ -161,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 7, "id": "c43d692e", "metadata": {}, "outputs": [ @@ -171,7 +177,7 @@ "np.float64(0.5627472794400139)" ] }, - "execution_count": 82, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -183,7 +189,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 8, "id": "08d566f8", "metadata": {}, "outputs": [ @@ -222,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 9, "id": "3a5814db", "metadata": {}, "outputs": [ @@ -250,7 +256,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 10, "id": "5e1987d3", "metadata": {}, "outputs": [], @@ -261,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 11, "id": "99e69d68", "metadata": {}, "outputs": [ @@ -275,7 +281,7 @@ " np.float64(100.0)]" ] }, - "execution_count": 86, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -292,7 +298,7 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 12, "id": "ce70f9a3", "metadata": {}, "outputs": [ @@ -323,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 13, "id": "4abce843", "metadata": {}, "outputs": [ @@ -613,7 +619,7 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 14, "id": "34ad74ff", "metadata": {}, "outputs": [], @@ -623,7 +629,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 15, "id": "b3b5f51c", "metadata": {}, "outputs": [ @@ -684,14 +690,14 @@ { "cell_type": "code", "execution_count": null, - "id": "3a289826", + "id": "e1789f3d", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 18, "id": "eb44a56c", "metadata": {}, "outputs": [ @@ -758,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 19, "id": "ff3b4355", "metadata": {}, "outputs": [], @@ -768,6 +774,14 @@ "# * Could also plot the confusion matrix instead\n" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "786b91d9", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "id": "197531d3", @@ -778,7 +792,7 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 20, "id": "c944d423", "metadata": {}, "outputs": [ @@ -787,7 +801,7 @@ "text/plain": [ "{'bg': {'phi-4': {'metrics': {'Fleiss': 0.2502797242524014,\n", " 'Cohen': 0.2581460372083022,\n", - " 'Spearman': 0.6311440245975249,\n", + " 'Spearman': 0.636985906295526,\n", " 'Kendall': 0.524629373412667,\n", " 'Krippendorff': 0.5890210059887584,\n", " 'Invalid': 0,\n", @@ -834,7 +848,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.16588711569468226,\n", " 'Cohen': 0.19228036253776437,\n", - " 'Spearman': 0.5866735918259259,\n", + " 'Spearman': 0.591981858701982,\n", " 'Kendall': 0.4939727977473699,\n", " 'Krippendorff': 0.5239927892374399,\n", " 'Invalid': 0,\n", @@ -881,7 +895,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.1952697772865512,\n", " 'Cohen': 0.21288702771196144,\n", - " 'Spearman': 0.6894543026772014,\n", + " 'Spearman': 0.6949435819158003,\n", " 'Kendall': 0.5780140123660208,\n", " 'Krippendorff': 0.6132355579928987,\n", " 'Invalid': 0,\n", @@ -928,7 +942,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.025509070998077806,\n", " 'Cohen': 0.08529134099763735,\n", - " 'Spearman': 0.6621198760734975,\n", + " 'Spearman': 0.665015121881333,\n", " 'Kendall': 0.5710736903378152,\n", " 'Krippendorff': 0.5366922584229493,\n", " 'Invalid': 2,\n", @@ -975,7 +989,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.20970578693031436,\n", " 'Cohen': 0.22677390868517155,\n", - " 'Spearman': 0.6476570429117524,\n", + " 'Spearman': 0.6548091179003084,\n", " 'Kendall': 0.5439294506597407,\n", " 'Krippendorff': 0.5745297705960156,\n", " 'Invalid': 0,\n", @@ -1022,7 +1036,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.0748672732118802,\n", " 'Cohen': -0.004948005531708599,\n", - " 'Spearman': 0.5845839095381624,\n", + " 'Spearman': 0.5917735395767074,\n", " 'Kendall': 0.4886454021363991,\n", " 'Krippendorff': 0.20213144548093886,\n", " 'Invalid': 0,\n", @@ -1069,7 +1083,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.08805710097211039,\n", " 'Cohen': -0.02465995247255859,\n", - " 'Spearman': 0.7131750895812335,\n", + " 'Spearman': 0.7121437200586265,\n", " 'Kendall': 0.6106605794735107,\n", " 'Krippendorff': 0.3024829613772677,\n", " 'Invalid': 0,\n", @@ -1116,7 +1130,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.18746775596467924,\n", " 'Cohen': 0.2146604678052657,\n", - " 'Spearman': 0.7072854808518002,\n", + " 'Spearman': 0.7120255639992602,\n", " 'Kendall': 0.6048434606941641,\n", " 'Krippendorff': 0.6035543126477034,\n", " 'Invalid': 0,\n", @@ -1163,7 +1177,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.10959884026410578,\n", " 'Cohen': -0.02306686589465823,\n", - " 'Spearman': 0.4563674269747377,\n", + " 'Spearman': 0.4670353897953112,\n", " 'Kendall': 0.36817233744751726,\n", " 'Krippendorff': -0.020749787234160655,\n", " 'Invalid': 198,\n", @@ -1210,7 +1224,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13297603241902303,\n", " 'Cohen': 0.1734400094010733,\n", - " 'Spearman': 0.6911600163966094,\n", + " 'Spearman': 0.691804608571313,\n", " 'Kendall': 0.5934610549123195,\n", " 'Krippendorff': 0.5907768825035782,\n", " 'Invalid': 1,\n", @@ -1257,7 +1271,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.09640031331237015,\n", " 'Cohen': 0.12505495954977142,\n", - " 'Spearman': 0.6716945975644261,\n", + " 'Spearman': 0.6648756282989798,\n", " 'Kendall': 0.5478529174647802,\n", " 'Krippendorff': 0.5323514771423119,\n", " 'Invalid': 40,\n", @@ -1304,7 +1318,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.056315443761833006,\n", " 'Cohen': 0.001451882424917561,\n", - " 'Spearman': 0.6014362105080493,\n", + " 'Spearman': 0.6075480658175866,\n", " 'Kendall': 0.5060105233253961,\n", " 'Krippendorff': 0.2565356722442852,\n", " 'Invalid': 0,\n", @@ -1351,7 +1365,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'nn': {'phi-4': {'metrics': {'Fleiss': 0.16444244299451757,\n", " 'Cohen': 0.18324801543141167,\n", - " 'Spearman': 0.6209741069451624,\n", + " 'Spearman': 0.634040725900716,\n", " 'Kendall': 0.5131672067321597,\n", " 'Krippendorff': 0.4859623258032618,\n", " 'Invalid': 0,\n", @@ -1398,7 +1412,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06694713783776174,\n", " 'Cohen': 0.10713148756728164,\n", - " 'Spearman': 0.578123570001379,\n", + " 'Spearman': 0.5848739446808434,\n", " 'Kendall': 0.4936621218347517,\n", " 'Krippendorff': 0.4709800690856343,\n", " 'Invalid': 0,\n", @@ -1445,7 +1459,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.25042940399718033,\n", " 'Cohen': 0.26392734576086097,\n", - " 'Spearman': 0.6779077917660319,\n", + " 'Spearman': 0.6845612778214859,\n", " 'Kendall': 0.5711313557788666,\n", " 'Krippendorff': 0.6245946737902759,\n", " 'Invalid': 0,\n", @@ -1492,7 +1506,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.04859592016160266,\n", " 'Cohen': 0.11581036126296129,\n", - " 'Spearman': 0.6014322241851677,\n", + " 'Spearman': 0.6069087021477471,\n", " 'Kendall': 0.5171421992696367,\n", " 'Krippendorff': 0.5077404646762644,\n", " 'Invalid': 0,\n", @@ -1539,7 +1553,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.12543698377608567,\n", " 'Cohen': 0.14984805363947706,\n", - " 'Spearman': 0.646030067841479,\n", + " 'Spearman': 0.6500373105943037,\n", " 'Kendall': 0.5436493560045431,\n", " 'Krippendorff': 0.5292841606177214,\n", " 'Invalid': 0,\n", @@ -1586,7 +1600,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11999214935845538,\n", " 'Cohen': -0.033177929660978656,\n", - " 'Spearman': 0.6027588423936515,\n", + " 'Spearman': 0.6095380753376158,\n", " 'Kendall': 0.5135247406237631,\n", " 'Krippendorff': 0.18211136335594036,\n", " 'Invalid': 0,\n", @@ -1633,7 +1647,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09611125521259406,\n", " 'Cohen': -0.03410401088015358,\n", - " 'Spearman': 0.6916172547036901,\n", + " 'Spearman': 0.6956512373043822,\n", " 'Kendall': 0.5964952117080603,\n", " 'Krippendorff': 0.3163952215507081,\n", " 'Invalid': 1,\n", @@ -1680,7 +1694,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.16278427188788,\n", " 'Cohen': 0.19544073247248805,\n", - " 'Spearman': 0.6440932599142971,\n", + " 'Spearman': 0.647420568112268,\n", " 'Kendall': 0.5539589469544739,\n", " 'Krippendorff': 0.5516442303342037,\n", " 'Invalid': 0,\n", @@ -1727,7 +1741,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07365376503906643,\n", " 'Cohen': -0.010854765506807862,\n", - " 'Spearman': 0.45160943424490707,\n", + " 'Spearman': 0.4340909875992279,\n", " 'Kendall': 0.36469976884772837,\n", " 'Krippendorff': 0.17707943687895744,\n", " 'Invalid': 328,\n", @@ -1774,7 +1788,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13109122967413311,\n", " 'Cohen': 0.16828355969835773,\n", - " 'Spearman': 0.6582505485546322,\n", + " 'Spearman': 0.6657686594626404,\n", " 'Kendall': 0.5654799331153871,\n", " 'Krippendorff': 0.562397590808722,\n", " 'Invalid': 1,\n", @@ -1821,7 +1835,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.16152820783816604,\n", " 'Cohen': 0.17970270285969858,\n", - " 'Spearman': 0.6598531346966264,\n", + " 'Spearman': 0.6615289237764627,\n", " 'Kendall': 0.5355522810668969,\n", " 'Krippendorff': 0.582108869117056,\n", " 'Invalid': 42,\n", @@ -1868,7 +1882,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.062333647725757634,\n", " 'Cohen': -0.0025724911221094438,\n", - " 'Spearman': 0.6256584690813798,\n", + " 'Spearman': 0.6280202984692997,\n", " 'Kendall': 0.5266668355988499,\n", " 'Krippendorff': 0.28553359406392387,\n", " 'Invalid': 0,\n", @@ -1915,7 +1929,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sq': {'phi-4': {'metrics': {'Fleiss': 0.15789680599340014,\n", " 'Cohen': 0.17313658976746882,\n", - " 'Spearman': 0.6155713315141391,\n", + " 'Spearman': 0.6245111661920767,\n", " 'Kendall': 0.5070353469354135,\n", " 'Krippendorff': 0.5200690567490972,\n", " 'Invalid': 0,\n", @@ -1962,7 +1976,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08598490157992747,\n", " 'Cohen': 0.12068965517241381,\n", - " 'Spearman': 0.6035969849270258,\n", + " 'Spearman': 0.6083300415015487,\n", " 'Kendall': 0.5094162432445601,\n", " 'Krippendorff': 0.5064341379930453,\n", " 'Invalid': 0,\n", @@ -2009,7 +2023,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.19373418484154717,\n", " 'Cohen': 0.21228474154858945,\n", - " 'Spearman': 0.6878597146510587,\n", + " 'Spearman': 0.6954788065437562,\n", " 'Kendall': 0.5766711648489272,\n", " 'Krippendorff': 0.6023978898305775,\n", " 'Invalid': 0,\n", @@ -2056,7 +2070,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.016226760701848763,\n", " 'Cohen': 0.0784990379069509,\n", - " 'Spearman': 0.6280728849239657,\n", + " 'Spearman': 0.63524288413785,\n", " 'Kendall': 0.537931055791393,\n", " 'Krippendorff': 0.5127235529602789,\n", " 'Invalid': 3,\n", @@ -2103,7 +2117,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.09217360854424836,\n", " 'Cohen': 0.11830557471210079,\n", - " 'Spearman': 0.6536760125194008,\n", + " 'Spearman': 0.6585330014328645,\n", " 'Kendall': 0.549619687494579,\n", " 'Krippendorff': 0.5329373360984615,\n", " 'Invalid': 0,\n", @@ -2150,7 +2164,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.1594965426526844,\n", " 'Cohen': -0.06960134295726661,\n", - " 'Spearman': 0.6173848780690402,\n", + " 'Spearman': 0.6235393914987921,\n", " 'Kendall': 0.5267091052413663,\n", " 'Krippendorff': 0.12429444632553532,\n", " 'Invalid': 0,\n", @@ -2197,7 +2211,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09829219072875885,\n", " 'Cohen': -0.03227126970048433,\n", - " 'Spearman': 0.6890277208153167,\n", + " 'Spearman': 0.6919942016950994,\n", " 'Kendall': 0.5899349929185254,\n", " 'Krippendorff': 0.2695447372109828,\n", " 'Invalid': 0,\n", @@ -2244,7 +2258,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.16695059625212946,\n", " 'Cohen': 0.20005003897266138,\n", - " 'Spearman': 0.665144802737207,\n", + " 'Spearman': 0.6734350800449852,\n", " 'Kendall': 0.5710603560366054,\n", " 'Krippendorff': 0.552526906643166,\n", " 'Invalid': 0,\n", @@ -2291,7 +2305,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.0681746779767515,\n", " 'Cohen': 0.01953930581285601,\n", - " 'Spearman': 0.3660080827874114,\n", + " 'Spearman': 0.35921921068177504,\n", " 'Kendall': 0.29578049895997244,\n", " 'Krippendorff': -0.10150519008432224,\n", " 'Invalid': 255,\n", @@ -2338,7 +2352,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10842349727488122,\n", " 'Cohen': 0.15418092619334933,\n", - " 'Spearman': 0.6821129504596419,\n", + " 'Spearman': 0.6892349330543994,\n", " 'Kendall': 0.5881935928131693,\n", " 'Krippendorff': 0.5621908933290543,\n", " 'Invalid': 4,\n", @@ -2385,7 +2399,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 1, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.06785449230690486,\n", " 'Cohen': 0.10029641014381385,\n", - " 'Spearman': 0.6729470772740832,\n", + " 'Spearman': 0.678574708423601,\n", " 'Kendall': 0.5540202691527693,\n", " 'Krippendorff': 0.5226504197503163,\n", " 'Invalid': 39,\n", @@ -2432,7 +2446,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06714244101369066,\n", " 'Cohen': -0.004414103196797914,\n", - " 'Spearman': 0.6376440405185222,\n", + " 'Spearman': 0.6439282024623049,\n", " 'Kendall': 0.5402659277104233,\n", " 'Krippendorff': 0.24937926488826512,\n", " 'Invalid': 0,\n", @@ -2479,7 +2493,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'nb': {'phi-4': {'metrics': {'Fleiss': 0.21552882131522622,\n", " 'Cohen': 0.22812283649074583,\n", - " 'Spearman': 0.6498534442554926,\n", + " 'Spearman': 0.6563181307136616,\n", " 'Kendall': 0.542353733268824,\n", " 'Krippendorff': 0.5531401487075167,\n", " 'Invalid': 0,\n", @@ -2526,7 +2540,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0760532145238589,\n", " 'Cohen': 0.11510918701714945,\n", - " 'Spearman': 0.5946333886099705,\n", + " 'Spearman': 0.5946243553177213,\n", " 'Kendall': 0.5041168968431521,\n", " 'Krippendorff': 0.4909249050765856,\n", " 'Invalid': 0,\n", @@ -2573,7 +2587,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2473059927126134,\n", " 'Cohen': 0.26172212875569123,\n", - " 'Spearman': 0.684938864469191,\n", + " 'Spearman': 0.6935803198625042,\n", " 'Kendall': 0.5765971169616891,\n", " 'Krippendorff': 0.6294024949736439,\n", " 'Invalid': 0,\n", @@ -2620,7 +2634,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.05644862886979403,\n", " 'Cohen': 0.12310866574965607,\n", - " 'Spearman': 0.6089708676155107,\n", + " 'Spearman': 0.6134978838460946,\n", " 'Kendall': 0.5248674438181551,\n", " 'Krippendorff': 0.5126263169377094,\n", " 'Invalid': 1,\n", @@ -2667,7 +2681,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.15087117437375586,\n", " 'Cohen': 0.1747603622035312,\n", - " 'Spearman': 0.6566076811289737,\n", + " 'Spearman': 0.659861073319925,\n", " 'Kendall': 0.5585164950656233,\n", " 'Krippendorff': 0.5681127287770646,\n", " 'Invalid': 0,\n", @@ -2714,7 +2728,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.12907609021259053,\n", " 'Cohen': -0.04250178123354287,\n", - " 'Spearman': 0.6245634680624422,\n", + " 'Spearman': 0.6286145557631627,\n", " 'Kendall': 0.5322031489932144,\n", " 'Krippendorff': 0.22830888130604177,\n", " 'Invalid': 0,\n", @@ -2761,7 +2775,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09780265670222289,\n", " 'Cohen': -0.034907270451700834,\n", - " 'Spearman': 0.6956820260923505,\n", + " 'Spearman': 0.7011387123642994,\n", " 'Kendall': 0.5963815718522555,\n", " 'Krippendorff': 0.3055541217476164,\n", " 'Invalid': 0,\n", @@ -2808,7 +2822,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.22053178868029868,\n", " 'Cohen': 0.24504634994206254,\n", - " 'Spearman': 0.6747227013355853,\n", + " 'Spearman': 0.6804091524864903,\n", " 'Kendall': 0.5805903852931942,\n", " 'Krippendorff': 0.5859043559322508,\n", " 'Invalid': 0,\n", @@ -2855,7 +2869,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.04678362573099412,\n", " 'Cohen': 0.023906684482323026,\n", - " 'Spearman': 0.47623723204990437,\n", + " 'Spearman': 0.47486473315204364,\n", " 'Kendall': 0.39222905368278405,\n", " 'Krippendorff': 0.0954564495004836,\n", " 'Invalid': 332,\n", @@ -2902,7 +2916,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1438858309727244,\n", " 'Cohen': 0.17958979489744875,\n", - " 'Spearman': 0.6947722013864978,\n", + " 'Spearman': 0.6986179274966334,\n", " 'Kendall': 0.5974775270838849,\n", " 'Krippendorff': 0.6088878412396672,\n", " 'Invalid': 1,\n", @@ -2949,7 +2963,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.2020930818199387,\n", " 'Cohen': 0.21798948480117553,\n", - " 'Spearman': 0.6308886758496952,\n", + " 'Spearman': 0.6264739506274926,\n", " 'Kendall': 0.5135673261706963,\n", " 'Krippendorff': 0.571737621630807,\n", " 'Invalid': 46,\n", @@ -2996,7 +3010,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05871015924257385,\n", " 'Cohen': -0.00012289317851843506,\n", - " 'Spearman': 0.6180548305505907,\n", + " 'Spearman': 0.6219216252080505,\n", " 'Kendall': 0.5212956259806314,\n", " 'Krippendorff': 0.29490611294803326,\n", " 'Invalid': 0,\n", @@ -3043,7 +3057,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'et': {'phi-4': {'metrics': {'Fleiss': 0.16558092638361183,\n", " 'Cohen': 0.18244334035304144,\n", - " 'Spearman': 0.649066914283782,\n", + " 'Spearman': 0.6566756846898585,\n", " 'Kendall': 0.5389754356719453,\n", " 'Krippendorff': 0.5261555326699758,\n", " 'Invalid': 0,\n", @@ -3090,7 +3104,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0895834113111502,\n", " 'Cohen': 0.12669226203013995,\n", - " 'Spearman': 0.5886573583101743,\n", + " 'Spearman': 0.5956360590128252,\n", " 'Kendall': 0.49874009555449356,\n", " 'Krippendorff': 0.49507456049286813,\n", " 'Invalid': 0,\n", @@ -3137,7 +3151,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.24470925752722303,\n", " 'Cohen': 0.26033761882388673,\n", - " 'Spearman': 0.698458605424478,\n", + " 'Spearman': 0.7070158912394379,\n", " 'Kendall': 0.5901434719753905,\n", " 'Krippendorff': 0.6423805561344249,\n", " 'Invalid': 0,\n", @@ -3184,7 +3198,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.03454532837466557,\n", " 'Cohen': 0.09800315039283869,\n", - " 'Spearman': 0.6557414926861599,\n", + " 'Spearman': 0.65735345677687,\n", " 'Kendall': 0.5626698305604065,\n", " 'Krippendorff': 0.5419859856252587,\n", " 'Invalid': 2,\n", @@ -3231,7 +3245,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.10319149451923962,\n", " 'Cohen': 0.1272540268171396,\n", - " 'Spearman': 0.6445511400063554,\n", + " 'Spearman': 0.6456343157414739,\n", " 'Kendall': 0.5396706764523056,\n", " 'Krippendorff': 0.5212560060610887,\n", " 'Invalid': 0,\n", @@ -3278,7 +3292,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.14657761817663142,\n", " 'Cohen': -0.05280118333817585,\n", - " 'Spearman': 0.6667264909459095,\n", + " 'Spearman': 0.6763546819274491,\n", " 'Kendall': 0.5673434199162278,\n", " 'Krippendorff': 0.16944107152963261,\n", " 'Invalid': 0,\n", @@ -3325,7 +3339,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.11110305788897666,\n", " 'Cohen': -0.0446954277822198,\n", - " 'Spearman': 0.702773253534524,\n", + " 'Spearman': 0.707520571044935,\n", " 'Kendall': 0.6013422169595338,\n", " 'Krippendorff': 0.2842703490147853,\n", " 'Invalid': 0,\n", @@ -3372,7 +3386,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.12574630984276067,\n", " 'Cohen': 0.16326854003803093,\n", - " 'Spearman': 0.6628129312802449,\n", + " 'Spearman': 0.6644256929785255,\n", " 'Kendall': 0.5696115657462317,\n", " 'Krippendorff': 0.5630571153102941,\n", " 'Invalid': 0,\n", @@ -3419,7 +3433,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 0, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.08448804414469645,\n", " 'Cohen': 0.009214395742893178,\n", - " 'Spearman': 0.35903676649546806,\n", + " 'Spearman': 0.3432645593736001,\n", " 'Kendall': 0.2917905871150624,\n", " 'Krippendorff': -0.13586505052232534,\n", " 'Invalid': 310,\n", @@ -3466,7 +3480,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.11180771628168028,\n", " 'Cohen': 0.15448403553349477,\n", - " 'Spearman': 0.6913342173111973,\n", + " 'Spearman': 0.6971600041831558,\n", " 'Kendall': 0.5944550436574051,\n", " 'Krippendorff': 0.5741091963068756,\n", " 'Invalid': 3,\n", @@ -3513,7 +3527,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.10729452617254405,\n", " 'Cohen': 0.12806939144981844,\n", - " 'Spearman': 0.6300324475976044,\n", + " 'Spearman': 0.635154729662691,\n", " 'Kendall': 0.5121721384494948,\n", " 'Krippendorff': 0.508324808469824,\n", " 'Invalid': 47,\n", @@ -3560,7 +3574,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05602272754771406,\n", " 'Cohen': 0.004294097783132167,\n", - " 'Spearman': 0.6099479753396261,\n", + " 'Spearman': 0.6165461936907847,\n", " 'Kendall': 0.5154962710136125,\n", " 'Krippendorff': 0.2516655391841167,\n", " 'Invalid': 0,\n", @@ -3607,7 +3621,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'fi': {'phi-4': {'metrics': {'Fleiss': 0.17799737596005955,\n", " 'Cohen': 0.19335705812574144,\n", - " 'Spearman': 0.6342030573922413,\n", + " 'Spearman': 0.6431971250533177,\n", " 'Kendall': 0.527903153069031,\n", " 'Krippendorff': 0.5198763506255754,\n", " 'Invalid': 1,\n", @@ -3654,7 +3668,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0799419224278231,\n", " 'Cohen': 0.12044397564366882,\n", - " 'Spearman': 0.5693590267173353,\n", + " 'Spearman': 0.5753257918187117,\n", " 'Kendall': 0.48002557414113606,\n", " 'Krippendorff': 0.49056819129065155,\n", " 'Invalid': 0,\n", @@ -3701,7 +3715,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.23305220144665115,\n", " 'Cohen': 0.24754064876521797,\n", - " 'Spearman': 0.6863272805635778,\n", + " 'Spearman': 0.692986433376017,\n", " 'Kendall': 0.5800932515445063,\n", " 'Krippendorff': 0.6251044833983963,\n", " 'Invalid': 0,\n", @@ -3748,7 +3762,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.0559095674833824,\n", " 'Cohen': 0.1154658642773011,\n", - " 'Spearman': 0.6137039308126477,\n", + " 'Spearman': 0.6193441128720899,\n", " 'Kendall': 0.5287490739901568,\n", " 'Krippendorff': 0.5101093034583393,\n", " 'Invalid': 0,\n", @@ -3795,7 +3809,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.12866837991323654,\n", " 'Cohen': 0.15145594322885858,\n", - " 'Spearman': 0.6380991240400192,\n", + " 'Spearman': 0.6436732674970624,\n", " 'Kendall': 0.5358767107250354,\n", " 'Krippendorff': 0.546653150132477,\n", " 'Invalid': 0,\n", @@ -3842,7 +3856,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.12265671469961818,\n", " 'Cohen': -0.036134870459898494,\n", - " 'Spearman': 0.6535279126776141,\n", + " 'Spearman': 0.6585517101461686,\n", " 'Kendall': 0.5525679800008736,\n", " 'Krippendorff': 0.20785813017563182,\n", " 'Invalid': 0,\n", @@ -3889,7 +3903,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.08193308477857468,\n", " 'Cohen': -0.017636724647494217,\n", - " 'Spearman': 0.6953442146130218,\n", + " 'Spearman': 0.6984872995286274,\n", " 'Kendall': 0.59499080583488,\n", " 'Krippendorff': 0.2740359826391312,\n", " 'Invalid': 2,\n", @@ -3936,7 +3950,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.17134305648705192,\n", " 'Cohen': 0.20430996366712162,\n", - " 'Spearman': 0.678894143442974,\n", + " 'Spearman': 0.6828395768356903,\n", " 'Kendall': 0.5839683952485305,\n", " 'Krippendorff': 0.5905102998926354,\n", " 'Invalid': 0,\n", @@ -3983,7 +3997,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.11366938363416972,\n", " 'Cohen': -0.03674751272293797,\n", - " 'Spearman': 0.3988427405913572,\n", + " 'Spearman': 0.40082114874913743,\n", " 'Kendall': 0.3200064356928644,\n", " 'Krippendorff': -0.04394949941349213,\n", " 'Invalid': 286,\n", @@ -4030,7 +4044,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.08210228519360778,\n", " 'Cohen': 0.1288029124834017,\n", - " 'Spearman': 0.6791722611224639,\n", + " 'Spearman': 0.6791813625289526,\n", " 'Kendall': 0.582352940026658,\n", " 'Krippendorff': 0.5755812159992642,\n", " 'Invalid': 3,\n", @@ -4077,7 +4091,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.10361815797050448,\n", " 'Cohen': 0.12953350316024914,\n", - " 'Spearman': 0.639146462938812,\n", + " 'Spearman': 0.6454197303558545,\n", " 'Kendall': 0.5179859753459962,\n", " 'Krippendorff': 0.5398566751000995,\n", " 'Invalid': 44,\n", @@ -4124,7 +4138,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06677233617400673,\n", " 'Cohen': -0.004852380215398355,\n", - " 'Spearman': 0.639125951028085,\n", + " 'Spearman': 0.6450452722543237,\n", " 'Kendall': 0.5423502940229661,\n", " 'Krippendorff': 0.27209767614373526,\n", " 'Invalid': 0,\n", @@ -4171,7 +4185,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sh': {'phi-4': {'metrics': {'Fleiss': 0.20313725490196075,\n", " 'Cohen': 0.21800467653936095,\n", - " 'Spearman': 0.6485362703210477,\n", + " 'Spearman': 0.6554663925488476,\n", " 'Kendall': 0.5376677050331645,\n", " 'Krippendorff': 0.5292993999160559,\n", " 'Invalid': 0,\n", @@ -4218,7 +4232,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09437125808984881,\n", " 'Cohen': 0.13390968365129197,\n", - " 'Spearman': 0.6234968231456077,\n", + " 'Spearman': 0.623576292531096,\n", " 'Kendall': 0.5335544734338298,\n", " 'Krippendorff': 0.5119142304104873,\n", " 'Invalid': 0,\n", @@ -4265,7 +4279,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.22750487124510738,\n", " 'Cohen': 0.24382329009716186,\n", - " 'Spearman': 0.6662629599356265,\n", + " 'Spearman': 0.674819904250106,\n", " 'Kendall': 0.5579494304454636,\n", " 'Krippendorff': 0.6060795671633568,\n", " 'Invalid': 0,\n", @@ -4312,7 +4326,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.044906996428497666,\n", " 'Cohen': 0.10380213958128537,\n", - " 'Spearman': 0.6222135974917152,\n", + " 'Spearman': 0.6286083427715494,\n", " 'Kendall': 0.5321687342666803,\n", " 'Krippendorff': 0.5114430343127077,\n", " 'Invalid': 1,\n", @@ -4359,7 +4373,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.13513884800314005,\n", " 'Cohen': 0.15801239031892889,\n", - " 'Spearman': 0.6704917167857553,\n", + " 'Spearman': 0.6761963882518163,\n", " 'Kendall': 0.5652203558661212,\n", " 'Krippendorff': 0.5603545852266225,\n", " 'Invalid': 0,\n", @@ -4406,7 +4420,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.13296647354003543,\n", " 'Cohen': -0.048800082582683535,\n", - " 'Spearman': 0.6212210274224423,\n", + " 'Spearman': 0.6291692291598887,\n", " 'Kendall': 0.5339937642598233,\n", " 'Krippendorff': 0.20112831546952759,\n", " 'Invalid': 0,\n", @@ -4453,7 +4467,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.12300337885021087,\n", " 'Cohen': -0.05456335967088055,\n", - " 'Spearman': 0.686629951810602,\n", + " 'Spearman': 0.6918590835361813,\n", " 'Kendall': 0.5889710515818496,\n", " 'Krippendorff': 0.26307015332750805,\n", " 'Invalid': 1,\n", @@ -4500,7 +4514,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.14664917900471663,\n", " 'Cohen': 0.1775779085030872,\n", - " 'Spearman': 0.6691108537743504,\n", + " 'Spearman': 0.6773996874892033,\n", " 'Kendall': 0.5719402254843323,\n", " 'Krippendorff': 0.5747099192335852,\n", " 'Invalid': 0,\n", @@ -4547,7 +4561,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.06764089614785368,\n", " 'Cohen': 0.005285920230658325,\n", - " 'Spearman': 0.4309070296556221,\n", + " 'Spearman': 0.44308363524283045,\n", " 'Kendall': 0.3408113280859837,\n", " 'Krippendorff': 0.03154292540336412,\n", " 'Invalid': 268,\n", @@ -4594,7 +4608,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13519132510881204,\n", " 'Cohen': 0.1757686264045777,\n", - " 'Spearman': 0.6953792914578804,\n", + " 'Spearman': 0.6984476056476294,\n", " 'Kendall': 0.5956052208779614,\n", " 'Krippendorff': 0.5863041455081363,\n", " 'Invalid': 1,\n", @@ -4641,7 +4655,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.12891077460475328,\n", " 'Cohen': 0.14958112548474,\n", - " 'Spearman': 0.6770303827279359,\n", + " 'Spearman': 0.6871907106901511,\n", " 'Kendall': 0.5587995012295227,\n", " 'Krippendorff': 0.5777755460904532,\n", " 'Invalid': 52,\n", @@ -4688,7 +4702,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.0794071027507834,\n", " 'Cohen': -0.018040762171525282,\n", - " 'Spearman': 0.6256620256239181,\n", + " 'Spearman': 0.6309446962555323,\n", " 'Kendall': 0.5350801903599895,\n", " 'Krippendorff': 0.25703937818941536,\n", " 'Invalid': 0,\n", @@ -4735,7 +4749,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'hy': {'phi-4': {'metrics': {'Fleiss': 0.2397968438236895,\n", " 'Cohen': 0.2522525201463022,\n", - " 'Spearman': 0.5669584085235572,\n", + " 'Spearman': 0.5719106287459507,\n", " 'Kendall': 0.47307198544618234,\n", " 'Krippendorff': 0.5424462022354862,\n", " 'Invalid': 0,\n", @@ -4782,7 +4796,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09791424817257521,\n", " 'Cohen': 0.13659873115412235,\n", - " 'Spearman': 0.5336732922423744,\n", + " 'Spearman': 0.5381011974727566,\n", " 'Kendall': 0.4496145499577497,\n", " 'Krippendorff': 0.4671161675407054,\n", " 'Invalid': 0,\n", @@ -4829,7 +4843,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.12349026374168107,\n", " 'Cohen': 0.15545062099219054,\n", - " 'Spearman': 0.6612737318527119,\n", + " 'Spearman': 0.6660551580883765,\n", " 'Kendall': 0.5556493811588552,\n", " 'Krippendorff': 0.5424010832912614,\n", " 'Invalid': 0,\n", @@ -4876,7 +4890,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.05725669996179251,\n", " 'Cohen': 0.12007103244494255,\n", - " 'Spearman': 0.652252081802573,\n", + " 'Spearman': 0.6564826152980173,\n", " 'Kendall': 0.5656859024069502,\n", " 'Krippendorff': 0.5376077874299889,\n", " 'Invalid': 0,\n", @@ -4923,7 +4937,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1589883393846268,\n", " 'Cohen': 0.17912296319232113,\n", - " 'Spearman': 0.6227050864927768,\n", + " 'Spearman': 0.624367789831242,\n", " 'Kendall': 0.5239263090857502,\n", " 'Krippendorff': 0.5471387382826456,\n", " 'Invalid': 0,\n", @@ -4970,7 +4984,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.1027168472281418,\n", " 'Cohen': -0.03391169391187976,\n", - " 'Spearman': 0.5663583468352424,\n", + " 'Spearman': 0.5656676125374659,\n", " 'Kendall': 0.4789207970978006,\n", " 'Krippendorff': 0.17301426327090852,\n", " 'Invalid': 0,\n", @@ -5017,7 +5031,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10206020479620773,\n", " 'Cohen': -0.03547058688200244,\n", - " 'Spearman': 0.7091625861986491,\n", + " 'Spearman': 0.7120379814384182,\n", " 'Kendall': 0.6108350486043852,\n", " 'Krippendorff': 0.2849834704403197,\n", " 'Invalid': 0,\n", @@ -5064,7 +5078,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.12885555303953578,\n", " 'Cohen': 0.1672414715653988,\n", - " 'Spearman': 0.6572753228987811,\n", + " 'Spearman': 0.6592964222577726,\n", " 'Kendall': 0.5633211515611941,\n", " 'Krippendorff': 0.5492512346769144,\n", " 'Invalid': 0,\n", @@ -5111,7 +5125,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.09615611598536411,\n", " 'Cohen': -0.007266811279826424,\n", - " 'Spearman': 0.36282427871261896,\n", + " 'Spearman': 0.3611669042541707,\n", " 'Kendall': 0.2919531005969239,\n", " 'Krippendorff': -0.16647940523774873,\n", " 'Invalid': 257,\n", @@ -5158,7 +5172,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.09387222600823615,\n", " 'Cohen': 0.15471573031484376,\n", - " 'Spearman': 0.6602913120088547,\n", + " 'Spearman': 0.6657677007442705,\n", " 'Kendall': 0.5702839750007359,\n", " 'Krippendorff': 0.5366892892316792,\n", " 'Invalid': 1,\n", @@ -5205,7 +5219,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.07604812249362014,\n", " 'Cohen': 0.10516432416033317,\n", - " 'Spearman': 0.6155965883059586,\n", + " 'Spearman': 0.6271738753182688,\n", " 'Kendall': 0.498526101961292,\n", " 'Krippendorff': 0.4891358183092449,\n", " 'Invalid': 22,\n", @@ -5252,7 +5266,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05427025966220607,\n", " 'Cohen': 0.007510045725370507,\n", - " 'Spearman': 0.6092376964822472,\n", + " 'Spearman': 0.6134831783342036,\n", " 'Kendall': 0.5163917469910526,\n", " 'Krippendorff': 0.23313843826102343,\n", " 'Invalid': 0,\n", @@ -5299,7 +5313,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'hr': {'phi-4': {'metrics': {'Fleiss': 0.18593838287348957,\n", " 'Cohen': 0.2017650215658603,\n", - " 'Spearman': 0.6651474649282079,\n", + " 'Spearman': 0.6703029479182365,\n", " 'Kendall': 0.5535088164082764,\n", " 'Krippendorff': 0.5387423856085166,\n", " 'Invalid': 0,\n", @@ -5346,7 +5360,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08246173601474638,\n", " 'Cohen': 0.12157714195070679,\n", - " 'Spearman': 0.5894191103512997,\n", + " 'Spearman': 0.5930093633035253,\n", " 'Kendall': 0.4999180079987575,\n", " 'Krippendorff': 0.48423877672580706,\n", " 'Invalid': 0,\n", @@ -5393,7 +5407,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.21941927177730838,\n", " 'Cohen': 0.23799436751707082,\n", - " 'Spearman': 0.682107514098201,\n", + " 'Spearman': 0.6877385523570422,\n", " 'Kendall': 0.5751164784719149,\n", " 'Krippendorff': 0.6145470449477848,\n", " 'Invalid': 0,\n", @@ -5440,7 +5454,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.04866601835017551,\n", " 'Cohen': 0.10303622238721932,\n", - " 'Spearman': 0.66474270625812,\n", + " 'Spearman': 0.6687948306293467,\n", " 'Kendall': 0.5710579407822272,\n", " 'Krippendorff': 0.5460460354719934,\n", " 'Invalid': 2,\n", @@ -5487,7 +5501,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.14534739189280807,\n", " 'Cohen': 0.1664642150428085,\n", - " 'Spearman': 0.6463164231966281,\n", + " 'Spearman': 0.6511385385355974,\n", " 'Kendall': 0.5447181509301078,\n", " 'Krippendorff': 0.5363744809754563,\n", " 'Invalid': 0,\n", @@ -5534,7 +5548,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11584124197843347,\n", " 'Cohen': -0.03606947945812666,\n", - " 'Spearman': 0.618282055489546,\n", + " 'Spearman': 0.6231946820096644,\n", " 'Kendall': 0.5207517850859654,\n", " 'Krippendorff': 0.20648828674933994,\n", " 'Invalid': 0,\n", @@ -5581,7 +5595,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.1331501826889906,\n", " 'Cohen': -0.06239818684042797,\n", - " 'Spearman': 0.7000555674777095,\n", + " 'Spearman': 0.7040813452227204,\n", " 'Kendall': 0.6012108922781682,\n", " 'Krippendorff': 0.2501343749250968,\n", " 'Invalid': 2,\n", @@ -5628,7 +5642,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.19319174527629376,\n", " 'Cohen': 0.22313521500813704,\n", - " 'Spearman': 0.7013084062851969,\n", + " 'Spearman': 0.706880756986347,\n", " 'Kendall': 0.6061847072113131,\n", " 'Krippendorff': 0.608756125799004,\n", " 'Invalid': 0,\n", @@ -5675,7 +5689,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.05163297045101089,\n", " 'Cohen': 0.018938368089139956,\n", - " 'Spearman': 0.47170730592701166,\n", + " 'Spearman': 0.4622799973940039,\n", " 'Kendall': 0.3828313547913429,\n", " 'Krippendorff': 0.06651671266102122,\n", " 'Invalid': 257,\n", @@ -5722,7 +5736,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.11955089247453832,\n", " 'Cohen': 0.16004689717588494,\n", - " 'Spearman': 0.6872712557829016,\n", + " 'Spearman': 0.6908199159401305,\n", " 'Kendall': 0.591741414853888,\n", " 'Krippendorff': 0.5812350581883734,\n", " 'Invalid': 4,\n", @@ -5769,7 +5783,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1646630487050903,\n", " 'Cohen': 0.18366870399234114,\n", - " 'Spearman': 0.6445035347269901,\n", + " 'Spearman': 0.646811506963114,\n", " 'Kendall': 0.5205301206489735,\n", " 'Krippendorff': 0.5550466139609931,\n", " 'Invalid': 42,\n", @@ -5816,7 +5830,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.08432542162710817,\n", " 'Cohen': -0.023880343333050114,\n", - " 'Spearman': 0.6302631298549143,\n", + " 'Spearman': 0.6354242827810219,\n", " 'Kendall': 0.5361032121164497,\n", " 'Krippendorff': 0.26981074112728554,\n", " 'Invalid': 0,\n", @@ -5863,7 +5877,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}}},\n", " 'el': {'phi-4': {'metrics': {'Fleiss': 0.2460012984713451,\n", " 'Cohen': 0.2564785309994617,\n", - " 'Spearman': 0.6149812367399186,\n", + " 'Spearman': 0.6183578406474384,\n", " 'Kendall': 0.5147457996840178,\n", " 'Krippendorff': 0.5752421391728113,\n", " 'Invalid': 0,\n", @@ -5910,7 +5924,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.1771981715514923,\n", " 'Cohen': 0.2018934980475129,\n", - " 'Spearman': 0.5817754112387205,\n", + " 'Spearman': 0.587040293888872,\n", " 'Kendall': 0.4918442527293123,\n", " 'Krippendorff': 0.5266164552917545,\n", " 'Invalid': 1,\n", @@ -5957,7 +5971,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.16832014935197043,\n", " 'Cohen': 0.19086827741659051,\n", - " 'Spearman': 0.6826122610472766,\n", + " 'Spearman': 0.6899182854708372,\n", " 'Kendall': 0.5727902802931757,\n", " 'Krippendorff': 0.5756889144367185,\n", " 'Invalid': 0,\n", @@ -6004,7 +6018,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.04958318175920954,\n", " 'Cohen': 0.10577360351174481,\n", - " 'Spearman': 0.650306271528812,\n", + " 'Spearman': 0.6545541939296697,\n", " 'Kendall': 0.5619388950393851,\n", " 'Krippendorff': 0.5272706955658846,\n", " 'Invalid': 2,\n", @@ -6051,7 +6065,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1653007310929532,\n", " 'Cohen': 0.17850163496701033,\n", - " 'Spearman': 0.6236711282848736,\n", + " 'Spearman': 0.6307567152373387,\n", " 'Kendall': 0.5220084352396945,\n", " 'Krippendorff': 0.5650156294194755,\n", " 'Invalid': 1,\n", @@ -6098,7 +6112,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.16528532053162986,\n", " 'Cohen': -0.07840169517178741,\n", - " 'Spearman': 0.6373615668562864,\n", + " 'Spearman': 0.639703838313411,\n", " 'Kendall': 0.5455717661232881,\n", " 'Krippendorff': 0.19151187487166954,\n", " 'Invalid': 1,\n", @@ -6145,7 +6159,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.12637133898513095,\n", " 'Cohen': -0.05556131860598312,\n", - " 'Spearman': 0.7018148733448731,\n", + " 'Spearman': 0.7050367116075933,\n", " 'Kendall': 0.601641156096354,\n", " 'Krippendorff': 0.25665488525104974,\n", " 'Invalid': 0,\n", @@ -6192,7 +6206,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.15699472439512457,\n", " 'Cohen': 0.1886243056288437,\n", - " 'Spearman': 0.6991164590758019,\n", + " 'Spearman': 0.7046284888610606,\n", " 'Kendall': 0.6005552826317324,\n", " 'Krippendorff': 0.5950591954687967,\n", " 'Invalid': 0,\n", @@ -6239,7 +6253,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.08529318875671127,\n", " 'Cohen': -0.003426124197002167,\n", - " 'Spearman': 0.48318723485930276,\n", + " 'Spearman': 0.48375095770315674,\n", " 'Kendall': 0.39485328447948376,\n", " 'Krippendorff': 0.014744904722679197,\n", " 'Invalid': 269,\n", @@ -6286,7 +6300,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.12044377684393867,\n", " 'Cohen': 0.15942500036934715,\n", - " 'Spearman': 0.6901680704518787,\n", + " 'Spearman': 0.6951791157786579,\n", " 'Kendall': 0.5928388865688672,\n", " 'Krippendorff': 0.5843584348092454,\n", " 'Invalid': 3,\n", @@ -6333,7 +6347,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08195292066259803,\n", " 'Cohen': 0.11068636548003341,\n", - " 'Spearman': 0.6517214272250328,\n", + " 'Spearman': 0.6486097317978743,\n", " 'Kendall': 0.5329606763614796,\n", " 'Krippendorff': 0.5252201930620052,\n", " 'Invalid': 43,\n", @@ -6380,7 +6394,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05852845247874627,\n", " 'Cohen': 0.0022267429074114276,\n", - " 'Spearman': 0.6103770080773455,\n", + " 'Spearman': 0.6157309164701358,\n", " 'Kendall': 0.5163740782736762,\n", " 'Krippendorff': 0.25520791456964087,\n", " 'Invalid': 1,\n", @@ -6427,7 +6441,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'mt': {'phi-4': {'metrics': {'Fleiss': 0.10125982667258987,\n", " 'Cohen': 0.1265873508057207,\n", - " 'Spearman': 0.6047382203323012,\n", + " 'Spearman': 0.6152128834145014,\n", " 'Kendall': 0.4975008776453506,\n", " 'Krippendorff': 0.42555986116868505,\n", " 'Invalid': 0,\n", @@ -6474,7 +6488,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09432820008324189,\n", " 'Cohen': 0.13452220824113048,\n", - " 'Spearman': 0.551924449177352,\n", + " 'Spearman': 0.5602689093473517,\n", " 'Kendall': 0.4681067128289585,\n", " 'Krippendorff': 0.4527712675188118,\n", " 'Invalid': 0,\n", @@ -6521,7 +6535,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.24278557478863166,\n", " 'Cohen': 0.25870684577530356,\n", - " 'Spearman': 0.6655855192300131,\n", + " 'Spearman': 0.674016633289588,\n", " 'Kendall': 0.5599140351700173,\n", " 'Krippendorff': 0.6104227383222653,\n", " 'Invalid': 0,\n", @@ -6568,7 +6582,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.08144054771196177,\n", " 'Cohen': 0.13407501742076555,\n", - " 'Spearman': 0.6477552565116212,\n", + " 'Spearman': 0.6528755007075321,\n", " 'Kendall': 0.5596339297846159,\n", " 'Krippendorff': 0.526443572831842,\n", " 'Invalid': 1,\n", @@ -6615,7 +6629,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.08687298029054705,\n", " 'Cohen': 0.11604727190741015,\n", - " 'Spearman': 0.6525056448027281,\n", + " 'Spearman': 0.6592188711650635,\n", " 'Kendall': 0.5500111427401194,\n", " 'Krippendorff': 0.5035969951890261,\n", " 'Invalid': 0,\n", @@ -6662,7 +6676,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10950949301923314,\n", " 'Cohen': -0.030618353008952104,\n", - " 'Spearman': 0.5889575932442084,\n", + " 'Spearman': 0.5929470487557785,\n", " 'Kendall': 0.49910185635521637,\n", " 'Krippendorff': 0.17391390484687053,\n", " 'Invalid': 0,\n", @@ -6709,7 +6723,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09101181651801447,\n", " 'Cohen': -0.026912535396279358,\n", - " 'Spearman': 0.670724761228237,\n", + " 'Spearman': 0.6722684801511977,\n", " 'Kendall': 0.5698816760065639,\n", " 'Krippendorff': 0.25880841953879496,\n", " 'Invalid': 0,\n", @@ -6756,7 +6770,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.14062617539530897,\n", " 'Cohen': 0.17554739784553064,\n", - " 'Spearman': 0.6551265609313056,\n", + " 'Spearman': 0.6596022979210151,\n", " 'Kendall': 0.5606481638863476,\n", " 'Krippendorff': 0.5544345991450169,\n", " 'Invalid': 0,\n", @@ -6803,7 +6817,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.12671966314566768,\n", " 'Cohen': -0.03884513264463729,\n", - " 'Spearman': 0.3837851816455217,\n", + " 'Spearman': 0.38704970527708393,\n", " 'Kendall': 0.3106665554881096,\n", " 'Krippendorff': -0.0952859549588736,\n", " 'Invalid': 190,\n", @@ -6850,7 +6864,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.08249253179396931,\n", " 'Cohen': 0.13606010016694503,\n", - " 'Spearman': 0.6545566960660002,\n", + " 'Spearman': 0.6580776465133312,\n", " 'Kendall': 0.5613381454769161,\n", " 'Krippendorff': 0.5448734020843023,\n", " 'Invalid': 3,\n", @@ -6897,7 +6911,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.058144281798565414,\n", " 'Cohen': 0.09071654163963261,\n", - " 'Spearman': 0.6436781180673005,\n", + " 'Spearman': 0.6470376646053079,\n", " 'Kendall': 0.5237927316725144,\n", " 'Krippendorff': 0.47941672565092575,\n", " 'Invalid': 35,\n", @@ -6944,7 +6958,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07354620919454938,\n", " 'Cohen': -0.009348351498016383,\n", - " 'Spearman': 0.6221080233324323,\n", + " 'Spearman': 0.6270882233604248,\n", " 'Kendall': 0.5313440114075515,\n", " 'Krippendorff': 0.2563880474857083,\n", " 'Invalid': 0,\n", @@ -6991,7 +7005,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'eu': {'phi-4': {'metrics': {'Fleiss': 0.07952690056150694,\n", " 'Cohen': 0.10907680521895835,\n", - " 'Spearman': 0.6180019572318131,\n", + " 'Spearman': 0.6268184296895588,\n", " 'Kendall': 0.5195049696495918,\n", " 'Krippendorff': 0.42221154011575124,\n", " 'Invalid': 0,\n", @@ -7038,7 +7052,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08891727556077873,\n", " 'Cohen': 0.1314166577360365,\n", - " 'Spearman': 0.57295782247282,\n", + " 'Spearman': 0.5722588447139946,\n", " 'Kendall': 0.48902514193568963,\n", " 'Krippendorff': 0.4837633372101541,\n", " 'Invalid': 0,\n", @@ -7085,7 +7099,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.1790498442367601,\n", " 'Cohen': 0.19624849882765583,\n", - " 'Spearman': 0.7005631599116607,\n", + " 'Spearman': 0.7045551180816955,\n", " 'Kendall': 0.5915864361673783,\n", " 'Krippendorff': 0.614899952731007,\n", " 'Invalid': 0,\n", @@ -7132,7 +7146,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.06382714387766732,\n", " 'Cohen': 0.12567925586432283,\n", - " 'Spearman': 0.6439700271737424,\n", + " 'Spearman': 0.6492218313912486,\n", " 'Kendall': 0.5604988960440244,\n", " 'Krippendorff': 0.5419640178805267,\n", " 'Invalid': 0,\n", @@ -7179,7 +7193,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.08107117102802595,\n", " 'Cohen': 0.113404590522731,\n", - " 'Spearman': 0.673814758330447,\n", + " 'Spearman': 0.6764856256669906,\n", " 'Kendall': 0.5729043431302293,\n", " 'Krippendorff': 0.4927233874982814,\n", " 'Invalid': 0,\n", @@ -7226,7 +7240,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.1343801382329731,\n", " 'Cohen': -0.05206964371493572,\n", - " 'Spearman': 0.5858514944164387,\n", + " 'Spearman': 0.5848071285993002,\n", " 'Kendall': 0.4929225020300007,\n", " 'Krippendorff': 0.13304125267497213,\n", " 'Invalid': 0,\n", @@ -7273,7 +7287,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.0949216534882179,\n", " 'Cohen': -0.032095040194005,\n", - " 'Spearman': 0.6991448136718292,\n", + " 'Spearman': 0.7022592249353097,\n", " 'Kendall': 0.6003642948435497,\n", " 'Krippendorff': 0.31717865010498947,\n", " 'Invalid': 0,\n", @@ -7320,7 +7334,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.13265476220544037,\n", " 'Cohen': 0.1629870478066091,\n", - " 'Spearman': 0.6761149859148676,\n", + " 'Spearman': 0.6822382470653958,\n", " 'Kendall': 0.5775457944664929,\n", " 'Krippendorff': 0.5708483338693953,\n", " 'Invalid': 0,\n", @@ -7367,7 +7381,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.19492782385259777,\n", " 'Cohen': -0.04881000403388458,\n", - " 'Spearman': 0.32360423488613255,\n", + " 'Spearman': 0.33978824081969095,\n", " 'Kendall': 0.2643803147943323,\n", " 'Krippendorff': -0.3375390874502997,\n", " 'Invalid': 208,\n", @@ -7414,7 +7428,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.09432034867883411,\n", " 'Cohen': 0.14826437812219806,\n", - " 'Spearman': 0.6967135599131963,\n", + " 'Spearman': 0.7003532938236706,\n", " 'Kendall': 0.6053281866161742,\n", " 'Krippendorff': 0.569808058165949,\n", " 'Invalid': 1,\n", @@ -7461,7 +7475,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.10289029829743318,\n", " 'Cohen': 0.12956291960655597,\n", - " 'Spearman': 0.6899368472953464,\n", + " 'Spearman': 0.6844696943568959,\n", " 'Kendall': 0.5687732579993986,\n", " 'Krippendorff': 0.5486628728601476,\n", " 'Invalid': 37,\n", @@ -7508,7 +7522,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.10390632856130268,\n", " 'Cohen': -0.03855756406647304,\n", - " 'Spearman': 0.6182428548924105,\n", + " 'Spearman': 0.6192926162199824,\n", " 'Kendall': 0.5293400040267092,\n", " 'Krippendorff': 0.21851201987705526,\n", " 'Invalid': 0,\n", @@ -7555,7 +7569,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'da': {'phi-4': {'metrics': {'Fleiss': 0.195410216794434,\n", " 'Cohen': 0.2074255386181324,\n", - " 'Spearman': 0.6301690297786188,\n", + " 'Spearman': 0.6355681406117013,\n", " 'Kendall': 0.5251505641675952,\n", " 'Krippendorff': 0.5354316959369512,\n", " 'Invalid': 0,\n", @@ -7602,7 +7616,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09264381499247225,\n", " 'Cohen': 0.1336004737842562,\n", - " 'Spearman': 0.5901238831650634,\n", + " 'Spearman': 0.5938060125908852,\n", " 'Kendall': 0.49887871329901307,\n", " 'Krippendorff': 0.4900934927433027,\n", " 'Invalid': 0,\n", @@ -7649,7 +7663,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.26755379936854745,\n", " 'Cohen': 0.28242254028948655,\n", - " 'Spearman': 0.6791212156121506,\n", + " 'Spearman': 0.6878616785100714,\n", " 'Kendall': 0.5721703483907488,\n", " 'Krippendorff': 0.6208962559213441,\n", " 'Invalid': 0,\n", @@ -7696,7 +7710,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.07520059712632951,\n", " 'Cohen': 0.13827993254637427,\n", - " 'Spearman': 0.6150475368389057,\n", + " 'Spearman': 0.6200934109244058,\n", " 'Kendall': 0.5302804375325604,\n", " 'Krippendorff': 0.5210792107694335,\n", " 'Invalid': 0,\n", @@ -7743,7 +7757,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.14748246796706013,\n", " 'Cohen': 0.16998843166418776,\n", - " 'Spearman': 0.6630716603647894,\n", + " 'Spearman': 0.6654808023512272,\n", " 'Kendall': 0.5586203824945674,\n", " 'Krippendorff': 0.5649995577519957,\n", " 'Invalid': 0,\n", @@ -7790,7 +7804,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.13314893973682004,\n", " 'Cohen': -0.045460771967035685,\n", - " 'Spearman': 0.6585723328688602,\n", + " 'Spearman': 0.662467179979225,\n", " 'Kendall': 0.5624141706737313,\n", " 'Krippendorff': 0.22062391878707543,\n", " 'Invalid': 0,\n", @@ -7837,7 +7851,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09771806603911055,\n", " 'Cohen': -0.033975385460035756,\n", - " 'Spearman': 0.7069734787859107,\n", + " 'Spearman': 0.7127071328403662,\n", " 'Kendall': 0.6072065660271785,\n", " 'Krippendorff': 0.3199817853165817,\n", " 'Invalid': 2,\n", @@ -7884,7 +7898,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.1883153743501902,\n", " 'Cohen': 0.21430843680111056,\n", - " 'Spearman': 0.6795642702526636,\n", + " 'Spearman': 0.6830487530099215,\n", " 'Kendall': 0.5830288176400527,\n", " 'Krippendorff': 0.5895484611425207,\n", " 'Invalid': 0,\n", @@ -7931,7 +7945,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': 0.04972586412395707,\n", " 'Cohen': 0.09774572230437284,\n", - " 'Spearman': 0.5319619030224955,\n", + " 'Spearman': 0.5253645190079144,\n", " 'Kendall': 0.436627898135033,\n", " 'Krippendorff': 0.2608998294100867,\n", " 'Invalid': 313,\n", @@ -7978,7 +7992,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13116213395543003,\n", " 'Cohen': 0.1662575602859162,\n", - " 'Spearman': 0.6774188380645677,\n", + " 'Spearman': 0.6804885069016888,\n", " 'Kendall': 0.5804370428335067,\n", " 'Krippendorff': 0.5871734481408813,\n", " 'Invalid': 1,\n", @@ -8025,7 +8039,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1633776573219277,\n", " 'Cohen': 0.18360137869391402,\n", - " 'Spearman': 0.6383587604624152,\n", + " 'Spearman': 0.6410946148477193,\n", " 'Kendall': 0.5240723067528528,\n", " 'Krippendorff': 0.5652410412076154,\n", " 'Invalid': 62,\n", @@ -8072,7 +8086,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.047993183032683885,\n", " 'Cohen': 0.009288799282746285,\n", - " 'Spearman': 0.6268338299932582,\n", + " 'Spearman': 0.6316753484512889,\n", " 'Kendall': 0.5296978703363052,\n", " 'Krippendorff': 0.2935555697729285,\n", " 'Invalid': 0,\n", @@ -8119,7 +8133,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'mk': {'phi-4': {'metrics': {'Fleiss': 0.1999462797482112,\n", " 'Cohen': 0.20991850829407743,\n", - " 'Spearman': 0.6127020778469268,\n", + " 'Spearman': 0.6185226818256321,\n", " 'Kendall': 0.5109324902946139,\n", " 'Krippendorff': 0.55607580063667,\n", " 'Invalid': 0,\n", @@ -8166,7 +8180,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09628411607156365,\n", " 'Cohen': 0.12798773513737138,\n", - " 'Spearman': 0.5855316446490235,\n", + " 'Spearman': 0.5891677577150736,\n", " 'Kendall': 0.4941335008312805,\n", " 'Krippendorff': 0.5059260886620232,\n", " 'Invalid': 0,\n", @@ -8213,7 +8227,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2103323895590118,\n", " 'Cohen': 0.2301147643266339,\n", - " 'Spearman': 0.682493511490174,\n", + " 'Spearman': 0.6916393105910902,\n", " 'Kendall': 0.5730862371703953,\n", " 'Krippendorff': 0.6014533800903612,\n", " 'Invalid': 0,\n", @@ -8260,7 +8274,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.0927170361920089,\n", " 'Cohen': 0.14433237271853983,\n", - " 'Spearman': 0.6598146452778264,\n", + " 'Spearman': 0.6648605725818062,\n", " 'Kendall': 0.5676040417937402,\n", " 'Krippendorff': 0.5535764891046631,\n", " 'Invalid': 0,\n", @@ -8307,7 +8321,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.13554134812433272,\n", " 'Cohen': 0.15902720409517856,\n", - " 'Spearman': 0.649385599793245,\n", + " 'Spearman': 0.651702042178097,\n", " 'Kendall': 0.5508695302619782,\n", " 'Krippendorff': 0.5499237084327541,\n", " 'Invalid': 0,\n", @@ -8354,7 +8368,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10284505260402657,\n", " 'Cohen': -0.03193457969358038,\n", - " 'Spearman': 0.6088558307004232,\n", + " 'Spearman': 0.6182319643008533,\n", " 'Kendall': 0.5140940674457272,\n", " 'Krippendorff': 0.21577674338053743,\n", " 'Invalid': 0,\n", @@ -8401,7 +8415,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10806220799004826,\n", " 'Cohen': -0.042270001462629825,\n", - " 'Spearman': 0.6961325607908384,\n", + " 'Spearman': 0.6982585706314755,\n", " 'Kendall': 0.5949970514249361,\n", " 'Krippendorff': 0.26727559242158794,\n", " 'Invalid': 0,\n", @@ -8448,7 +8462,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.17067937364171648,\n", " 'Cohen': 0.20073729779873595,\n", - " 'Spearman': 0.6834028549815762,\n", + " 'Spearman': 0.6886037723317114,\n", " 'Kendall': 0.5830509659904313,\n", " 'Krippendorff': 0.5660101264909707,\n", " 'Invalid': 0,\n", @@ -8495,7 +8509,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07126474176494511,\n", " 'Cohen': 0.0015464386427727073,\n", - " 'Spearman': 0.4489508922981743,\n", + " 'Spearman': 0.4584913379406041,\n", " 'Kendall': 0.35928307672266824,\n", " 'Krippendorff': 0.10195432185905617,\n", " 'Invalid': 313,\n", @@ -8542,7 +8556,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.13718694386651242,\n", " 'Cohen': 0.1783997430893507,\n", - " 'Spearman': 0.6893554335988565,\n", + " 'Spearman': 0.6944544899748724,\n", " 'Kendall': 0.5951667422379241,\n", " 'Krippendorff': 0.5752383349400148,\n", " 'Invalid': 2,\n", @@ -8589,7 +8603,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08507715215716172,\n", " 'Cohen': 0.1143448715226163,\n", - " 'Spearman': 0.6913950369625951,\n", + " 'Spearman': 0.6850548387772861,\n", " 'Kendall': 0.5742758174008288,\n", " 'Krippendorff': 0.538321737317955,\n", " 'Invalid': 31,\n", @@ -8636,7 +8650,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.062348067578078314,\n", " 'Cohen': -0.001844093611893971,\n", - " 'Spearman': 0.6265945125925181,\n", + " 'Spearman': 0.6336290552747106,\n", " 'Kendall': 0.5282998804119547,\n", " 'Krippendorff': 0.2428850955936387,\n", " 'Invalid': 0,\n", @@ -8683,7 +8697,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sv': {'phi-4': {'metrics': {'Fleiss': 0.22190244554852706,\n", " 'Cohen': 0.23316881709406723,\n", - " 'Spearman': 0.6409972792070059,\n", + " 'Spearman': 0.6466607960801041,\n", " 'Kendall': 0.5364517240781522,\n", " 'Krippendorff': 0.5507744996003143,\n", " 'Invalid': 1,\n", @@ -8730,7 +8744,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0953309728140191,\n", " 'Cohen': 0.13102335121944186,\n", - " 'Spearman': 0.5844193624778261,\n", + " 'Spearman': 0.591646329807139,\n", " 'Kendall': 0.492311755374174,\n", " 'Krippendorff': 0.4998396116720517,\n", " 'Invalid': 0,\n", @@ -8777,7 +8791,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.24514839631567767,\n", " 'Cohen': 0.2589956354641051,\n", - " 'Spearman': 0.6857349187964531,\n", + " 'Spearman': 0.6909643456979241,\n", " 'Kendall': 0.5733974461737357,\n", " 'Krippendorff': 0.6174201427982247,\n", " 'Invalid': 0,\n", @@ -8824,7 +8838,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.10992385851434973,\n", " 'Cohen': 0.16502869046310842,\n", - " 'Spearman': 0.6541627441093852,\n", + " 'Spearman': 0.6618758502020395,\n", " 'Kendall': 0.5640448158757305,\n", " 'Krippendorff': 0.5602324191771517,\n", " 'Invalid': 0,\n", @@ -8871,7 +8885,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1463215059786182,\n", " 'Cohen': 0.16881410909987626,\n", - " 'Spearman': 0.6605955757768099,\n", + " 'Spearman': 0.6638122072777445,\n", " 'Kendall': 0.5562228501219548,\n", " 'Krippendorff': 0.5748221186689149,\n", " 'Invalid': 0,\n", @@ -8918,7 +8932,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.12014741426759515,\n", " 'Cohen': -0.034408383535246,\n", - " 'Spearman': 0.6565686542488809,\n", + " 'Spearman': 0.6560692433514062,\n", " 'Kendall': 0.5609628214744885,\n", " 'Krippendorff': 0.21304468449698788,\n", " 'Invalid': 0,\n", @@ -8965,7 +8979,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.08115956759425302,\n", " 'Cohen': -0.0194693173416578,\n", - " 'Spearman': 0.7133046758662102,\n", + " 'Spearman': 0.7167548185707496,\n", " 'Kendall': 0.6116330346074136,\n", " 'Krippendorff': 0.32891568998633147,\n", " 'Invalid': 1,\n", @@ -9012,7 +9026,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.18615791582368416,\n", " 'Cohen': 0.2132636663683688,\n", - " 'Spearman': 0.6862152281692794,\n", + " 'Spearman': 0.6933402342854686,\n", " 'Kendall': 0.5863109850602262,\n", " 'Krippendorff': 0.5916554442574787,\n", " 'Invalid': 0,\n", @@ -9059,7 +9073,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.10310419338404508,\n", " 'Cohen': -0.035829759155394436,\n", - " 'Spearman': 0.5434219225852525,\n", + " 'Spearman': 0.5414884179588088,\n", " 'Kendall': 0.4406784757658552,\n", " 'Krippendorff': 0.17101678686484012,\n", " 'Invalid': 323,\n", @@ -9106,7 +9120,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.12878305028989678,\n", " 'Cohen': 0.1652203463288745,\n", - " 'Spearman': 0.6829730918908239,\n", + " 'Spearman': 0.6894573751544244,\n", " 'Kendall': 0.5860764105625597,\n", " 'Krippendorff': 0.5910578537109343,\n", " 'Invalid': 2,\n", @@ -9153,7 +9167,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1507098993034647,\n", " 'Cohen': 0.169010889292196,\n", - " 'Spearman': 0.6237927948607579,\n", + " 'Spearman': 0.6252027549817402,\n", " 'Kendall': 0.506935187019661,\n", " 'Krippendorff': 0.5549923848561078,\n", " 'Invalid': 67,\n", @@ -9200,7 +9214,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07672102756530522,\n", " 'Cohen': -0.016139796515983074,\n", - " 'Spearman': 0.6545755573192027,\n", + " 'Spearman': 0.6595696205389856,\n", " 'Kendall': 0.5569947268913363,\n", " 'Krippendorff': 0.3039385258684627,\n", " 'Invalid': 0,\n", @@ -9247,7 +9261,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'pl': {'phi-4': {'metrics': {'Fleiss': 0.20557117590481178,\n", " 'Cohen': 0.21682025414686212,\n", - " 'Spearman': 0.6459685747609837,\n", + " 'Spearman': 0.6578205554398511,\n", " 'Kendall': 0.5375851907089526,\n", " 'Krippendorff': 0.5524020541565153,\n", " 'Invalid': 0,\n", @@ -9294,7 +9308,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06613538655122309,\n", " 'Cohen': 0.1013593054040679,\n", - " 'Spearman': 0.5815503177914422,\n", + " 'Spearman': 0.5877767401802108,\n", " 'Kendall': 0.48956607654426004,\n", " 'Krippendorff': 0.49531447907705695,\n", " 'Invalid': 0,\n", @@ -9341,7 +9355,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.21720641072416633,\n", " 'Cohen': 0.23406056135572706,\n", - " 'Spearman': 0.6836704925572018,\n", + " 'Spearman': 0.6897283835821124,\n", " 'Kendall': 0.5735073455943227,\n", " 'Krippendorff': 0.6221903976765624,\n", " 'Invalid': 0,\n", @@ -9388,7 +9402,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.032253936730792396,\n", " 'Cohen': 0.09872247116026311,\n", - " 'Spearman': 0.6301334640702682,\n", + " 'Spearman': 0.6317048923049332,\n", " 'Kendall': 0.5461855152879105,\n", " 'Krippendorff': 0.5302628718324456,\n", " 'Invalid': 0,\n", @@ -9435,7 +9449,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.17105868884802278,\n", " 'Cohen': 0.1888502240442368,\n", - " 'Spearman': 0.6307656628604472,\n", + " 'Spearman': 0.6416288817552053,\n", " 'Kendall': 0.5274869390406203,\n", " 'Krippendorff': 0.5588116883636804,\n", " 'Invalid': 0,\n", @@ -9482,7 +9496,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.13162833169160412,\n", " 'Cohen': -0.040274607608992596,\n", - " 'Spearman': 0.6000756452633135,\n", + " 'Spearman': 0.6050722394407275,\n", " 'Kendall': 0.5090159311883685,\n", " 'Krippendorff': 0.1704380832089194,\n", " 'Invalid': 0,\n", @@ -9529,7 +9543,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.12245763636231424,\n", " 'Cohen': -0.054136372120974885,\n", - " 'Spearman': 0.7213696978190606,\n", + " 'Spearman': 0.7290343318484526,\n", " 'Kendall': 0.6229507408693421,\n", " 'Krippendorff': 0.3016172468890952,\n", " 'Invalid': 1,\n", @@ -9576,7 +9590,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.1892591733335329,\n", " 'Cohen': 0.21692239484945441,\n", - " 'Spearman': 0.6640486349038174,\n", + " 'Spearman': 0.6650968172974302,\n", " 'Kendall': 0.5686423845614813,\n", " 'Krippendorff': 0.5881035570625532,\n", " 'Invalid': 0,\n", @@ -9623,7 +9637,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.052830640972712374,\n", " 'Cohen': 0.011256190904997854,\n", - " 'Spearman': 0.4449622587491797,\n", + " 'Spearman': 0.4473328475253046,\n", " 'Kendall': 0.3534680868001957,\n", " 'Krippendorff': 0.0882604518536968,\n", " 'Invalid': 295,\n", @@ -9670,7 +9684,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.15530440935918408,\n", " 'Cohen': 0.19071083621142826,\n", - " 'Spearman': 0.6930929484312037,\n", + " 'Spearman': 0.6982136541973727,\n", " 'Kendall': 0.5966648842718432,\n", " 'Krippendorff': 0.6119524971832113,\n", " 'Invalid': 1,\n", @@ -9717,7 +9731,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.13846374079950372,\n", " 'Cohen': 0.15877018771003082,\n", - " 'Spearman': 0.6524395016623825,\n", + " 'Spearman': 0.6542129292940191,\n", " 'Kendall': 0.5335019194551602,\n", " 'Krippendorff': 0.5619589856418514,\n", " 'Invalid': 51,\n", @@ -9764,7 +9778,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07140016821587544,\n", " 'Cohen': -0.01146219160379669,\n", - " 'Spearman': 0.6206015906540859,\n", + " 'Spearman': 0.6266969844686984,\n", " 'Kendall': 0.5237616398748435,\n", " 'Krippendorff': 0.27793600237429794,\n", " 'Invalid': 0,\n", @@ -9811,7 +9825,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'cs': {'phi-4': {'metrics': {'Fleiss': 0.22243601700322982,\n", " 'Cohen': 0.23355686513581264,\n", - " 'Spearman': 0.6363744178790373,\n", + " 'Spearman': 0.6425275924136147,\n", " 'Kendall': 0.5280921365915271,\n", " 'Krippendorff': 0.5496139767674719,\n", " 'Invalid': 0,\n", @@ -9858,7 +9872,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10366826955604394,\n", " 'Cohen': 0.13900175232520073,\n", - " 'Spearman': 0.593417788553288,\n", + " 'Spearman': 0.5995512861609984,\n", " 'Kendall': 0.5012203022231464,\n", " 'Krippendorff': 0.514418110672844,\n", " 'Invalid': 0,\n", @@ -9905,7 +9919,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.22541932275964946,\n", " 'Cohen': 0.24095388123317685,\n", - " 'Spearman': 0.6835036977740511,\n", + " 'Spearman': 0.6904211403747502,\n", " 'Kendall': 0.5756882552156459,\n", " 'Krippendorff': 0.615847426198448,\n", " 'Invalid': 0,\n", @@ -9952,7 +9966,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.0574702742145121,\n", " 'Cohen': 0.11502521648111153,\n", - " 'Spearman': 0.6703854778865829,\n", + " 'Spearman': 0.6742456665520513,\n", " 'Kendall': 0.5754789822583627,\n", " 'Krippendorff': 0.5592635711762943,\n", " 'Invalid': 0,\n", @@ -9999,7 +10013,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.18393928516486335,\n", " 'Cohen': 0.20335160905840288,\n", - " 'Spearman': 0.6490607345376566,\n", + " 'Spearman': 0.656749799677534,\n", " 'Kendall': 0.5460937312955724,\n", " 'Krippendorff': 0.5681774149274572,\n", " 'Invalid': 0,\n", @@ -10046,7 +10060,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11785415963600934,\n", " 'Cohen': -0.028264085809394768,\n", - " 'Spearman': 0.6437547278120541,\n", + " 'Spearman': 0.6499739397071886,\n", " 'Kendall': 0.5460388026814268,\n", " 'Krippendorff': 0.19765402151083344,\n", " 'Invalid': 0,\n", @@ -10093,7 +10107,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10159781920895798,\n", " 'Cohen': -0.035161336998986936,\n", - " 'Spearman': 0.7285878502261494,\n", + " 'Spearman': 0.729521530573961,\n", " 'Kendall': 0.6278076672371097,\n", " 'Krippendorff': 0.3029223713882663,\n", " 'Invalid': 0,\n", @@ -10140,7 +10154,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.22235460197635187,\n", " 'Cohen': 0.24895812181514032,\n", - " 'Spearman': 0.696527064526805,\n", + " 'Spearman': 0.6996206086490144,\n", " 'Kendall': 0.6019784562453934,\n", " 'Krippendorff': 0.6132520741867014,\n", " 'Invalid': 0,\n", @@ -10187,7 +10201,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07696317601708366,\n", " 'Cohen': 0.0041353415250869885,\n", - " 'Spearman': 0.45522819892888655,\n", + " 'Spearman': 0.4777873799906214,\n", " 'Kendall': 0.36404724982365133,\n", " 'Krippendorff': 0.004499223431700283,\n", " 'Invalid': 143,\n", @@ -10234,7 +10248,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10993622236195418,\n", " 'Cohen': 0.14939123097903406,\n", - " 'Spearman': 0.6876006389085294,\n", + " 'Spearman': 0.6891610068094658,\n", " 'Kendall': 0.5914530906678815,\n", " 'Krippendorff': 0.5969666383991323,\n", " 'Invalid': 1,\n", @@ -10281,7 +10295,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.14277890619122852,\n", " 'Cohen': 0.16148819685641957,\n", - " 'Spearman': 0.663418006202801,\n", + " 'Spearman': 0.6647051078956249,\n", " 'Kendall': 0.547738124428748,\n", " 'Krippendorff': 0.5744925583388755,\n", " 'Invalid': 53,\n", @@ -10328,7 +10342,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04654442877291962,\n", " 'Cohen': 0.011528758023824026,\n", - " 'Spearman': 0.636327662568522,\n", + " 'Spearman': 0.6425889899511723,\n", " 'Kendall': 0.5393440074530751,\n", " 'Krippendorff': 0.2771986832345311,\n", " 'Invalid': 0,\n", @@ -10375,7 +10389,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'es': {'phi-4': {'metrics': {'Fleiss': 0.22566967921538816,\n", " 'Cohen': 0.2365711226823689,\n", - " 'Spearman': 0.6368830818583854,\n", + " 'Spearman': 0.6424367358777032,\n", " 'Kendall': 0.5339696804020988,\n", " 'Krippendorff': 0.547890180694453,\n", " 'Invalid': 0,\n", @@ -10422,7 +10436,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06451348837209307,\n", " 'Cohen': 0.10390924989544925,\n", - " 'Spearman': 0.6051553774551707,\n", + " 'Spearman': 0.6099698453842608,\n", " 'Kendall': 0.5135226552908125,\n", " 'Krippendorff': 0.4818875652503647,\n", " 'Invalid': 0,\n", @@ -10469,7 +10483,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.187808069530978,\n", " 'Cohen': 0.2075626393808211,\n", - " 'Spearman': 0.6963590562387573,\n", + " 'Spearman': 0.7044638593677771,\n", " 'Kendall': 0.5869134421684615,\n", " 'Krippendorff': 0.6037083039264448,\n", " 'Invalid': 0,\n", @@ -10516,7 +10530,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.0781852132427646,\n", " 'Cohen': 0.1343969623288812,\n", - " 'Spearman': 0.6529045899173779,\n", + " 'Spearman': 0.6597547052001983,\n", " 'Kendall': 0.5656710961489775,\n", " 'Krippendorff': 0.5407366682824177,\n", " 'Invalid': 0,\n", @@ -10563,7 +10577,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.14250485181888484,\n", " 'Cohen': 0.16458953314252134,\n", - " 'Spearman': 0.6585874790491857,\n", + " 'Spearman': 0.6631586054654145,\n", " 'Kendall': 0.5516214349525573,\n", " 'Krippendorff': 0.5760881746536972,\n", " 'Invalid': 0,\n", @@ -10610,7 +10624,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10722170041341669,\n", " 'Cohen': -0.02778384790684596,\n", - " 'Spearman': 0.6179901676064945,\n", + " 'Spearman': 0.6205995096384024,\n", " 'Kendall': 0.5230637106476714,\n", " 'Krippendorff': 0.21910625992730148,\n", " 'Invalid': 0,\n", @@ -10657,7 +10671,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.11458180019543734,\n", " 'Cohen': -0.048162316946437356,\n", - " 'Spearman': 0.6979780148181274,\n", + " 'Spearman': 0.7038622450040771,\n", " 'Kendall': 0.5974227838006986,\n", " 'Krippendorff': 0.29086138491542557,\n", " 'Invalid': 0,\n", @@ -10704,7 +10718,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.20608908043830618,\n", " 'Cohen': 0.2335810635413561,\n", - " 'Spearman': 0.6793744340358849,\n", + " 'Spearman': 0.6837274044778654,\n", " 'Kendall': 0.5839060022582565,\n", " 'Krippendorff': 0.5896384370474785,\n", " 'Invalid': 0,\n", @@ -10751,7 +10765,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07696205830612526,\n", " 'Cohen': -0.0006053513055408466,\n", - " 'Spearman': 0.5526230559035593,\n", + " 'Spearman': 0.5635429636532285,\n", " 'Kendall': 0.4478170865238588,\n", " 'Krippendorff': 0.14479351121104556,\n", " 'Invalid': 217,\n", @@ -10798,7 +10812,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.14288647938229013,\n", " 'Cohen': 0.17726428251110027,\n", - " 'Spearman': 0.659290830507018,\n", + " 'Spearman': 0.6639432528754559,\n", " 'Kendall': 0.5643714819828817,\n", " 'Krippendorff': 0.5751105381373665,\n", " 'Invalid': 2,\n", @@ -10845,7 +10859,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.18629669426711326,\n", " 'Cohen': 0.20134498824376057,\n", - " 'Spearman': 0.6427462053819742,\n", + " 'Spearman': 0.6513410297019224,\n", " 'Kendall': 0.5237410218540497,\n", " 'Krippendorff': 0.5792479569147012,\n", " 'Invalid': 64,\n", @@ -10892,7 +10906,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.08322433159653218,\n", " 'Cohen': -0.021401087544121733,\n", - " 'Spearman': 0.6405085672570966,\n", + " 'Spearman': 0.6472580554659703,\n", " 'Kendall': 0.5430148406502159,\n", " 'Krippendorff': 0.2562472226004705,\n", " 'Invalid': 0,\n", @@ -10939,7 +10953,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'tr': {'phi-4': {'metrics': {'Fleiss': 0.24017114637544867,\n", " 'Cohen': 0.25351301933430404,\n", - " 'Spearman': 0.6506139785053923,\n", + " 'Spearman': 0.6583440225936218,\n", " 'Kendall': 0.5419714998542989,\n", " 'Krippendorff': 0.5565940981983335,\n", " 'Invalid': 0,\n", @@ -10986,7 +11000,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.14126882113018063,\n", " 'Cohen': 0.1782717940127786,\n", - " 'Spearman': 0.6133730350071849,\n", + " 'Spearman': 0.6167791376721194,\n", " 'Kendall': 0.5214167879150541,\n", " 'Krippendorff': 0.515356848243858,\n", " 'Invalid': 0,\n", @@ -11033,7 +11047,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2684021761813938,\n", " 'Cohen': 0.28200597276533323,\n", - " 'Spearman': 0.6885610187424852,\n", + " 'Spearman': 0.6971656587338136,\n", " 'Kendall': 0.5802353508090317,\n", " 'Krippendorff': 0.6437666346895605,\n", " 'Invalid': 0,\n", @@ -11080,7 +11094,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.08446466274313806,\n", " 'Cohen': 0.14048922020654697,\n", - " 'Spearman': 0.6575183053605921,\n", + " 'Spearman': 0.6624890748701617,\n", " 'Kendall': 0.5675661896062716,\n", " 'Krippendorff': 0.5532264001630438,\n", " 'Invalid': 1,\n", @@ -11127,7 +11141,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1428398284768228,\n", " 'Cohen': 0.1656946017365044,\n", - " 'Spearman': 0.646583259229483,\n", + " 'Spearman': 0.6486405721607714,\n", " 'Kendall': 0.5417701810653808,\n", " 'Krippendorff': 0.5454856038913323,\n", " 'Invalid': 0,\n", @@ -11174,7 +11188,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.1399902128231207,\n", " 'Cohen': -0.04731114549036719,\n", - " 'Spearman': 0.6429015691440293,\n", + " 'Spearman': 0.6492371073148979,\n", " 'Kendall': 0.5469981975548602,\n", " 'Krippendorff': 0.1899475785548791,\n", " 'Invalid': 0,\n", @@ -11221,7 +11235,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.0881522367761965,\n", " 'Cohen': -0.023241843510077853,\n", - " 'Spearman': 0.6856674083054953,\n", + " 'Spearman': 0.6872040626458895,\n", " 'Kendall': 0.5844473559148776,\n", " 'Krippendorff': 0.2675229574068234,\n", " 'Invalid': 0,\n", @@ -11268,7 +11282,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.22114593987525824,\n", " 'Cohen': 0.24831123584631765,\n", - " 'Spearman': 0.7153431939751708,\n", + " 'Spearman': 0.7195268341555376,\n", " 'Kendall': 0.6210157883965518,\n", " 'Krippendorff': 0.6333109033677062,\n", " 'Invalid': 0,\n", @@ -11315,7 +11329,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.1608706776091791,\n", " 'Cohen': -0.05899567317187038,\n", - " 'Spearman': 0.48352508438693453,\n", + " 'Spearman': 0.4843881921578221,\n", " 'Kendall': 0.39861884617766263,\n", " 'Krippendorff': -0.042240873578598404,\n", " 'Invalid': 260,\n", @@ -11362,7 +11376,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10878683601647034,\n", " 'Cohen': 0.152539069162285,\n", - " 'Spearman': 0.6938344515526925,\n", + " 'Spearman': 0.6981729360300727,\n", " 'Kendall': 0.5980867072597336,\n", " 'Krippendorff': 0.5864204698396918,\n", " 'Invalid': 1,\n", @@ -11409,7 +11423,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.16597729293282615,\n", " 'Cohen': 0.1854538415113246,\n", - " 'Spearman': 0.6436484930824882,\n", + " 'Spearman': 0.64268970405614,\n", " 'Kendall': 0.5225949744551703,\n", " 'Krippendorff': 0.5484219833499763,\n", " 'Invalid': 45,\n", @@ -11456,7 +11470,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07198498809151489,\n", " 'Cohen': -0.012741314496370393,\n", - " 'Spearman': 0.6311755769638117,\n", + " 'Spearman': 0.6380158291371096,\n", " 'Kendall': 0.5317207376017842,\n", " 'Krippendorff': 0.28144677392374096,\n", " 'Invalid': 0,\n", @@ -11503,7 +11517,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'fr': {'phi-4': {'metrics': {'Fleiss': 0.18072474074377248,\n", " 'Cohen': 0.19381585505218069,\n", - " 'Spearman': 0.6118911419547828,\n", + " 'Spearman': 0.6224269044724228,\n", " 'Kendall': 0.507501915945731,\n", " 'Krippendorff': 0.524659445400935,\n", " 'Invalid': 9,\n", @@ -11550,7 +11564,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06362515290936376,\n", " 'Cohen': 0.10511269512206667,\n", - " 'Spearman': 0.6169962220796649,\n", + " 'Spearman': 0.6228714762402974,\n", " 'Kendall': 0.5219195837240582,\n", " 'Krippendorff': 0.49755490198120467,\n", " 'Invalid': 0,\n", @@ -11597,7 +11611,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.19281441150769643,\n", " 'Cohen': 0.2117783851956736,\n", - " 'Spearman': 0.6932090554744796,\n", + " 'Spearman': 0.7009376881007874,\n", " 'Kendall': 0.5824461754244241,\n", " 'Krippendorff': 0.6068109901170714,\n", " 'Invalid': 0,\n", @@ -11644,7 +11658,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.06027895509006439,\n", " 'Cohen': 0.1213197993722046,\n", - " 'Spearman': 0.6396739890934453,\n", + " 'Spearman': 0.6420812835845574,\n", " 'Kendall': 0.5513282078017098,\n", " 'Krippendorff': 0.5369362606683725,\n", " 'Invalid': 0,\n", @@ -11691,7 +11705,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.13211119005674354,\n", " 'Cohen': 0.15562783782888034,\n", - " 'Spearman': 0.6251980756429071,\n", + " 'Spearman': 0.6289326720306853,\n", " 'Kendall': 0.5251311846484898,\n", " 'Krippendorff': 0.5420936139424033,\n", " 'Invalid': 0,\n", @@ -11738,7 +11752,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.05833874683280317,\n", " 'Cohen': 0.012454369765943829,\n", - " 'Spearman': 0.5824506242158284,\n", + " 'Spearman': 0.5871886761222456,\n", " 'Kendall': 0.4874177099677098,\n", " 'Krippendorff': 0.23726395450409432,\n", " 'Invalid': 0,\n", @@ -11785,7 +11799,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.1093414282227094,\n", " 'Cohen': -0.042163340371909275,\n", - " 'Spearman': 0.6963999254135463,\n", + " 'Spearman': 0.699135214557241,\n", " 'Kendall': 0.5992019511039763,\n", " 'Krippendorff': 0.2711953157699525,\n", " 'Invalid': 1,\n", @@ -11832,7 +11846,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.1740089475110849,\n", " 'Cohen': 0.20242143076686647,\n", - " 'Spearman': 0.6763119361327616,\n", + " 'Spearman': 0.683769586871251,\n", " 'Kendall': 0.5782595077827976,\n", " 'Krippendorff': 0.5754380464823079,\n", " 'Invalid': 0,\n", @@ -11879,7 +11893,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.05517750266458965,\n", " 'Cohen': 0.012945976623615518,\n", - " 'Spearman': 0.4981869290503239,\n", + " 'Spearman': 0.48386426008364597,\n", " 'Kendall': 0.40101729167080563,\n", " 'Krippendorff': 0.05818209193602042,\n", " 'Invalid': 316,\n", @@ -11926,7 +11940,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.180527320889546,\n", " 'Cohen': 0.21268735851010834,\n", - " 'Spearman': 0.684715626756924,\n", + " 'Spearman': 0.6877443984173865,\n", " 'Kendall': 0.5904873212279812,\n", " 'Krippendorff': 0.6181251861397463,\n", " 'Invalid': 1,\n", @@ -11973,7 +11987,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1354924433004306,\n", " 'Cohen': 0.1587893213599848,\n", - " 'Spearman': 0.6674861259461091,\n", + " 'Spearman': 0.6671851880365198,\n", " 'Kendall': 0.5473391819414487,\n", " 'Krippendorff': 0.5865592281673595,\n", " 'Invalid': 34,\n", @@ -12020,7 +12034,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06482211722825577,\n", " 'Cohen': -0.004605442796031589,\n", - " 'Spearman': 0.6309003287737424,\n", + " 'Spearman': 0.6362640861493704,\n", " 'Kendall': 0.5364486726733165,\n", " 'Krippendorff': 0.2838059019995858,\n", " 'Invalid': 0,\n", @@ -12067,7 +12081,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'nl': {'phi-4': {'metrics': {'Fleiss': 0.19749905527500086,\n", " 'Cohen': 0.21062413408576375,\n", - " 'Spearman': 0.5962768953243347,\n", + " 'Spearman': 0.6017338518953714,\n", " 'Kendall': 0.49417415317567037,\n", " 'Krippendorff': 0.4962034728408595,\n", " 'Invalid': 0,\n", @@ -12114,7 +12128,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.10490512706951376,\n", " 'Cohen': 0.14144702299695477,\n", - " 'Spearman': 0.6143398745511875,\n", + " 'Spearman': 0.6150116797901293,\n", " 'Kendall': 0.5252208293659809,\n", " 'Krippendorff': 0.492011111270901,\n", " 'Invalid': 0,\n", @@ -12161,7 +12175,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.23860614374956293,\n", " 'Cohen': 0.2558182280915081,\n", - " 'Spearman': 0.6715978742656323,\n", + " 'Spearman': 0.6786086903747087,\n", " 'Kendall': 0.5645675752491084,\n", " 'Krippendorff': 0.6004384519045698,\n", " 'Invalid': 0,\n", @@ -12208,7 +12222,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.049411305602481075,\n", " 'Cohen': 0.114040964777948,\n", - " 'Spearman': 0.629445516554736,\n", + " 'Spearman': 0.6394215435120016,\n", " 'Kendall': 0.541622482834839,\n", " 'Krippendorff': 0.5318916101283754,\n", " 'Invalid': 1,\n", @@ -12255,7 +12269,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.104611852531386,\n", " 'Cohen': 0.13197061882108263,\n", - " 'Spearman': 0.6450567275003815,\n", + " 'Spearman': 0.6513746043526876,\n", " 'Kendall': 0.5455268225993654,\n", " 'Krippendorff': 0.538379425961808,\n", " 'Invalid': 0,\n", @@ -12302,7 +12316,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11831453329534218,\n", " 'Cohen': -0.02950615868873263,\n", - " 'Spearman': 0.6419445690583515,\n", + " 'Spearman': 0.6445973541437551,\n", " 'Kendall': 0.5418044075860917,\n", " 'Krippendorff': 0.18402637778278186,\n", " 'Invalid': 0,\n", @@ -12349,7 +12363,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.08976211231251495,\n", " 'Cohen': -0.0273455204713704,\n", - " 'Spearman': 0.697361838555444,\n", + " 'Spearman': 0.6989913208087782,\n", " 'Kendall': 0.598806433786417,\n", " 'Krippendorff': 0.3058174880930301,\n", " 'Invalid': 1,\n", @@ -12396,7 +12410,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.19030103740056278,\n", " 'Cohen': 0.21752925702984738,\n", - " 'Spearman': 0.6894359179540224,\n", + " 'Spearman': 0.6942254307446798,\n", " 'Kendall': 0.5919004863222185,\n", " 'Krippendorff': 0.5860852208038714,\n", " 'Invalid': 0,\n", @@ -12443,7 +12457,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.028838674179900214,\n", " 'Cohen': 0.028781745889601362,\n", - " 'Spearman': 0.552079255490546,\n", + " 'Spearman': 0.5649511005348035,\n", " 'Kendall': 0.4503619457817632,\n", " 'Krippendorff': 0.19131781360379319,\n", " 'Invalid': 254,\n", @@ -12490,7 +12504,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.15799694327070032,\n", " 'Cohen': 0.19207544007532185,\n", - " 'Spearman': 0.6768434765887341,\n", + " 'Spearman': 0.6804738889270094,\n", " 'Kendall': 0.5805122775735712,\n", " 'Krippendorff': 0.6020436066257648,\n", " 'Invalid': 2,\n", @@ -12537,7 +12551,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.11857815860347998,\n", " 'Cohen': 0.13881004185948898,\n", - " 'Spearman': 0.6261108170842574,\n", + " 'Spearman': 0.6282193233965776,\n", " 'Kendall': 0.5087307149759583,\n", " 'Krippendorff': 0.5495888849160869,\n", " 'Invalid': 37,\n", @@ -12584,7 +12598,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04430980715377089,\n", " 'Cohen': 0.012983226582359286,\n", - " 'Spearman': 0.6355964660471657,\n", + " 'Spearman': 0.6409816882191227,\n", " 'Kendall': 0.537345844983624,\n", " 'Krippendorff': 0.2995519014865615,\n", " 'Invalid': 0,\n", @@ -12631,7 +12645,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'de': {'phi-4': {'metrics': {'Fleiss': 0.21790219457404525,\n", " 'Cohen': 0.230746818047172,\n", - " 'Spearman': 0.6225697181989267,\n", + " 'Spearman': 0.6276948531045122,\n", " 'Kendall': 0.5152196309359278,\n", " 'Krippendorff': 0.5229276850254223,\n", " 'Invalid': 0,\n", @@ -12678,7 +12692,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06454252633411683,\n", " 'Cohen': 0.10418780577270281,\n", - " 'Spearman': 0.5817115492713107,\n", + " 'Spearman': 0.5871325263469134,\n", " 'Kendall': 0.4914502119354108,\n", " 'Krippendorff': 0.46933790759333727,\n", " 'Invalid': 0,\n", @@ -12725,7 +12739,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.22149663602812664,\n", " 'Cohen': 0.23818779692682213,\n", - " 'Spearman': 0.6894881472476444,\n", + " 'Spearman': 0.697175369075446,\n", " 'Kendall': 0.581053541110699,\n", " 'Krippendorff': 0.6140631708274648,\n", " 'Invalid': 0,\n", @@ -12772,7 +12786,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.03227354284124583,\n", " 'Cohen': 0.09887681038867213,\n", - " 'Spearman': 0.6197557583464899,\n", + " 'Spearman': 0.6218870534802078,\n", " 'Kendall': 0.5339781090424877,\n", " 'Krippendorff': 0.5193614671572371,\n", " 'Invalid': 0,\n", @@ -12819,7 +12833,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.16176955204643811,\n", " 'Cohen': 0.18093738819320215,\n", - " 'Spearman': 0.6337546092713023,\n", + " 'Spearman': 0.638094327670404,\n", " 'Kendall': 0.5350459984364871,\n", " 'Krippendorff': 0.5684031200578643,\n", " 'Invalid': 0,\n", @@ -12866,7 +12880,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10518735435836338,\n", " 'Cohen': -0.026045160344544183,\n", - " 'Spearman': 0.61692452206064,\n", + " 'Spearman': 0.6222004781558779,\n", " 'Kendall': 0.5190059489219454,\n", " 'Krippendorff': 0.22762330379594742,\n", " 'Invalid': 0,\n", @@ -12913,7 +12927,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.0861972323124968,\n", " 'Cohen': -0.02373895383939817,\n", - " 'Spearman': 0.6781976546525984,\n", + " 'Spearman': 0.68367956094756,\n", " 'Kendall': 0.5800068638059478,\n", " 'Krippendorff': 0.2960127214120797,\n", " 'Invalid': 0,\n", @@ -12960,7 +12974,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.20750818581359107,\n", " 'Cohen': 0.23537702607470057,\n", - " 'Spearman': 0.7029774925190886,\n", + " 'Spearman': 0.7048528909290414,\n", " 'Kendall': 0.6076767913633502,\n", " 'Krippendorff': 0.607827764754351,\n", " 'Invalid': 0,\n", @@ -13007,7 +13021,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.022933167676140228,\n", " 'Cohen': 0.037843522972946575,\n", - " 'Spearman': 0.5973261273147846,\n", + " 'Spearman': 0.6014058610578566,\n", " 'Kendall': 0.4994593093193661,\n", " 'Krippendorff': 0.2520696085494646,\n", " 'Invalid': 264,\n", @@ -13054,7 +13068,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1632721595730228,\n", " 'Cohen': 0.1972651926907848,\n", - " 'Spearman': 0.6880854445039468,\n", + " 'Spearman': 0.6915812578630529,\n", " 'Kendall': 0.5926759477956665,\n", " 'Krippendorff': 0.6120759836155344,\n", " 'Invalid': 1,\n", @@ -13101,7 +13115,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1843475459257938,\n", " 'Cohen': 0.200375640873788,\n", - " 'Spearman': 0.6188050023143503,\n", + " 'Spearman': 0.6154631597016689,\n", " 'Kendall': 0.5075398877011381,\n", " 'Krippendorff': 0.5713376526505718,\n", " 'Invalid': 40,\n", @@ -13148,7 +13162,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04715633312969314,\n", " 'Cohen': 0.009793530720208943,\n", - " 'Spearman': 0.6443943395247512,\n", + " 'Spearman': 0.6500245441904008,\n", " 'Kendall': 0.547525489583711,\n", " 'Krippendorff': 0.3097379227640713,\n", " 'Invalid': 0,\n", @@ -13195,7 +13209,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'it': {'phi-4': {'metrics': {'Fleiss': 0.24044996078800035,\n", " 'Cohen': 0.2530726637537587,\n", - " 'Spearman': 0.6174805183356731,\n", + " 'Spearman': 0.6276525154745057,\n", " 'Kendall': 0.5142921540855047,\n", " 'Krippendorff': 0.526819018233728,\n", " 'Invalid': 1,\n", @@ -13242,7 +13256,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06173214241285798,\n", " 'Cohen': 0.10228381807534659,\n", - " 'Spearman': 0.5772739847353938,\n", + " 'Spearman': 0.58492992934578,\n", " 'Kendall': 0.4877496825068927,\n", " 'Krippendorff': 0.46341190055078196,\n", " 'Invalid': 0,\n", @@ -13289,7 +13303,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.20982046081883746,\n", " 'Cohen': 0.22676855051216904,\n", - " 'Spearman': 0.6782415529596452,\n", + " 'Spearman': 0.6850493006295878,\n", " 'Kendall': 0.567597764411304,\n", " 'Krippendorff': 0.601616514546842,\n", " 'Invalid': 0,\n", @@ -13336,7 +13350,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.037656903765690405,\n", " 'Cohen': 0.10225870332634956,\n", - " 'Spearman': 0.6320358558594364,\n", + " 'Spearman': 0.6318601928415856,\n", " 'Kendall': 0.5443424011315313,\n", " 'Krippendorff': 0.5242934652141771,\n", " 'Invalid': 1,\n", @@ -13383,7 +13397,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.12997793933438567,\n", " 'Cohen': 0.15188330748912882,\n", - " 'Spearman': 0.6608363433337863,\n", + " 'Spearman': 0.6670290182364002,\n", " 'Kendall': 0.5595646970064342,\n", " 'Krippendorff': 0.5700553571149084,\n", " 'Invalid': 0,\n", @@ -13430,7 +13444,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.08765361374308182,\n", " 'Cohen': -0.013875296609601406,\n", - " 'Spearman': 0.6111773900291828,\n", + " 'Spearman': 0.6090754952932688,\n", " 'Kendall': 0.5138170014192945,\n", " 'Krippendorff': 0.23873667692162093,\n", " 'Invalid': 0,\n", @@ -13477,7 +13491,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10877788519724868,\n", " 'Cohen': -0.04219543147208116,\n", - " 'Spearman': 0.7019093426525898,\n", + " 'Spearman': 0.7055295165209193,\n", " 'Kendall': 0.6028509154160367,\n", " 'Krippendorff': 0.29286334206533327,\n", " 'Invalid': 0,\n", @@ -13524,7 +13538,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.1828535162984544,\n", " 'Cohen': 0.21217581506945005,\n", - " 'Spearman': 0.6647691860296875,\n", + " 'Spearman': 0.6686477475607646,\n", " 'Kendall': 0.569705781113034,\n", " 'Krippendorff': 0.5783262428695751,\n", " 'Invalid': 0,\n", @@ -13571,7 +13585,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 1, '4': 0, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.037598367822792245,\n", " 'Cohen': 0.023441396508728007,\n", - " 'Spearman': 0.47231710932797266,\n", + " 'Spearman': 0.4790301254803887,\n", " 'Kendall': 0.38370219508418346,\n", " 'Krippendorff': 0.11078890463249214,\n", " 'Invalid': 244,\n", @@ -13618,7 +13632,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.16688217084830123,\n", " 'Cohen': 0.20078403631326092,\n", - " 'Spearman': 0.6721136282022295,\n", + " 'Spearman': 0.6761206514872166,\n", " 'Kendall': 0.5768533675004286,\n", " 'Krippendorff': 0.6016761061967593,\n", " 'Invalid': 1,\n", @@ -13665,7 +13679,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1392825964538014,\n", " 'Cohen': 0.15901508579280466,\n", - " 'Spearman': 0.6687193415411001,\n", + " 'Spearman': 0.6715447771041636,\n", " 'Kendall': 0.5475795397306189,\n", " 'Krippendorff': 0.5945581260733762,\n", " 'Invalid': 51,\n", @@ -13712,7 +13726,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06424716343940354,\n", " 'Cohen': -0.0037603728543822434,\n", - " 'Spearman': 0.6248734362056104,\n", + " 'Spearman': 0.6298714793309707,\n", " 'Kendall': 0.530703695814679,\n", " 'Krippendorff': 0.2719466720917523,\n", " 'Invalid': 0,\n", @@ -13759,7 +13773,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'ro': {'phi-4': {'metrics': {'Fleiss': 0.17982575986962762,\n", " 'Cohen': 0.19075655561708782,\n", - " 'Spearman': 0.6406325280640629,\n", + " 'Spearman': 0.6473128154430938,\n", " 'Kendall': 0.530183011869488,\n", " 'Krippendorff': 0.5514652151776293,\n", " 'Invalid': 0,\n", @@ -13806,7 +13820,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08649983396625897,\n", " 'Cohen': 0.12671672641694087,\n", - " 'Spearman': 0.5916588804446729,\n", + " 'Spearman': 0.5951731806789663,\n", " 'Kendall': 0.5006393262937947,\n", " 'Krippendorff': 0.4941370166641462,\n", " 'Invalid': 0,\n", @@ -13853,7 +13867,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.21792718968296618,\n", " 'Cohen': 0.2369349885780624,\n", - " 'Spearman': 0.6919261188614564,\n", + " 'Spearman': 0.6955869318500117,\n", " 'Kendall': 0.5829388638937573,\n", " 'Krippendorff': 0.6007810987073277,\n", " 'Invalid': 0,\n", @@ -13900,7 +13914,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.06622685764802673,\n", " 'Cohen': 0.1209150169581219,\n", - " 'Spearman': 0.6463575490305947,\n", + " 'Spearman': 0.6493877405360879,\n", " 'Kendall': 0.5561427601313816,\n", " 'Krippendorff': 0.5430803920448131,\n", " 'Invalid': 2,\n", @@ -13947,7 +13961,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1282618310482087,\n", " 'Cohen': 0.1503787179013486,\n", - " 'Spearman': 0.6517565042273524,\n", + " 'Spearman': 0.6562437998651242,\n", " 'Kendall': 0.5467187138302878,\n", " 'Krippendorff': 0.5560466776663234,\n", " 'Invalid': 0,\n", @@ -13994,7 +14008,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11391113336223843,\n", " 'Cohen': -0.028182654378858363,\n", - " 'Spearman': 0.6260205846730272,\n", + " 'Spearman': 0.630305505223741,\n", " 'Kendall': 0.5327592835080491,\n", " 'Krippendorff': 0.2129023984824392,\n", " 'Invalid': 0,\n", @@ -14041,7 +14055,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.11699014922461715,\n", " 'Cohen': -0.049152845148612734,\n", - " 'Spearman': 0.7098239977829804,\n", + " 'Spearman': 0.7178107376949358,\n", " 'Kendall': 0.611073548390273,\n", " 'Krippendorff': 0.2792245981260555,\n", " 'Invalid': 2,\n", @@ -14088,7 +14102,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.20703841288928693,\n", " 'Cohen': 0.23319549724729915,\n", - " 'Spearman': 0.6765738966575623,\n", + " 'Spearman': 0.6838791945060071,\n", " 'Kendall': 0.5797879076631515,\n", " 'Krippendorff': 0.5835725373755555,\n", " 'Invalid': 0,\n", @@ -14135,7 +14149,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.04792413218952474,\n", " 'Cohen': 0.01485325393449588,\n", - " 'Spearman': 0.5299239801261604,\n", + " 'Spearman': 0.538972633923543,\n", " 'Kendall': 0.43118402934284417,\n", " 'Krippendorff': 0.20295819179067154,\n", " 'Invalid': 249,\n", @@ -14182,7 +14196,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.11104528207598441,\n", " 'Cohen': 0.15127860821319483,\n", - " 'Spearman': 0.6726194436499735,\n", + " 'Spearman': 0.6772796626780714,\n", " 'Kendall': 0.5748306464919687,\n", " 'Krippendorff': 0.5818652066897299,\n", " 'Invalid': 2,\n", @@ -14229,7 +14243,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.12969699074275035,\n", " 'Cohen': 0.15062612615156956,\n", - " 'Spearman': 0.6856549344122829,\n", + " 'Spearman': 0.6862066027045421,\n", " 'Kendall': 0.5628058781006902,\n", " 'Krippendorff': 0.5774094561697447,\n", " 'Invalid': 44,\n", @@ -14276,7 +14290,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04720688574390627,\n", " 'Cohen': 0.009088959560517806,\n", - " 'Spearman': 0.6248526702931424,\n", + " 'Spearman': 0.6307093215547209,\n", " 'Kendall': 0.52826495780647,\n", " 'Krippendorff': 0.2900721605938025,\n", " 'Invalid': 0,\n", @@ -14323,7 +14337,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'lt': {'phi-4': {'metrics': {'Fleiss': 0.20412219178755234,\n", " 'Cohen': 0.21567706542843446,\n", - " 'Spearman': 0.6338286183564478,\n", + " 'Spearman': 0.6380591962126064,\n", " 'Kendall': 0.529572911832488,\n", " 'Krippendorff': 0.5546154024926158,\n", " 'Invalid': 0,\n", @@ -14370,7 +14384,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.09995821835040046,\n", " 'Cohen': 0.1342193042833696,\n", - " 'Spearman': 0.5811897205351297,\n", + " 'Spearman': 0.5894550466137274,\n", " 'Kendall': 0.4911509980019675,\n", " 'Krippendorff': 0.4970252115011522,\n", " 'Invalid': 0,\n", @@ -14417,7 +14431,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2237198591167705,\n", " 'Cohen': 0.23968782725304105,\n", - " 'Spearman': 0.6895467404519742,\n", + " 'Spearman': 0.6970744759953631,\n", " 'Kendall': 0.5787064794075746,\n", " 'Krippendorff': 0.6316224208646526,\n", " 'Invalid': 0,\n", @@ -14464,7 +14478,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.048797094870631025,\n", " 'Cohen': 0.10929281122150791,\n", - " 'Spearman': 0.6556936413877108,\n", + " 'Spearman': 0.6598908712189564,\n", " 'Kendall': 0.5665103751552063,\n", " 'Krippendorff': 0.5402385173124379,\n", " 'Invalid': 3,\n", @@ -14511,7 +14525,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.15469590411388787,\n", " 'Cohen': 0.17590027700831024,\n", - " 'Spearman': 0.6359202577508084,\n", + " 'Spearman': 0.6421188811925679,\n", " 'Kendall': 0.5354484304528153,\n", " 'Krippendorff': 0.5276977471026458,\n", " 'Invalid': 0,\n", @@ -14558,7 +14572,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.13797562318909984,\n", " 'Cohen': -0.04744041295464463,\n", - " 'Spearman': 0.6319767780034784,\n", + " 'Spearman': 0.6317197197764564,\n", " 'Kendall': 0.5360337139258441,\n", " 'Krippendorff': 0.19061813447405906,\n", " 'Invalid': 0,\n", @@ -14605,7 +14619,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.1248539906024137,\n", " 'Cohen': -0.05432652803236193,\n", - " 'Spearman': 0.7043224380653752,\n", + " 'Spearman': 0.7074118502355783,\n", " 'Kendall': 0.6060338679877387,\n", " 'Krippendorff': 0.25458416137486195,\n", " 'Invalid': 0,\n", @@ -14652,7 +14666,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.19216963457127348,\n", " 'Cohen': 0.2214759923437779,\n", - " 'Spearman': 0.6851882987903684,\n", + " 'Spearman': 0.6908544200618558,\n", " 'Kendall': 0.5902132682913738,\n", " 'Krippendorff': 0.5951868926012376,\n", " 'Invalid': 0,\n", @@ -14699,7 +14713,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.04814299119169417,\n", " 'Cohen': 0.011306694076834156,\n", - " 'Spearman': 0.4739778092940784,\n", + " 'Spearman': 0.48669414166879044,\n", " 'Kendall': 0.3790793028716514,\n", " 'Krippendorff': 0.0771050221129197,\n", " 'Invalid': 226,\n", @@ -14746,7 +14760,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.07390489212060948,\n", " 'Cohen': 0.12159081977521025,\n", - " 'Spearman': 0.681758944655894,\n", + " 'Spearman': 0.6865798016418396,\n", " 'Kendall': 0.5854514568692673,\n", " 'Krippendorff': 0.5631512640215335,\n", " 'Invalid': 3,\n", @@ -14793,7 +14807,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.11313747507970512,\n", " 'Cohen': 0.14348490442202,\n", - " 'Spearman': 0.6567311460881612,\n", + " 'Spearman': 0.6579838540956281,\n", " 'Kendall': 0.5353565007762726,\n", " 'Krippendorff': 0.5178339411692743,\n", " 'Invalid': 24,\n", @@ -14840,7 +14854,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 1, '3': 0, '4': 0, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.08129600150731557,\n", " 'Cohen': -0.019490842173828016,\n", - " 'Spearman': 0.6497219941488004,\n", + " 'Spearman': 0.6534612270353615,\n", " 'Kendall': 0.5533706953138916,\n", " 'Krippendorff': 0.2669345303512781,\n", " 'Invalid': 0,\n", @@ -14887,7 +14901,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'pt': {'phi-4': {'metrics': {'Fleiss': 0.22102833709328726,\n", " 'Cohen': 0.23424362076604355,\n", - " 'Spearman': 0.6084579778106662,\n", + " 'Spearman': 0.6200646754318665,\n", " 'Kendall': 0.5059833684653418,\n", " 'Krippendorff': 0.518575497495956,\n", " 'Invalid': 0,\n", @@ -14934,7 +14948,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06426558801798297,\n", " 'Cohen': 0.10540531480319715,\n", - " 'Spearman': 0.6213525435873598,\n", + " 'Spearman': 0.6298004540049054,\n", " 'Kendall': 0.5272039124255627,\n", " 'Krippendorff': 0.49354629688840057,\n", " 'Invalid': 0,\n", @@ -14981,7 +14995,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.18923930514940837,\n", " 'Cohen': 0.20802750558056826,\n", - " 'Spearman': 0.6788269952935843,\n", + " 'Spearman': 0.6852172123546514,\n", " 'Kendall': 0.5714712095888327,\n", " 'Krippendorff': 0.5904145498820064,\n", " 'Invalid': 0,\n", @@ -15028,7 +15042,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.053724558849817444,\n", " 'Cohen': 0.11261608609648976,\n", - " 'Spearman': 0.6651768889116937,\n", + " 'Spearman': 0.6713700137356197,\n", " 'Kendall': 0.5747220182081597,\n", " 'Krippendorff': 0.5520611044786139,\n", " 'Invalid': 0,\n", @@ -15075,7 +15089,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1647297121877503,\n", " 'Cohen': 0.18547162060169486,\n", - " 'Spearman': 0.6403936236937944,\n", + " 'Spearman': 0.6441188756506936,\n", " 'Kendall': 0.5376871616783945,\n", " 'Krippendorff': 0.5435927602330077,\n", " 'Invalid': 0,\n", @@ -15122,7 +15136,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.08948023240363821,\n", " 'Cohen': -0.01261462739920427,\n", - " 'Spearman': 0.5920041796475257,\n", + " 'Spearman': 0.5979050885526739,\n", " 'Kendall': 0.49889193176377716,\n", " 'Krippendorff': 0.22662089877878255,\n", " 'Invalid': 0,\n", @@ -15169,7 +15183,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.11052552585801768,\n", " 'Cohen': -0.042816875375444985,\n", - " 'Spearman': 0.6788114379395467,\n", + " 'Spearman': 0.6829944017592054,\n", " 'Kendall': 0.5809578323269349,\n", " 'Krippendorff': 0.2552333988508979,\n", " 'Invalid': 3,\n", @@ -15216,7 +15230,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.13664114837352337,\n", " 'Cohen': 0.16987039886949873,\n", - " 'Spearman': 0.6487019948342316,\n", + " 'Spearman': 0.6548304184744376,\n", " 'Kendall': 0.5543416043243656,\n", " 'Krippendorff': 0.5463734253773516,\n", " 'Invalid': 0,\n", @@ -15263,7 +15277,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07865119714943726,\n", " 'Cohen': -0.019425051334702292,\n", - " 'Spearman': 0.6193400811204306,\n", + " 'Spearman': 0.6281247255234246,\n", " 'Kendall': 0.51342241188897,\n", " 'Krippendorff': 0.2628089088187101,\n", " 'Invalid': 268,\n", @@ -15310,7 +15324,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.14889491852300177,\n", " 'Cohen': 0.18236557868180392,\n", - " 'Spearman': 0.6817494551907026,\n", + " 'Spearman': 0.6873702626299159,\n", " 'Kendall': 0.5839267610291519,\n", " 'Krippendorff': 0.5974593154718288,\n", " 'Invalid': 0,\n", @@ -15357,7 +15371,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.15854090426159842,\n", " 'Cohen': 0.17723398679760904,\n", - " 'Spearman': 0.6619816151053166,\n", + " 'Spearman': 0.6487259929645315,\n", " 'Kendall': 0.5434522844599411,\n", " 'Krippendorff': 0.5871515769487199,\n", " 'Invalid': 65,\n", @@ -15404,7 +15418,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05947511681052679,\n", " 'Cohen': 3.20559788979935e-05,\n", - " 'Spearman': 0.617980222932999,\n", + " 'Spearman': 0.6236014766333406,\n", " 'Kendall': 0.5203806054904722,\n", " 'Krippendorff': 0.2595830615505833,\n", " 'Invalid': 0,\n", @@ -15451,7 +15465,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'ga': {'phi-4': {'metrics': {'Fleiss': 0.12457104157927451,\n", " 'Cohen': 0.14925123893066417,\n", - " 'Spearman': 0.6254924312313971,\n", + " 'Spearman': 0.6342510093639441,\n", " 'Kendall': 0.5218157629215376,\n", " 'Krippendorff': 0.4669674866397687,\n", " 'Invalid': 0,\n", @@ -15498,7 +15512,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.06497775304449128,\n", " 'Cohen': 0.1089589817806943,\n", - " 'Spearman': 0.5174620021576043,\n", + " 'Spearman': 0.5189714955229375,\n", " 'Kendall': 0.4389795763893931,\n", " 'Krippendorff': 0.4499060958170651,\n", " 'Invalid': 0,\n", @@ -15545,7 +15559,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2071062417096718,\n", " 'Cohen': 0.22772139580147366,\n", - " 'Spearman': 0.6937590747955955,\n", + " 'Spearman': 0.7008924663672177,\n", " 'Kendall': 0.5814990188211127,\n", " 'Krippendorff': 0.6000949758713365,\n", " 'Invalid': 0,\n", @@ -15592,7 +15606,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.04193405533733551,\n", " 'Cohen': 0.10836568663792268,\n", - " 'Spearman': 0.6179259480981374,\n", + " 'Spearman': 0.618260212980319,\n", " 'Kendall': 0.530175668738537,\n", " 'Krippendorff': 0.5160297815644144,\n", " 'Invalid': 0,\n", @@ -15639,7 +15653,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.10834285771449867,\n", " 'Cohen': 0.1324206468944975,\n", - " 'Spearman': 0.6088868209848117,\n", + " 'Spearman': 0.6147307462328605,\n", " 'Kendall': 0.5055088444937663,\n", " 'Krippendorff': 0.5090494381296595,\n", " 'Invalid': 0,\n", @@ -15686,7 +15700,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10431285619069723,\n", " 'Cohen': -0.032989921821731105,\n", - " 'Spearman': 0.5546481421153001,\n", + " 'Spearman': 0.5561814345910385,\n", " 'Kendall': 0.4627855055227546,\n", " 'Krippendorff': 0.17237778409518656,\n", " 'Invalid': 0,\n", @@ -15733,7 +15747,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.062098929812091426,\n", " 'Cohen': -0.0034143250323936947,\n", - " 'Spearman': 0.6709149896182085,\n", + " 'Spearman': 0.6741647223298821,\n", " 'Kendall': 0.5691367101674724,\n", " 'Krippendorff': 0.308576939164782,\n", " 'Invalid': 1,\n", @@ -15780,7 +15794,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.14050066973639894,\n", " 'Cohen': 0.17930929515505023,\n", - " 'Spearman': 0.6820583393002873,\n", + " 'Spearman': 0.6816369364591798,\n", " 'Kendall': 0.5875288709506022,\n", " 'Krippendorff': 0.5811404257556978,\n", " 'Invalid': 0,\n", @@ -15827,7 +15841,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.1437979918753767,\n", " 'Cohen': -0.042296288357803746,\n", - " 'Spearman': 0.26294084134131585,\n", + " 'Spearman': 0.28026868821908546,\n", " 'Kendall': 0.21094026909975058,\n", " 'Krippendorff': -0.2108242810472163,\n", " 'Invalid': 147,\n", @@ -15874,7 +15888,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.05954056313288965,\n", " 'Cohen': 0.11965134706814573,\n", - " 'Spearman': 0.6419892624023276,\n", + " 'Spearman': 0.6441946775817693,\n", " 'Kendall': 0.5525683137159276,\n", " 'Krippendorff': 0.5369881411559905,\n", " 'Invalid': 0,\n", @@ -15921,7 +15935,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.04353483237202593,\n", " 'Cohen': 0.08023009549396332,\n", - " 'Spearman': 0.6282728911734249,\n", + " 'Spearman': 0.6144327619913339,\n", " 'Kendall': 0.5105225469740864,\n", " 'Krippendorff': 0.43858672805353127,\n", " 'Invalid': 32,\n", @@ -15968,7 +15982,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.08249456048468132,\n", " 'Cohen': -0.02146308573997069,\n", - " 'Spearman': 0.6158103318043068,\n", + " 'Spearman': 0.6225953537567184,\n", " 'Kendall': 0.5240824920036155,\n", " 'Krippendorff': 0.24245997035976063,\n", " 'Invalid': 0,\n", @@ -16015,7 +16029,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sr': {'phi-4': {'metrics': {'Fleiss': 0.20730770945514168,\n", " 'Cohen': 0.22252831343740442,\n", - " 'Spearman': 0.6506783699897731,\n", + " 'Spearman': 0.6593492179508463,\n", " 'Kendall': 0.5407279952306375,\n", " 'Krippendorff': 0.5241226886031578,\n", " 'Invalid': 1,\n", @@ -16062,7 +16076,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.08950246899043218,\n", " 'Cohen': 0.12608990482419657,\n", - " 'Spearman': 0.6206018212409361,\n", + " 'Spearman': 0.6273747864707626,\n", " 'Kendall': 0.5234333993278183,\n", " 'Krippendorff': 0.5151347071751727,\n", " 'Invalid': 0,\n", @@ -16109,7 +16123,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.22967447139801217,\n", " 'Cohen': 0.2479079349293173,\n", - " 'Spearman': 0.6790974648815822,\n", + " 'Spearman': 0.6870100190860253,\n", " 'Kendall': 0.5704261266474713,\n", " 'Krippendorff': 0.6066090041083707,\n", " 'Invalid': 0,\n", @@ -16156,7 +16170,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.04398509671821569,\n", " 'Cohen': 0.10105629916158343,\n", - " 'Spearman': 0.6392110483557758,\n", + " 'Spearman': 0.6451923877296519,\n", " 'Kendall': 0.5474482698212314,\n", " 'Krippendorff': 0.5309189739847024,\n", " 'Invalid': 0,\n", @@ -16203,7 +16217,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.13027983362299597,\n", " 'Cohen': 0.15358520686444044,\n", - " 'Spearman': 0.6596718655664434,\n", + " 'Spearman': 0.6657829767642025,\n", " 'Kendall': 0.5566894741120766,\n", " 'Krippendorff': 0.5517070514385931,\n", " 'Invalid': 0,\n", @@ -16250,7 +16264,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.12093691518261397,\n", " 'Cohen': -0.04204004669120942,\n", - " 'Spearman': 0.6259270867924381,\n", + " 'Spearman': 0.6334971901111014,\n", " 'Kendall': 0.533468659491098,\n", " 'Krippendorff': 0.21876226127808318,\n", " 'Invalid': 0,\n", @@ -16297,7 +16311,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.11685463506127491,\n", " 'Cohen': -0.046978667289385934,\n", - " 'Spearman': 0.691321221928529,\n", + " 'Spearman': 0.6956133403626067,\n", " 'Kendall': 0.5931064703185996,\n", " 'Krippendorff': 0.25285990173245854,\n", " 'Invalid': 2,\n", @@ -16344,7 +16358,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.21228215183862972,\n", " 'Cohen': 0.23874545375086798,\n", - " 'Spearman': 0.6918599552088621,\n", + " 'Spearman': 0.6961203304597621,\n", " 'Kendall': 0.5964742313023443,\n", " 'Krippendorff': 0.603033686697906,\n", " 'Invalid': 0,\n", @@ -16391,7 +16405,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.07686928274135153,\n", " 'Cohen': -0.002730748225013624,\n", - " 'Spearman': 0.3708692996481354,\n", + " 'Spearman': 0.37827235474335846,\n", " 'Kendall': 0.2961673784710649,\n", " 'Krippendorff': -0.04442786592757608,\n", " 'Invalid': 275,\n", @@ -16438,7 +16452,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10494429313542633,\n", " 'Cohen': 0.1457074331001128,\n", - " 'Spearman': 0.6701892878709204,\n", + " 'Spearman': 0.6773168029591019,\n", " 'Kendall': 0.5690610416494011,\n", " 'Krippendorff': 0.5601289786831702,\n", " 'Invalid': 3,\n", @@ -16485,7 +16499,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.15465422503547382,\n", " 'Cohen': 0.1734769030504757,\n", - " 'Spearman': 0.7129200043322576,\n", + " 'Spearman': 0.7076341648601796,\n", " 'Kendall': 0.5942565616396468,\n", " 'Krippendorff': 0.6243893375390726,\n", " 'Invalid': 45,\n", @@ -16532,7 +16546,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06638407756583596,\n", " 'Cohen': -0.0066598596278206745,\n", - " 'Spearman': 0.6369557046568095,\n", + " 'Spearman': 0.6434536100479542,\n", " 'Kendall': 0.541489911337688,\n", " 'Krippendorff': 0.2792745489954064,\n", " 'Invalid': 0,\n", @@ -16579,7 +16593,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'gl': {'phi-4': {'metrics': {'Fleiss': 0.21187438713714818,\n", " 'Cohen': 0.22574633187624948,\n", - " 'Spearman': 0.6340015698387376,\n", + " 'Spearman': 0.6432511041115291,\n", " 'Kendall': 0.5261019450887813,\n", " 'Krippendorff': 0.5334851189073117,\n", " 'Invalid': 0,\n", @@ -16626,7 +16640,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.07392082504161504,\n", " 'Cohen': 0.11562954180371754,\n", - " 'Spearman': 0.5812259108523925,\n", + " 'Spearman': 0.5822913412469801,\n", " 'Kendall': 0.49591557896440963,\n", " 'Krippendorff': 0.472053372622636,\n", " 'Invalid': 0,\n", @@ -16673,7 +16687,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.218579287527891,\n", " 'Cohen': 0.23668647391784292,\n", - " 'Spearman': 0.6839316298520874,\n", + " 'Spearman': 0.6917950794360014,\n", " 'Kendall': 0.5728227635604007,\n", " 'Krippendorff': 0.5990148104351336,\n", " 'Invalid': 0,\n", @@ -16720,7 +16734,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.021596215442745308,\n", " 'Cohen': 0.08918701114008054,\n", - " 'Spearman': 0.6243301957811804,\n", + " 'Spearman': 0.6297149099492506,\n", " 'Kendall': 0.5361626069990575,\n", " 'Krippendorff': 0.520630215894191,\n", " 'Invalid': 0,\n", @@ -16767,7 +16781,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.11717266059974014,\n", " 'Cohen': 0.14440285907248995,\n", - " 'Spearman': 0.6527368639730377,\n", + " 'Spearman': 0.6589372312871454,\n", " 'Kendall': 0.5487551974603594,\n", " 'Krippendorff': 0.5270318046903425,\n", " 'Invalid': 0,\n", @@ -16814,7 +16828,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.07655097119410685,\n", " 'Cohen': 0.0028093758473691777,\n", - " 'Spearman': 0.5799951949921415,\n", + " 'Spearman': 0.5846799876078983,\n", " 'Kendall': 0.486256342739207,\n", " 'Krippendorff': 0.1738090801197042,\n", " 'Invalid': 0,\n", @@ -16861,7 +16875,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.08028090836691847,\n", " 'Cohen': -0.01724819677942735,\n", - " 'Spearman': 0.7071067594216045,\n", + " 'Spearman': 0.7101106294235779,\n", " 'Kendall': 0.6063947049304294,\n", " 'Krippendorff': 0.305620594875214,\n", " 'Invalid': 0,\n", @@ -16908,7 +16922,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.19155859549482332,\n", " 'Cohen': 0.22118264732608617,\n", - " 'Spearman': 0.6825131541469606,\n", + " 'Spearman': 0.6915948903538425,\n", " 'Kendall': 0.5884237497585882,\n", " 'Krippendorff': 0.5902925698275671,\n", " 'Invalid': 0,\n", @@ -16955,7 +16969,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.08132644673725022,\n", " 'Cohen': -0.004994184853253092,\n", - " 'Spearman': 0.5609371739766963,\n", + " 'Spearman': 0.5643765681877343,\n", " 'Kendall': 0.4645598315786723,\n", " 'Krippendorff': 0.11570967136392052,\n", " 'Invalid': 285,\n", @@ -17002,7 +17016,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.14492429290026596,\n", " 'Cohen': 0.18305951183482272,\n", - " 'Spearman': 0.6994603238433144,\n", + " 'Spearman': 0.705290572851986,\n", " 'Kendall': 0.6047805220478177,\n", " 'Krippendorff': 0.5946248402679714,\n", " 'Invalid': 0,\n", @@ -17049,7 +17063,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.12641174595203097,\n", " 'Cohen': 0.14791596721906974,\n", - " 'Spearman': 0.6651830788195848,\n", + " 'Spearman': 0.6573589901042487,\n", " 'Kendall': 0.5406254412055883,\n", " 'Krippendorff': 0.5652205417601655,\n", " 'Invalid': 39,\n", @@ -17096,7 +17110,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.10576541615874548,\n", " 'Cohen': -0.04031415270608374,\n", - " 'Spearman': 0.6404493855815631,\n", + " 'Spearman': 0.6460335198853472,\n", " 'Kendall': 0.5489249710856442,\n", " 'Krippendorff': 0.24834996757336836,\n", " 'Invalid': 0,\n", @@ -17143,7 +17157,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sl': {'phi-4': {'metrics': {'Fleiss': 0.19266391608357403,\n", " 'Cohen': 0.20761881901104184,\n", - " 'Spearman': 0.6598664266737215,\n", + " 'Spearman': 0.6716898485821494,\n", " 'Kendall': 0.5489919013254142,\n", " 'Krippendorff': 0.5301271531552201,\n", " 'Invalid': 0,\n", @@ -17190,7 +17204,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.1081646442257588,\n", " 'Cohen': 0.1416010328624977,\n", - " 'Spearman': 0.6238143321344347,\n", + " 'Spearman': 0.6299814275864881,\n", " 'Kendall': 0.5282375132203505,\n", " 'Krippendorff': 0.5216337315060091,\n", " 'Invalid': 0,\n", @@ -17237,7 +17251,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.24806017687120926,\n", " 'Cohen': 0.26315439966227594,\n", - " 'Spearman': 0.6862072210053723,\n", + " 'Spearman': 0.6936223836067604,\n", " 'Kendall': 0.5784726459217217,\n", " 'Krippendorff': 0.6314313898248809,\n", " 'Invalid': 0,\n", @@ -17284,7 +17298,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.06229762984069424,\n", " 'Cohen': 0.1179800778730622,\n", - " 'Spearman': 0.6585306291399853,\n", + " 'Spearman': 0.6660980355488648,\n", " 'Kendall': 0.5663018693665679,\n", " 'Krippendorff': 0.5463347239114598,\n", " 'Invalid': 1,\n", @@ -17331,7 +17345,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.12375673699780677,\n", " 'Cohen': 0.14832126989522987,\n", - " 'Spearman': 0.6578452184100957,\n", + " 'Spearman': 0.6613875409307258,\n", " 'Kendall': 0.5497906591554118,\n", " 'Krippendorff': 0.5415908744330743,\n", " 'Invalid': 0,\n", @@ -17378,7 +17392,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.13923595462521693,\n", " 'Cohen': -0.05051992148124573,\n", - " 'Spearman': 0.6276055217642026,\n", + " 'Spearman': 0.6323671438316602,\n", " 'Kendall': 0.5361352717758541,\n", " 'Krippendorff': 0.1996477747760933,\n", " 'Invalid': 0,\n", @@ -17425,7 +17439,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.12479981119034371,\n", " 'Cohen': -0.05559900012204655,\n", - " 'Spearman': 0.7230704539307024,\n", + " 'Spearman': 0.7265484252690757,\n", " 'Kendall': 0.622514803705285,\n", " 'Krippendorff': 0.2700431636455105,\n", " 'Invalid': 0,\n", @@ -17472,7 +17486,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.18899211690635367,\n", " 'Cohen': 0.21740889323399526,\n", - " 'Spearman': 0.6839505636675683,\n", + " 'Spearman': 0.6890388882919357,\n", " 'Kendall': 0.589793019562599,\n", " 'Krippendorff': 0.5977866061953192,\n", " 'Invalid': 0,\n", @@ -17519,7 +17533,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.13600190801764916,\n", " 'Cohen': -0.0365007979109242,\n", - " 'Spearman': 0.45549423511786014,\n", + " 'Spearman': 0.4655219224245794,\n", " 'Kendall': 0.37198510779388705,\n", " 'Krippendorff': -0.10453379231573745,\n", " 'Invalid': 233,\n", @@ -17566,7 +17580,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.06734694930913634,\n", " 'Cohen': 0.11487800457513453,\n", - " 'Spearman': 0.681847078588012,\n", + " 'Spearman': 0.6851728161661139,\n", " 'Kendall': 0.5850502855854306,\n", " 'Krippendorff': 0.566868380957171,\n", " 'Invalid': 2,\n", @@ -17613,7 +17627,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1445366568743685,\n", " 'Cohen': 0.16807710657246056,\n", - " 'Spearman': 0.658244618960136,\n", + " 'Spearman': 0.6482438163992557,\n", " 'Kendall': 0.5403952851132321,\n", " 'Krippendorff': 0.5347226317157574,\n", " 'Invalid': 46,\n", @@ -17660,7 +17674,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.0730385598889096,\n", " 'Cohen': -0.009270172979516378,\n", - " 'Spearman': 0.6257959652485627,\n", + " 'Spearman': 0.6323502453497302,\n", " 'Kendall': 0.5299434413871362,\n", " 'Krippendorff': 0.2411743458599812,\n", " 'Invalid': 0,\n", @@ -17707,7 +17721,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'lv': {'phi-4': {'metrics': {'Fleiss': 0.21530792968615847,\n", " 'Cohen': 0.2279699959453979,\n", - " 'Spearman': 0.6605593148116243,\n", + " 'Spearman': 0.6663971242237371,\n", " 'Kendall': 0.5506696575257908,\n", " 'Krippendorff': 0.5705512305157412,\n", " 'Invalid': 0,\n", @@ -17754,7 +17768,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12364814527782084,\n", " 'Cohen': 0.15685086035626505,\n", - " 'Spearman': 0.5817896446994788,\n", + " 'Spearman': 0.5898477761428,\n", " 'Kendall': 0.4905216935658466,\n", " 'Krippendorff': 0.4984914567266746,\n", " 'Invalid': 0,\n", @@ -17801,7 +17815,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.25069325138529286,\n", " 'Cohen': 0.2671043538355219,\n", - " 'Spearman': 0.6920123163991659,\n", + " 'Spearman': 0.6993864912975261,\n", " 'Kendall': 0.5833994836461937,\n", " 'Krippendorff': 0.6303699936655691,\n", " 'Invalid': 0,\n", @@ -17848,7 +17862,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.03570232841272259,\n", " 'Cohen': 0.09437306158617631,\n", - " 'Spearman': 0.6285912490233438,\n", + " 'Spearman': 0.6331556240360017,\n", " 'Kendall': 0.5407020103393796,\n", " 'Krippendorff': 0.5110579316141894,\n", " 'Invalid': 0,\n", @@ -17895,7 +17909,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.15295976278148432,\n", " 'Cohen': 0.17328038562631054,\n", - " 'Spearman': 0.6531932465260446,\n", + " 'Spearman': 0.6602537350004568,\n", " 'Kendall': 0.5493163452342668,\n", " 'Krippendorff': 0.5472564045363023,\n", " 'Invalid': 0,\n", @@ -17942,7 +17956,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.12302046151525813,\n", " 'Cohen': -0.0380708750282146,\n", - " 'Spearman': 0.6431655452709906,\n", + " 'Spearman': 0.6448343402261263,\n", " 'Kendall': 0.543875842263305,\n", " 'Krippendorff': 0.20492885177360642,\n", " 'Invalid': 0,\n", @@ -17989,7 +18003,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10147443565877902,\n", " 'Cohen': -0.03449142053317389,\n", - " 'Spearman': 0.7164388720556818,\n", + " 'Spearman': 0.7190206300733474,\n", " 'Kendall': 0.6173644455947936,\n", " 'Krippendorff': 0.2844323768042787,\n", " 'Invalid': 2,\n", @@ -18036,7 +18050,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.15745031664938725,\n", " 'Cohen': 0.19181220405268096,\n", - " 'Spearman': 0.6648092904455963,\n", + " 'Spearman': 0.6688682534037828,\n", " 'Kendall': 0.5697969571291819,\n", " 'Krippendorff': 0.567469755497712,\n", " 'Invalid': 0,\n", @@ -18083,7 +18097,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.10956240171950164,\n", " 'Cohen': -0.011982755694354807,\n", - " 'Spearman': 0.50763462339627,\n", + " 'Spearman': 0.4895141793253782,\n", " 'Kendall': 0.4060737817958491,\n", " 'Krippendorff': -0.07158492031027297,\n", " 'Invalid': 254,\n", @@ -18130,7 +18144,7 @@ " '5': {'-1': 2, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.08097432521395662,\n", " 'Cohen': 0.1287862407862408,\n", - " 'Spearman': 0.679076755966462,\n", + " 'Spearman': 0.6817413928280561,\n", " 'Kendall': 0.5845637926908267,\n", " 'Krippendorff': 0.5534179055404889,\n", " 'Invalid': 3,\n", @@ -18177,7 +18191,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08535765130539082,\n", " 'Cohen': 0.11497681481682354,\n", - " 'Spearman': 0.6776898952634417,\n", + " 'Spearman': 0.6725985083561833,\n", " 'Kendall': 0.561325927638002,\n", " 'Krippendorff': 0.5124989068278222,\n", " 'Invalid': 38,\n", @@ -18224,7 +18238,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07185221617868302,\n", " 'Cohen': -0.00880437495745312,\n", - " 'Spearman': 0.6259117741442847,\n", + " 'Spearman': 0.6339129390027314,\n", " 'Kendall': 0.5309903421995182,\n", " 'Krippendorff': 0.24471234937515807,\n", " 'Invalid': 0,\n", @@ -18271,7 +18285,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'hu': {'phi-4': {'metrics': {'Fleiss': 0.21657438369629106,\n", " 'Cohen': 0.23120919388689887,\n", - " 'Spearman': 0.6468113833003012,\n", + " 'Spearman': 0.655409537814319,\n", " 'Kendall': 0.5407778162009823,\n", " 'Krippendorff': 0.5392635339166326,\n", " 'Invalid': 1,\n", @@ -18318,7 +18332,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.12755629545255412,\n", " 'Cohen': 0.16182766217399247,\n", - " 'Spearman': 0.5636475010853697,\n", + " 'Spearman': 0.569543047666189,\n", " 'Kendall': 0.47764109519110004,\n", " 'Krippendorff': 0.4912977107473687,\n", " 'Invalid': 0,\n", @@ -18365,7 +18379,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.23203753772256003,\n", " 'Cohen': 0.24909752409752406,\n", - " 'Spearman': 0.6845393245732467,\n", + " 'Spearman': 0.6912713295446201,\n", " 'Kendall': 0.5788083353585051,\n", " 'Krippendorff': 0.6240323476610714,\n", " 'Invalid': 0,\n", @@ -18412,7 +18426,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.07922542449533367,\n", " 'Cohen': 0.1379605661993245,\n", - " 'Spearman': 0.6351892826718665,\n", + " 'Spearman': 0.6396750234735307,\n", " 'Kendall': 0.5480039684809306,\n", " 'Krippendorff': 0.5347362347065028,\n", " 'Invalid': 2,\n", @@ -18459,7 +18473,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.11999630279163556,\n", " 'Cohen': 0.14226375908618893,\n", - " 'Spearman': 0.6260965932059598,\n", + " 'Spearman': 0.6307015192937804,\n", " 'Kendall': 0.5220418075704708,\n", " 'Krippendorff': 0.5353096750079398,\n", " 'Invalid': 0,\n", @@ -18506,7 +18520,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.08837624303826612,\n", " 'Cohen': -0.01112809565616546,\n", - " 'Spearman': 0.6087971792629935,\n", + " 'Spearman': 0.6136226059052038,\n", " 'Kendall': 0.5144554587977409,\n", " 'Krippendorff': 0.23168602824539675,\n", " 'Invalid': 0,\n", @@ -18553,7 +18567,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10798087924447802,\n", " 'Cohen': -0.039564598372474835,\n", - " 'Spearman': 0.701714052768582,\n", + " 'Spearman': 0.7069438868115568,\n", " 'Kendall': 0.6003368856847533,\n", " 'Krippendorff': 0.2692419885808678,\n", " 'Invalid': 2,\n", @@ -18600,7 +18614,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.18703059168345856,\n", " 'Cohen': 0.2184131548727648,\n", - " 'Spearman': 0.6772418217490799,\n", + " 'Spearman': 0.6838808777860244,\n", " 'Kendall': 0.5831470116690491,\n", " 'Krippendorff': 0.5898774007158286,\n", " 'Invalid': 0,\n", @@ -18647,7 +18661,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.06303242422241305,\n", " 'Cohen': 0.0023086815723823984,\n", - " 'Spearman': 0.47675299802345006,\n", + " 'Spearman': 0.4861010599623172,\n", " 'Kendall': 0.38348755372495963,\n", " 'Krippendorff': 0.07471479155179295,\n", " 'Invalid': 237,\n", @@ -18694,7 +18708,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.1330923939101788,\n", " 'Cohen': 0.17221891291826452,\n", - " 'Spearman': 0.6918260974807484,\n", + " 'Spearman': 0.6937409014390623,\n", " 'Kendall': 0.5956201310825481,\n", " 'Krippendorff': 0.5988176763026796,\n", " 'Invalid': 3,\n", @@ -18741,7 +18755,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.13125775079955615,\n", " 'Cohen': 0.15458962768491358,\n", - " 'Spearman': 0.6646846101784928,\n", + " 'Spearman': 0.6632654551829412,\n", " 'Kendall': 0.5466576478329774,\n", " 'Krippendorff': 0.5565959337375257,\n", " 'Invalid': 27,\n", @@ -18788,7 +18802,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.06173865563678709,\n", " 'Cohen': -0.0036724738039337623,\n", - " 'Spearman': 0.6147295725727329,\n", + " 'Spearman': 0.6196971473393985,\n", " 'Kendall': 0.5205804369822976,\n", " 'Krippendorff': 0.27471614220273766,\n", " 'Invalid': 0,\n", @@ -18835,7 +18849,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'uk': {'phi-4': {'metrics': {'Fleiss': 0.2693842313962089,\n", " 'Cohen': 0.277344438137368,\n", - " 'Spearman': 0.6363538283772251,\n", + " 'Spearman': 0.6432833830881047,\n", " 'Kendall': 0.5303844808642745,\n", " 'Krippendorff': 0.6028395079188598,\n", " 'Invalid': 0,\n", @@ -18882,7 +18896,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.1442178532177311,\n", " 'Cohen': 0.16939108223558497,\n", - " 'Spearman': 0.6023196539198984,\n", + " 'Spearman': 0.6098808033093035,\n", " 'Kendall': 0.506251854177832,\n", " 'Krippendorff': 0.5337573187388648,\n", " 'Invalid': 0,\n", @@ -18929,7 +18943,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.19297133955937656,\n", " 'Cohen': 0.2141180980161178,\n", - " 'Spearman': 0.6773142446208753,\n", + " 'Spearman': 0.685131043937179,\n", " 'Kendall': 0.5690873927208422,\n", " 'Krippendorff': 0.5912482839053306,\n", " 'Invalid': 0,\n", @@ -18976,7 +18990,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.05699127510099088,\n", " 'Cohen': 0.11396757347757913,\n", - " 'Spearman': 0.659165358845604,\n", + " 'Spearman': 0.6640427586047261,\n", " 'Kendall': 0.5651932409489093,\n", " 'Krippendorff': 0.5527569235985632,\n", " 'Invalid': 2,\n", @@ -19023,7 +19037,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.18166349714743268,\n", " 'Cohen': 0.1998357736540839,\n", - " 'Spearman': 0.6348509401209812,\n", + " 'Spearman': 0.6377648863114097,\n", " 'Kendall': 0.5335978130619256,\n", " 'Krippendorff': 0.575382973294181,\n", " 'Invalid': 0,\n", @@ -19070,7 +19084,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.07860852005000477,\n", " 'Cohen': -0.005747667531955214,\n", - " 'Spearman': 0.6281324717551418,\n", + " 'Spearman': 0.6321422018538426,\n", " 'Kendall': 0.5302105741113742,\n", " 'Krippendorff': 0.23949609740651412,\n", " 'Invalid': 0,\n", @@ -19117,7 +19131,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.12275958625517484,\n", " 'Cohen': -0.05496659000285775,\n", - " 'Spearman': 0.7063226088270085,\n", + " 'Spearman': 0.7155095997798218,\n", " 'Kendall': 0.6080344633777259,\n", " 'Krippendorff': 0.28633180276006276,\n", " 'Invalid': 1,\n", @@ -19164,7 +19178,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.19146578552657523,\n", " 'Cohen': 0.21983229864519271,\n", - " 'Spearman': 0.6621528110647548,\n", + " 'Spearman': 0.6680578124105967,\n", " 'Kendall': 0.5681339517135188,\n", " 'Krippendorff': 0.5712611302663977,\n", " 'Invalid': 0,\n", @@ -19211,7 +19225,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.12905535093634904,\n", " 'Cohen': -0.025345318182674825,\n", - " 'Spearman': 0.5625420341773433,\n", + " 'Spearman': 0.5821931606293557,\n", " 'Kendall': 0.4613231373737725,\n", " 'Krippendorff': -0.006650254469360073,\n", " 'Invalid': 267,\n", @@ -19258,7 +19272,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10862978776161722,\n", " 'Cohen': 0.15055160904432086,\n", - " 'Spearman': 0.6886876667953257,\n", + " 'Spearman': 0.695009138889551,\n", " 'Kendall': 0.591076332649804,\n", " 'Krippendorff': 0.5861321111679656,\n", " 'Invalid': 2,\n", @@ -19305,7 +19319,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.11971684016328439,\n", " 'Cohen': 0.14617689131197542,\n", - " 'Spearman': 0.6742438964397334,\n", + " 'Spearman': 0.6717546685015094,\n", " 'Kendall': 0.556389834304377,\n", " 'Krippendorff': 0.5347900121551901,\n", " 'Invalid': 36,\n", @@ -19352,7 +19366,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07636505610611957,\n", " 'Cohen': -0.01496261618526007,\n", - " 'Spearman': 0.6174763745499032,\n", + " 'Spearman': 0.6249029503566623,\n", " 'Kendall': 0.522417130802557,\n", " 'Krippendorff': 0.2529120300555532,\n", " 'Invalid': 0,\n", @@ -19399,7 +19413,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'ca': {'phi-4': {'metrics': {'Fleiss': 0.17831361331107629,\n", " 'Cohen': 0.19070611866501852,\n", - " 'Spearman': 0.611385051958766,\n", + " 'Spearman': 0.6180017329391815,\n", " 'Kendall': 0.5067990031483525,\n", " 'Krippendorff': 0.5194355876430539,\n", " 'Invalid': 0,\n", @@ -19446,7 +19460,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0750993630352153,\n", " 'Cohen': 0.11628138370203311,\n", - " 'Spearman': 0.5945863874728321,\n", + " 'Spearman': 0.5997658490681664,\n", " 'Kendall': 0.5062005395263326,\n", " 'Krippendorff': 0.47174575296634147,\n", " 'Invalid': 0,\n", @@ -19493,7 +19507,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.19319984163357365,\n", " 'Cohen': 0.21312127608786202,\n", - " 'Spearman': 0.6903647538425488,\n", + " 'Spearman': 0.6974814935461331,\n", " 'Kendall': 0.580379743012352,\n", " 'Krippendorff': 0.6014011529183101,\n", " 'Invalid': 0,\n", @@ -19540,7 +19554,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.05162086291057979,\n", " 'Cohen': 0.11251768845374222,\n", - " 'Spearman': 0.6335311685069026,\n", + " 'Spearman': 0.6406908495829057,\n", " 'Kendall': 0.5444107890383387,\n", " 'Krippendorff': 0.5382630509131168,\n", " 'Invalid': 1,\n", @@ -19587,7 +19601,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.09899026106922366,\n", " 'Cohen': 0.1254114239500459,\n", - " 'Spearman': 0.6282595802774786,\n", + " 'Spearman': 0.6343876230062511,\n", " 'Kendall': 0.5297263255286792,\n", " 'Krippendorff': 0.5157360156368811,\n", " 'Invalid': 0,\n", @@ -19634,7 +19648,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.11072564741107548,\n", " 'Cohen': -0.027634978557920187,\n", - " 'Spearman': 0.5720752130228948,\n", + " 'Spearman': 0.5716624441111349,\n", " 'Kendall': 0.4864398684911518,\n", " 'Krippendorff': 0.17731035772532522,\n", " 'Invalid': 0,\n", @@ -19681,7 +19695,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.10630326554721116,\n", " 'Cohen': -0.04034152224973009,\n", - " 'Spearman': 0.6904695051919532,\n", + " 'Spearman': 0.694205798877411,\n", " 'Kendall': 0.5914073507053571,\n", " 'Krippendorff': 0.28003581901245245,\n", " 'Invalid': 0,\n", @@ -19728,7 +19742,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.17397608099336748,\n", " 'Cohen': 0.19981208894456615,\n", - " 'Spearman': 0.6891155218410073,\n", + " 'Spearman': 0.6932757298897455,\n", " 'Kendall': 0.5914717883700847,\n", " 'Krippendorff': 0.5930899264677099,\n", " 'Invalid': 0,\n", @@ -19775,7 +19789,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.03935165845099843,\n", " 'Cohen': 0.017687934301958474,\n", - " 'Spearman': 0.4884748798473978,\n", + " 'Spearman': 0.5136596951085984,\n", " 'Kendall': 0.3893278868975052,\n", " 'Krippendorff': 0.1436247650595749,\n", " 'Invalid': 200,\n", @@ -19822,7 +19836,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.14000362802985208,\n", " 'Cohen': 0.17544865293884215,\n", - " 'Spearman': 0.6893277745958467,\n", + " 'Spearman': 0.6937024237665929,\n", " 'Kendall': 0.5922721148271676,\n", " 'Krippendorff': 0.5916766343963406,\n", " 'Invalid': 1,\n", @@ -19869,7 +19883,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1683538389658931,\n", " 'Cohen': 0.18790075790963434,\n", - " 'Spearman': 0.6453267100453163,\n", + " 'Spearman': 0.6423645566006883,\n", " 'Kendall': 0.5307952992673095,\n", " 'Krippendorff': 0.5524647176829218,\n", " 'Invalid': 66,\n", @@ -19916,7 +19930,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07746607994132747,\n", " 'Cohen': -0.017028893099176434,\n", - " 'Spearman': 0.6229923273582118,\n", + " 'Spearman': 0.6286548107407953,\n", " 'Kendall': 0.5306363617051746,\n", " 'Krippendorff': 0.26014855691345595,\n", " 'Invalid': 0,\n", @@ -19963,7 +19977,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'sk': {'phi-4': {'metrics': {'Fleiss': 0.17264271653543306,\n", " 'Cohen': 0.18670330361418974,\n", - " 'Spearman': 0.631389619545959,\n", + " 'Spearman': 0.6397282504729449,\n", " 'Kendall': 0.5197100254843949,\n", " 'Krippendorff': 0.5190247963780557,\n", " 'Invalid': 0,\n", @@ -20010,7 +20024,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.07412981139986374,\n", " 'Cohen': 0.1107121283307605,\n", - " 'Spearman': 0.6146627719369416,\n", + " 'Spearman': 0.6167839309809399,\n", " 'Kendall': 0.5222468702918995,\n", " 'Krippendorff': 0.5202622396467917,\n", " 'Invalid': 0,\n", @@ -20057,7 +20071,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2181952411250722,\n", " 'Cohen': 0.23492449772091017,\n", - " 'Spearman': 0.6579710515378643,\n", + " 'Spearman': 0.6684337833634436,\n", " 'Kendall': 0.5510740498743465,\n", " 'Krippendorff': 0.6103718596092135,\n", " 'Invalid': 0,\n", @@ -20104,7 +20118,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.048342285608446015,\n", " 'Cohen': 0.10679653267289002,\n", - " 'Spearman': 0.6358174123984415,\n", + " 'Spearman': 0.641541317508014,\n", " 'Kendall': 0.5474302130713258,\n", " 'Krippendorff': 0.5279824764060826,\n", " 'Invalid': 0,\n", @@ -20151,7 +20165,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.1716655843680271,\n", " 'Cohen': 0.18830289604753858,\n", - " 'Spearman': 0.6656682376159857,\n", + " 'Spearman': 0.670211922170725,\n", " 'Kendall': 0.562321811766549,\n", " 'Krippendorff': 0.5833517589365766,\n", " 'Invalid': 0,\n", @@ -20198,7 +20212,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.1284351812376951,\n", " 'Cohen': -0.03583662018898881,\n", - " 'Spearman': 0.6708625796446264,\n", + " 'Spearman': 0.6753241959121116,\n", " 'Kendall': 0.5686548568024709,\n", " 'Krippendorff': 0.20668165454985676,\n", " 'Invalid': 0,\n", @@ -20245,7 +20259,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09761719155385751,\n", " 'Cohen': -0.03268422056512765,\n", - " 'Spearman': 0.7107795646536091,\n", + " 'Spearman': 0.7149546903307722,\n", " 'Kendall': 0.609199053182785,\n", " 'Krippendorff': 0.29198860699444995,\n", " 'Invalid': 0,\n", @@ -20292,7 +20306,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.17430357361721502,\n", " 'Cohen': 0.20439131377889175,\n", - " 'Spearman': 0.6838219187268263,\n", + " 'Spearman': 0.6874930573300714,\n", " 'Kendall': 0.5901789195332865,\n", " 'Krippendorff': 0.5962824061357372,\n", " 'Invalid': 0,\n", @@ -20339,7 +20353,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.08192730473212113,\n", " 'Cohen': 0.0005996586558421058,\n", - " 'Spearman': 0.4682367683083657,\n", + " 'Spearman': 0.4751423036972329,\n", " 'Kendall': 0.37927531538435977,\n", " 'Krippendorff': -0.028618634026752687,\n", " 'Invalid': 197,\n", @@ -20386,7 +20400,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 1}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.10977857155780481,\n", " 'Cohen': 0.14976770823561936,\n", - " 'Spearman': 0.6917277973997606,\n", + " 'Spearman': 0.6965920640860854,\n", " 'Kendall': 0.5933981676558868,\n", " 'Krippendorff': 0.5894470335935262,\n", " 'Invalid': 3,\n", @@ -20433,7 +20447,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.1582030460954228,\n", " 'Cohen': 0.17821285706236967,\n", - " 'Spearman': 0.6440885184672338,\n", + " 'Spearman': 0.6412235033534106,\n", " 'Kendall': 0.5255588647034436,\n", " 'Krippendorff': 0.5547940287678588,\n", " 'Invalid': 42,\n", @@ -20480,7 +20494,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 0, '5': 1}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.07555889499782055,\n", " 'Cohen': -0.011711564773787764,\n", - " 'Spearman': 0.6257614908581333,\n", + " 'Spearman': 0.63050154868145,\n", " 'Kendall': 0.5288965868992437,\n", " 'Krippendorff': 0.26126625686550864,\n", " 'Invalid': 0,\n", @@ -20527,7 +20541,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'is': {'phi-4': {'metrics': {'Fleiss': 0.24829906467303545,\n", " 'Cohen': 0.25738329942118876,\n", - " 'Spearman': 0.6390398881697575,\n", + " 'Spearman': 0.6467467015767657,\n", " 'Kendall': 0.5363582347296141,\n", " 'Krippendorff': 0.5615008315951123,\n", " 'Invalid': 0,\n", @@ -20574,7 +20588,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.11474513431264584,\n", " 'Cohen': 0.14972193726040706,\n", - " 'Spearman': 0.5757815477887399,\n", + " 'Spearman': 0.5792693993864673,\n", " 'Kendall': 0.49294567052618765,\n", " 'Krippendorff': 0.5041813201841212,\n", " 'Invalid': 0,\n", @@ -20621,7 +20635,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.22030095585377948,\n", " 'Cohen': 0.23870068631100672,\n", - " 'Spearman': 0.6860482681400506,\n", + " 'Spearman': 0.6925519203730254,\n", " 'Kendall': 0.5762981331544373,\n", " 'Krippendorff': 0.6109393998373888,\n", " 'Invalid': 0,\n", @@ -20668,7 +20682,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.03770001032311345,\n", " 'Cohen': 0.1008979639078309,\n", - " 'Spearman': 0.6155771403243887,\n", + " 'Spearman': 0.6164756403472222,\n", " 'Kendall': 0.5295705414728494,\n", " 'Krippendorff': 0.5115077263813894,\n", " 'Invalid': 0,\n", @@ -20715,7 +20729,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.18805668817544835,\n", " 'Cohen': 0.20392786621190873,\n", - " 'Spearman': 0.6216709167503274,\n", + " 'Spearman': 0.6292548075959544,\n", " 'Kendall': 0.5209674515217705,\n", " 'Krippendorff': 0.5494058702149784,\n", " 'Invalid': 0,\n", @@ -20762,7 +20776,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.10609341169192696,\n", " 'Cohen': -0.031750935989240725,\n", - " 'Spearman': 0.6227803734426208,\n", + " 'Spearman': 0.6281084698087767,\n", " 'Kendall': 0.5242394007173374,\n", " 'Krippendorff': 0.20544530734890298,\n", " 'Invalid': 0,\n", @@ -20809,7 +20823,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09126559014024986,\n", " 'Cohen': -0.029942952553221103,\n", - " 'Spearman': 0.6542022075086104,\n", + " 'Spearman': 0.6578519166083495,\n", " 'Kendall': 0.5564398920967126,\n", " 'Krippendorff': 0.2836552339431012,\n", " 'Invalid': 1,\n", @@ -20856,7 +20870,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.15578600166183854,\n", " 'Cohen': 0.18835258866436477,\n", - " 'Spearman': 0.6762366373383476,\n", + " 'Spearman': 0.6811738936450203,\n", " 'Kendall': 0.5835274270638383,\n", " 'Krippendorff': 0.5760095968722173,\n", " 'Invalid': 0,\n", @@ -20903,7 +20917,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.13088838992084553,\n", " 'Cohen': -0.04477737035096907,\n", - " 'Spearman': 0.3402870685021774,\n", + " 'Spearman': 0.34731329014107054,\n", " 'Kendall': 0.2709305268090385,\n", " 'Krippendorff': -0.10531333676013133,\n", " 'Invalid': 275,\n", @@ -20950,7 +20964,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.09081913253614435,\n", " 'Cohen': 0.1378024507213379,\n", - " 'Spearman': 0.6937926674613915,\n", + " 'Spearman': 0.6962073028756561,\n", " 'Kendall': 0.5951333355513575,\n", " 'Krippendorff': 0.5769864910460258,\n", " 'Invalid': 2,\n", @@ -20997,7 +21011,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.08584667794421413,\n", " 'Cohen': 0.11745127351705076,\n", - " 'Spearman': 0.6182045340307559,\n", + " 'Spearman': 0.6210836942447183,\n", " 'Kendall': 0.4971360462549563,\n", " 'Krippendorff': 0.524569277672268,\n", " 'Invalid': 41,\n", @@ -21044,7 +21058,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.05472378578616315,\n", " 'Cohen': 0.0011176396933680888,\n", - " 'Spearman': 0.6148706711254508,\n", + " 'Spearman': 0.6214811757759677,\n", " 'Kendall': 0.5207574560952076,\n", " 'Krippendorff': 0.2915623558589544,\n", " 'Invalid': 0,\n", @@ -21091,7 +21105,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}},\n", " 'en': {'phi-4': {'metrics': {'Fleiss': 0.23993094797501208,\n", " 'Cohen': 0.24896917337522073,\n", - " 'Spearman': 0.6342027470822779,\n", + " 'Spearman': 0.6399471317308785,\n", " 'Kendall': 0.5249793452885182,\n", " 'Krippendorff': 0.567784125276659,\n", " 'Invalid': 1,\n", @@ -21138,7 +21152,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-14B-Instruct': {'metrics': {'Fleiss': 0.0717828968755195,\n", " 'Cohen': 0.11337713684330297,\n", - " 'Spearman': 0.5936233242208634,\n", + " 'Spearman': 0.601031622722745,\n", " 'Kendall': 0.5067679635083551,\n", " 'Krippendorff': 0.4906785954856199,\n", " 'Invalid': 0,\n", @@ -21185,7 +21199,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Llama-3.3-70B-Instruct': {'metrics': {'Fleiss': 0.2046004842615012,\n", " 'Cohen': 0.2250110001217035,\n", - " 'Spearman': 0.6865733374724403,\n", + " 'Spearman': 0.6923941758637462,\n", " 'Kendall': 0.5793028368744321,\n", " 'Krippendorff': 0.6058481057178213,\n", " 'Invalid': 0,\n", @@ -21232,7 +21246,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 2}}},\n", " 'gemma-2-27b-it': {'metrics': {'Fleiss': 0.06032009053065508,\n", " 'Cohen': 0.11404728789986096,\n", - " 'Spearman': 0.6679900273712865,\n", + " 'Spearman': 0.6722676976109881,\n", " 'Kendall': 0.5769914456423153,\n", " 'Krippendorff': 0.5423307740032739,\n", " 'Invalid': 0,\n", @@ -21279,7 +21293,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Qwen2.5-32B-Instruct': {'metrics': {'Fleiss': 0.20016043748563153,\n", " 'Cohen': 0.21535132126353773,\n", - " 'Spearman': 0.6448531825484114,\n", + " 'Spearman': 0.6492893432244073,\n", " 'Kendall': 0.5440255102024589,\n", " 'Krippendorff': 0.6000020380564974,\n", " 'Invalid': 0,\n", @@ -21326,7 +21340,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-7B-Instruct': {'metrics': {'Fleiss': -0.06549118992997581,\n", " 'Cohen': 0.0024289968243115245,\n", - " 'Spearman': 0.6552767064593408,\n", + " 'Spearman': 0.6595291685609866,\n", " 'Kendall': 0.5573747415151047,\n", " 'Krippendorff': 0.33878320080769697,\n", " 'Invalid': 0,\n", @@ -21373,7 +21387,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'gemma-3-27b-it': {'metrics': {'Fleiss': -0.09321047526673132,\n", " 'Cohen': -0.027124806918580102,\n", - " 'Spearman': 0.6945292217290485,\n", + " 'Spearman': 0.6997657000494523,\n", " 'Kendall': 0.5917569903227342,\n", " 'Krippendorff': 0.26328740529471906,\n", " 'Invalid': 1,\n", @@ -21420,7 +21434,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 1}}},\n", " 'Mistral-Small-3.1-24B-Instruct-2503': {'metrics': {'Fleiss': 0.2030603423577392,\n", " 'Cohen': 0.22911234389986457,\n", - " 'Spearman': 0.6802434122230671,\n", + " 'Spearman': 0.686598954251573,\n", " 'Kendall': 0.5809625091677925,\n", " 'Krippendorff': 0.5942336007000478,\n", " 'Invalid': 0,\n", @@ -21467,7 +21481,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 1, '4': 1, '5': 0}}},\n", " 'Llama-3.2-3B-Instruct': {'metrics': {'Fleiss': -0.015194313931290941,\n", " 'Cohen': 0.044031415001724694,\n", - " 'Spearman': 0.5190235352094755,\n", + " 'Spearman': 0.5246848735548737,\n", " 'Kendall': 0.4223291996288165,\n", " 'Krippendorff': 0.2244617734534572,\n", " 'Invalid': 212,\n", @@ -21514,7 +21528,7 @@ " '5': {'-1': 1, '0': 0, '1': 0, '2': 0, '3': 0, '4': 1, '5': 0}}},\n", " 'gemma-2-9b-it': {'metrics': {'Fleiss': 0.16980417350263502,\n", " 'Cohen': 0.20283123202831232,\n", - " 'Spearman': 0.6927573544729271,\n", + " 'Spearman': 0.696039557933567,\n", " 'Kendall': 0.59414305625388,\n", " 'Krippendorff': 0.6197253239511314,\n", " 'Invalid': 1,\n", @@ -21561,7 +21575,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 2, '4': 0, '5': 0}}},\n", " 'Llama-3.1-8B-Instruct': {'metrics': {'Fleiss': 0.14013325530803808,\n", " 'Cohen': 0.16073642259264187,\n", - " 'Spearman': 0.6592540559697546,\n", + " 'Spearman': 0.6574998965887701,\n", " 'Kendall': 0.5434094381749343,\n", " 'Krippendorff': 0.5721133943736478,\n", " 'Invalid': 19,\n", @@ -21608,7 +21622,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}},\n", " 'Qwen2.5-72B-Instruct': {'metrics': {'Fleiss': -0.04149722289302098,\n", " 'Cohen': 0.009967265498386335,\n", - " 'Spearman': 0.6197428534095925,\n", + " 'Spearman': 0.6266890413298536,\n", " 'Kendall': 0.5264194487824005,\n", " 'Krippendorff': 0.3479816108585173,\n", " 'Invalid': 0,\n", @@ -21655,7 +21669,7 @@ " '5': {'-1': 0, '0': 0, '1': 0, '2': 0, '3': 0, '4': 2, '5': 0}}}}}" ] }, - "execution_count": 93, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -21676,466 +21690,466 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 21, "id": "773163e1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'bg': {'phi-4': 0.3007767238307655,\n", - " 'Qwen2.5-14B-Instruct': 0.27892558085476743,\n", - " 'Llama-3.3-70B-Instruct': 0.28429684004747086,\n", - " 'gemma-2-27b-it': 0.19655877639811004,\n", - " 'Qwen2.5-32B-Instruct': 0.3737258417905565,\n", - " 'Qwen2.5-7B-Instruct': 0.11355093565748602,\n", - " 'gemma-3-27b-it': 0.1314626366852865,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2767890378705405,\n", - " 'Llama-3.2-3B-Instruct': 0.08788561489818225,\n", - " 'gemma-2-9b-it': 0.2543133455470617,\n", - " 'Llama-3.1-8B-Instruct': 0.25640917913565986,\n", - " 'Qwen2.5-72B-Instruct': 0.12917755405681397},\n", - " 'nn': {'phi-4': 0.30331100804126787,\n", - " 'Qwen2.5-14B-Instruct': 0.219855607684768,\n", - " 'Llama-3.3-70B-Instruct': 0.32617488476870493,\n", - " 'gemma-2-27b-it': 0.2043518470748518,\n", - " 'Qwen2.5-32B-Instruct': 0.23588316380290322,\n", - " 'Qwen2.5-7B-Instruct': 0.08381818082540476,\n", - " 'gemma-3-27b-it': 0.10303833901376303,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.26659042774242714,\n", - " 'Llama-3.2-3B-Instruct': 0.15591916400981207,\n", - " 'gemma-2-9b-it': 0.23480436998776597,\n", - " 'Llama-3.1-8B-Instruct': 0.2502685148871469,\n", - " 'Qwen2.5-72B-Instruct': 0.12594242470678008},\n", - " 'sq': {'phi-4': 0.32050018285113074,\n", - " 'Qwen2.5-14B-Instruct': 0.23492841581076876,\n", - " 'Llama-3.3-70B-Instruct': 0.28740917577263464,\n", - " 'gemma-2-27b-it': 0.17437667728788542,\n", - " 'Qwen2.5-32B-Instruct': 0.22070050106091985,\n", - " 'Qwen2.5-7B-Instruct': 0.05932116833293529,\n", - " 'gemma-3-27b-it': 0.09706645147792976,\n", - " 'Mistral-Small-3.1-24B-Instruct-2503': 0.2597521681922373,\n", - " 'Llama-3.2-3B-Instruct': 0.13397217776205372,\n", - " 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0.7069438868115568,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.6838808777860244,\n", + " 'Llama-3.2-3B-Instruct': 0.4861010599623172,\n", + " 'gemma-2-9b-it': 0.6937409014390623,\n", + " 'Llama-3.1-8B-Instruct': 0.6632654551829412,\n", + " 'Qwen2.5-72B-Instruct': 0.6196971473393985},\n", + " 'uk': {'phi-4': 0.6432833830881047,\n", + " 'Qwen2.5-14B-Instruct': 0.6098808033093035,\n", + " 'Llama-3.3-70B-Instruct': 0.685131043937179,\n", + " 'gemma-2-27b-it': 0.6640427586047261,\n", + " 'Qwen2.5-32B-Instruct': 0.6377648863114097,\n", + " 'Qwen2.5-7B-Instruct': 0.6321422018538426,\n", + " 'gemma-3-27b-it': 0.7155095997798218,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.6680578124105967,\n", + " 'Llama-3.2-3B-Instruct': 0.5821931606293557,\n", + " 'gemma-2-9b-it': 0.695009138889551,\n", + " 'Llama-3.1-8B-Instruct': 0.6717546685015094,\n", + " 'Qwen2.5-72B-Instruct': 0.6249029503566623},\n", + " 'ca': {'phi-4': 0.6180017329391815,\n", + " 'Qwen2.5-14B-Instruct': 0.5997658490681664,\n", + " 'Llama-3.3-70B-Instruct': 0.6974814935461331,\n", + " 'gemma-2-27b-it': 0.6406908495829057,\n", + " 'Qwen2.5-32B-Instruct': 0.6343876230062511,\n", + " 'Qwen2.5-7B-Instruct': 0.5716624441111349,\n", + " 'gemma-3-27b-it': 0.694205798877411,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.6932757298897455,\n", + " 'Llama-3.2-3B-Instruct': 0.5136596951085984,\n", + " 'gemma-2-9b-it': 0.6937024237665929,\n", + " 'Llama-3.1-8B-Instruct': 0.6423645566006883,\n", + " 'Qwen2.5-72B-Instruct': 0.6286548107407953},\n", + " 'sk': {'phi-4': 0.6397282504729449,\n", + " 'Qwen2.5-14B-Instruct': 0.6167839309809399,\n", + " 'Llama-3.3-70B-Instruct': 0.6684337833634436,\n", + " 'gemma-2-27b-it': 0.641541317508014,\n", + " 'Qwen2.5-32B-Instruct': 0.670211922170725,\n", + " 'Qwen2.5-7B-Instruct': 0.6753241959121116,\n", + " 'gemma-3-27b-it': 0.7149546903307722,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.6874930573300714,\n", + " 'Llama-3.2-3B-Instruct': 0.4751423036972329,\n", + " 'gemma-2-9b-it': 0.6965920640860854,\n", + " 'Llama-3.1-8B-Instruct': 0.6412235033534106,\n", + " 'Qwen2.5-72B-Instruct': 0.63050154868145},\n", + " 'is': {'phi-4': 0.6467467015767657,\n", + " 'Qwen2.5-14B-Instruct': 0.5792693993864673,\n", + " 'Llama-3.3-70B-Instruct': 0.6925519203730254,\n", + " 'gemma-2-27b-it': 0.6164756403472222,\n", + " 'Qwen2.5-32B-Instruct': 0.6292548075959544,\n", + " 'Qwen2.5-7B-Instruct': 0.6281084698087767,\n", + " 'gemma-3-27b-it': 0.6578519166083495,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.6811738936450203,\n", + " 'Llama-3.2-3B-Instruct': 0.34731329014107054,\n", + " 'gemma-2-9b-it': 0.6962073028756561,\n", + " 'Llama-3.1-8B-Instruct': 0.6210836942447183,\n", + " 'Qwen2.5-72B-Instruct': 0.6214811757759677},\n", + " 'en': {'phi-4': 0.6399471317308785,\n", + " 'Qwen2.5-14B-Instruct': 0.601031622722745,\n", + " 'Llama-3.3-70B-Instruct': 0.6923941758637462,\n", + " 'gemma-2-27b-it': 0.6722676976109881,\n", + " 'Qwen2.5-32B-Instruct': 0.6492893432244073,\n", + " 'Qwen2.5-7B-Instruct': 0.6595291685609866,\n", + " 'gemma-3-27b-it': 0.6997657000494523,\n", + " 'Mistral-Small-3.1-24B-Instruct-2503': 0.686598954251573,\n", + " 'Llama-3.2-3B-Instruct': 0.5246848735548737,\n", + " 'gemma-2-9b-it': 0.696039557933567,\n", + " 'Llama-3.1-8B-Instruct': 0.6574998965887701,\n", + " 'Qwen2.5-72B-Instruct': 0.6266890413298536}}" ] }, - "execution_count": 107, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "metric_name = \"Macro-F1\" # \"Macro-F1\" # \"Spearman\" # \"Macro-F1\" # \"Spearman\" # \"NDCG@all\"\n", + "metric_name = \"Spearman\" # \"Macro-F1\" # \"Spearman\" # \"Macro-F1\" # \"Spearman\" # \"NDCG@all\"\n", "\n", "metric_results = {lang: {model: subsubresult[\"metrics\"][metric_name] for model, subsubresult in subresult.items()} for lang,subresult in results_complete.items()}\n", "metric_results" @@ -22151,7 +22165,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 22, "id": "6ce47470", "metadata": {}, "outputs": [], @@ -22162,19 +22176,19 @@ "\n", "avg_37 = metric_df.mean(axis=1)\n", "metric_df = metric_df[list(language_codes.keys())]\n", - "metric_df[\"avg-10\"] = metric_df.mean(axis=1)\n", + "metric_df[\"avg-13\"] = metric_df.mean(axis=1)\n", "metric_df[\"avg-37\"] = avg_37" ] }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 23, "id": "e9caf110", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -22222,7 +22236,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "id": "6d7739ea", "metadata": {}, "outputs": [], @@ -22240,14 +22254,134 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 25, "id": "a7766cf9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'fi': {'phi-4': {'F1-0.5': 0.8406961178045516,\n", + "{'bg': {'phi-4': {'F1-0.5': 0.8461538461538461,\n", + " 'F1-1.5': 0.749003984063745,\n", + " 'F1-2.5': 0.6060606060606061,\n", + " 'F1-3.5': 0.14084507042253522,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': 0.8173690932311622,\n", + " 'F1-1.5': 0.7393939393939394,\n", + " 'F1-2.5': 0.5259259259259259,\n", + " 'F1-3.5': 0.26666666666666666,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': 0.855191256830601,\n", + " 'F1-1.5': 0.7913385826771654,\n", + " 'F1-2.5': 0.6198083067092651,\n", + " 'F1-3.5': 0.1342281879194631,\n", + " 'F1-4.5': 0.125},\n", + " 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{'phi-4': {'F1-0.5': 0.8418156808803301,\n", " 'F1-1.5': 0.7410207939508506,\n", " 'F1-2.5': 0.5590062111801242,\n", @@ -22547,6 +22741,66 @@ " 'F1-2.5': 0.5473684210526316,\n", " 'F1-3.5': 0.14473684210526316,\n", " 'F1-4.5': 0.0}},\n", + " 'de': {'phi-4': {'F1-0.5': 0.8421052631578947,\n", + " 'F1-1.5': 0.76,\n", + " 'F1-2.5': 0.5529411764705883,\n", + " 'F1-3.5': 0.21052631578947367,\n", + " 'F1-4.5': 0.0},\n", + " 'Qwen2.5-14B-Instruct': {'F1-0.5': 0.7980295566502463,\n", + " 'F1-1.5': 0.7234848484848485,\n", + " 'F1-2.5': 0.5428571428571428,\n", + " 'F1-3.5': 0.1509433962264151,\n", + " 'F1-4.5': 0.0},\n", + " 'Llama-3.3-70B-Instruct': {'F1-0.5': 0.8649386084583902,\n", + " 'F1-1.5': 0.793713163064833,\n", + " 'F1-2.5': 0.6070287539936102,\n", + " 'F1-3.5': 0.15172413793103448,\n", + " 'F1-4.5': 0.14285714285714285},\n", + " 'gemma-2-27b-it': {'F1-0.5': 0.78125,\n", + " 'F1-1.5': 0.7473903966597077,\n", + " 'F1-2.5': 0.5150214592274678,\n", + " 'F1-3.5': 0.21621621621621623,\n", + 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'Llama-3.1-8B-Instruct': {'F1-0.5': np.float64(0.8295528541963014),\n", - " 'F1-1.5': np.float64(0.7614422792261674),\n", - " 'F1-2.5': np.float64(0.6230111832308236),\n", - " 'F1-3.5': np.float64(0.14456943280818038),\n", - " 'F1-4.5': np.float64(0.11507381507381506)},\n", - " 'Qwen2.5-72B-Instruct': {'F1-0.5': np.float64(0.7850647229253985),\n", - " 'F1-1.5': np.float64(0.6750876463030314),\n", - " 'F1-2.5': np.float64(0.5509999191472642),\n", - " 'F1-3.5': np.float64(0.16135963146573704),\n", + " 'Llama-3.1-8B-Instruct': {'F1-0.5': np.float64(0.83394976109212),\n", + " 'F1-1.5': np.float64(0.7608475493213457),\n", + " 'F1-2.5': np.float64(0.6194359459058413),\n", + " 'F1-3.5': np.float64(0.14243872373819372),\n", + " 'F1-4.5': np.float64(0.15720006489237257)},\n", + " 'Qwen2.5-72B-Instruct': {'F1-0.5': np.float64(0.7849783344318181),\n", + " 'F1-1.5': np.float64(0.6758250259629394),\n", + " 'F1-2.5': np.float64(0.5477845310447756),\n", + " 'F1-3.5': np.float64(0.15889754505156187),\n", " 'F1-4.5': np.float64(0.0)}}" ] }, - "execution_count": 23, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -22905,13 +23159,13 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 27, "id": "a049a58e", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -22950,7 +23204,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 28, "id": "13ca1ac3", "metadata": {}, "outputs": [], @@ -22976,41 +23230,50 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 56, "id": "d37c12bb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'pol': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/pol_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + "{'bul': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/bul_Cyrl_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'pol': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/pol_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'ita': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ita_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'tur': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/tur_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'ukr': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ukr_Cyrl_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'fin': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fin_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'ell': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/ell_Grek_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'nob': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/nob_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'lit': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/lit_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'fra': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/fra_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", " 'spa': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/spa_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", - " 'hun': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/hun_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl')}" + " 'hun': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/hun_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl'),\n", + " 'deu': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/deu_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl')}" ] }, - "execution_count": 59, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "language_codes_500k_docs = {\n", + " \"bul\": \"Bulgarian\",\n", + " \"pol\": \"Polish\",\n", + " \"ukr\": \"Ukrainian\",\n", + " \"deu\": \"German\",\n", + " \"nob\": \"Norwegian\", # Bokmal\n", " \"spa\": \"Spanish\",\n", " \"fra\": \"French\",\n", " \"ita\": \"Italian\",\n", - " \"pol\": \"Polish\",\n", - " \"ell\": \"Greek\", # Modern Greek\n", - " \"nob\": \"Norwegian\", # Norwegian Bokmål (dominant variety)\n", - " \"hun\": \"Hungarian\",\n", " \"fin\": \"Finnish\",\n", + " \"hun\": \"Hungarian\",\n", " \"lit\": \"Lithuanian\",\n", + " \"ell\": \"Greek\", # Modern Greek\n", + " \"tur\": \"Turkish\",\n", "}\n", + "\n", "model = ablated_models[2]\n", "model_annotations_paths = list((annotated_500k_samples_path / f\"{model}_aggregated\").glob(\"**/*.jsonl\"))\n", "# filter only the languages that we want to check\n", @@ -23020,7 +23283,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 57, "id": "57d3b39d", "metadata": {}, "outputs": [], @@ -23040,13 +23303,13 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": 58, "id": "dc8466ca", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -23074,13 +23337,13 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 60, "id": "7cd98dd1", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -23104,11 +23367,11 @@ " count = sum(counts[s]/num_scores for s in all_scores_sorted[i:])\n", " y_cumulative.append(count)\n", "\n", - " plt.plot(all_scores_sorted, y_cumulative, label=lang)\n", + " plt.plot(all_scores_sorted, y_cumulative, label=language_codes_500k_docs[lang])\n", "\n", "plt.xlabel(\"Score\")\n", "plt.ylabel(\"Number of Scores ≥ Score\")\n", - "plt.title(\"Right-Cumulative Score Distribution per Language\")\n", + "# plt.title(\"Right-Cumulative Score Distribution per Language\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.tight_layout()\n", @@ -23135,7 +23398,7 @@ }, { "cell_type": "code", - "execution_count": 139, + "execution_count": 33, "id": "22168b01", "metadata": {}, "outputs": [ @@ -23153,7 +23416,7 @@ " 'hun': PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/educational_content/Mistral-Small-3.1-24B-Instruct-2503_aggregated/hun_Latn_sampled_500k_Mistral-Small-3.1-24B-Instruct-2503_aggregated_scores_majority.jsonl')}" ] }, - "execution_count": 139, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -23179,7 +23442,7 @@ }, { "cell_type": "code", - "execution_count": 140, + "execution_count": 34, "id": "3cf84acb", "metadata": {}, "outputs": [], @@ -23199,7 +23462,7 @@ }, { "cell_type": "code", - "execution_count": 141, + "execution_count": 35, "id": "06bad9bb", "metadata": {}, "outputs": [], @@ -23225,7 +23488,7 @@ }, { "cell_type": "code", - "execution_count": 142, + "execution_count": 36, "id": "bcaa53ba", "metadata": {}, "outputs": [ @@ -23285,13 +23548,13 @@ }, { "cell_type": "code", - "execution_count": 121, + "execution_count": 55, "id": "dee2de32", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -23309,13 +23572,13 @@ "plt.legend()\n", "plt.grid(True)\n", "plt.tight_layout()\n", - "plt.savefig(plot_path / f\"llm_annotator_cummulative_score_dist_{model}.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", + "# plt.savefig(plot_path / f\"llm_annotator_cummulative_score_dist_{model}.pdf\", format=\"pdf\", bbox_inches=\"tight\", pad_inches=0)\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 110, + "execution_count": 38, "id": "5b50d0e9", "metadata": {}, "outputs": [ @@ -23340,7 +23603,7 @@ " 4.229837272117517e-05]" ] }, - "execution_count": 110, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -23359,7 +23622,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "12321a47", "metadata": {}, "outputs": [], @@ -23382,6 +23645,2728 @@ " \n", " series_list.append((all_scores_sorted, y_cumulative))" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "49c90381", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6a3ed6d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e9093fb", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a37ce0d6", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4508855c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "b96015d0", + "metadata": {}, + "source": [ + "## Human Annotations without Integer Scores" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "6fbcc419", + "metadata": {}, + "outputs": [], + "source": [ + "de_511 = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_de_deepl.jsonl\")\n", + "en_511 = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_aggregated_scores/511_test_documents_educational_content_en.jsonl\")\n", + "en_non_agg = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_human_as_a_judge/human_raw_scores/annotations__educational_content__en__gt.jsonl\")" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "dcabba2d", + "metadata": {}, + "outputs": [], + "source": [ + "de_511_list = []\n", + "en_511_list = []\n", + "en_non_agg_list = []\n", + "with open(de_511, 'r') as f:\n", + " for line in f:\n", + " de_511_list.append(json.loads(line))\n", + "\n", + "with open(en_511, 'r') as f:\n", + " for line in f:\n", + " en_511_list.append(json.loads(line))\n", + "\n", + "with open(en_non_agg, 'r') as f:\n", + " for line in f:\n", + " en_non_agg_list.append(json.loads(line))" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "b1412f3a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(511, 511)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(en_511_list), len(de_511_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "1ed7ccc4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Document ID: 0\n", + "Score: 2.0\n", + "Scores: [2, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 1\n", + "Score: 3.0\n", + "Scores: [3, 3, 1]\n", 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"========================================================================================================\n", + "Document ID: 347\n", + "Score: 1.0\n", + "Scores: [2, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 348\n", + "Score: 0.0\n", + "Scores: [2, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 349\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 350\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 351\n", + "Score: 2.0\n", + "Scores: [4, 2, 0]\n", + "========================================================================================================\n", + "Document ID: 352\n", + "Score: 4.0\n", + "Scores: [4, 1, 4]\n", + "========================================================================================================\n", + "Document ID: 353\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 354\n", + "Score: 0.0\n", + "Scores: [2, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 355\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 356\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 357\n", + "Score: 1.0\n", + "Scores: [0, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 358\n", + "Score: 3.0\n", + "Scores: [3, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 359\n", + "Score: 1.6666666666666667\n", + "Scores: [2, 3, 0]\n", + "========================================================================================================\n", + "Document ID: 360\n", + "Score: 2.0\n", + "Scores: [2, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 361\n", + "Score: 3.3333333333333335\n", + "Scores: [3, 2, 5]\n", + "========================================================================================================\n", + "Document ID: 362\n", + "Score: 3.0\n", + "Scores: [3, 3, 5]\n", + "========================================================================================================\n", + "Document ID: 363\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 364\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 365\n", + "Score: 3.0\n", + "Scores: [2, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 366\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 367\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 368\n", + "Score: 1.0\n", + "Scores: [2, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 369\n", + "Score: 4.0\n", + "Scores: [4, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 370\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 371\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 372\n", + "Score: 2.3333333333333335\n", + "Scores: [4, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 373\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 374\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 375\n", + "Score: 3.0\n", + "Scores: [3, 2, 4]\n", + "========================================================================================================\n", + "Document ID: 376\n", + "Score: 2.0\n", + "Scores: [2, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 377\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 378\n", + "Score: 2.0\n", + "Scores: [1, 2, 3]\n", + "========================================================================================================\n", + "Document ID: 379\n", + "Score: 4.0\n", + "Scores: [4, 2, 4]\n", + "========================================================================================================\n", + "Document ID: 380\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 381\n", + "Score: 2.0\n", + "Scores: [3, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 382\n", + "Score: 2.0\n", + "Scores: [2, 0, 2]\n", + "========================================================================================================\n", + "Document ID: 383\n", + "Score: 1.0\n", + "Scores: [1, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 384\n", + "Score: 2.0\n", + "Scores: [2, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 385\n", + "Score: 1.0\n", + "Scores: [1, 2, 1]\n", + "========================================================================================================\n", + "Document ID: 386\n", + "Score: 1.3333333333333333\n", + "Scores: [3, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 387\n", + "Score: 1.0\n", + "Scores: [1, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 388\n", + "Score: 4.0\n", + "Scores: [4, 4, 4]\n", + "========================================================================================================\n", + "Document ID: 389\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 390\n", + "Score: 3.0\n", + "Scores: [3, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 391\n", + "Score: 2.0\n", + "Scores: [2, 2, 1]\n", + "========================================================================================================\n", + "Document ID: 392\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 393\n", + "Score: 3.0\n", + "Scores: [4, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 394\n", + "Score: 0.0\n", + "Scores: [0, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 395\n", + "Score: 2.0\n", + "Scores: [3, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 396\n", + "Score: 3.0\n", + "Scores: [3, 1, 3]\n", + "========================================================================================================\n", + "Document ID: 397\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 398\n", + "Score: 1.0\n", + "Scores: [3, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 399\n", + "Score: 1.0\n", + "Scores: [2, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 400\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 401\n", + "Score: 0.0\n", + "Scores: [0, 0, 2]\n", + "========================================================================================================\n", + "Document ID: 402\n", + "Score: 1.0\n", + "Scores: [3, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 403\n", + "Score: 2.0\n", + "Scores: [2, 0, 2]\n", + "========================================================================================================\n", + "Document ID: 404\n", + "Score: 1.0\n", + "Scores: [1, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 405\n", + "Score: 0.0\n", + "Scores: [3, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 406\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 407\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 408\n", + "Score: 1.0\n", + "Scores: [1, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 409\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 410\n", + "Score: 1.3333333333333333\n", + "Scores: [3, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 411\n", + "Score: 2.0\n", + "Scores: [2, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 412\n", + "Score: 1.6666666666666667\n", + "Scores: [0, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 413\n", + "Score: 3.0\n", + "Scores: [3, 2, 3]\n", + "========================================================================================================\n", + "Document ID: 414\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 415\n", + "Score: 2.0\n", + "Scores: [2, 2, 0]\n", + "========================================================================================================\n", + "Document ID: 416\n", + "Score: 3.0\n", + "Scores: [3, 3, 0]\n", + "========================================================================================================\n", + "Document ID: 417\n", + "Score: 1.0\n", + "Scores: [1, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 418\n", + "Score: 4.0\n", + "Scores: [4, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 419\n", + "Score: 1.6666666666666667\n", + "Scores: [0, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 420\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 421\n", + "Score: 0.0\n", + "Scores: [0, 0, 2]\n", + "========================================================================================================\n", + "Document ID: 422\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 423\n", + "Score: 2.0\n", + "Scores: [3, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 424\n", + "Score: 2.0\n", + "Scores: [2, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 425\n", + "Score: 2.0\n", + "Scores: [3, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 426\n", + "Score: 2.0\n", + "Scores: [1, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 427\n", + "Score: 1.0\n", + "Scores: [0, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 428\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 429\n", + "Score: 3.0\n", + "Scores: [3, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 430\n", + "Score: 3.0\n", + "Scores: [3, 5, 3]\n", + "========================================================================================================\n", + "Document ID: 431\n", + "Score: 1.0\n", + "Scores: [0, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 432\n", + "Score: 2.3333333333333335\n", + "Scores: [1, 2, 4]\n", + "========================================================================================================\n", + "Document ID: 433\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 434\n", + "Score: 0.0\n", + "Scores: [3, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 435\n", + "Score: 2.0\n", + "Scores: [3, 2, 2]\n", + "========================================================================================================\n", + "Document ID: 436\n", + "Score: 3.0\n", + "Scores: [3, 0, 3]\n", + "========================================================================================================\n", + "Document ID: 437\n", + "Score: 3.0\n", + "Scores: [4, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 438\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 439\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 440\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 441\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 442\n", + "Score: 1.0\n", + "Scores: [1, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 443\n", + "Score: 0.0\n", + "Scores: [3, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 444\n", + "Score: 2.3333333333333335\n", + "Scores: [3, 0, 4]\n", + "========================================================================================================\n", + "Document ID: 445\n", + "Score: 2.0\n", + "Scores: [2, 3, 1]\n", + "========================================================================================================\n", + "Document ID: 446\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 447\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 448\n", + "Score: 3.0\n", + "Scores: [3, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 449\n", + "Score: 0.0\n", + "Scores: [0, 3, 0]\n", + "========================================================================================================\n", + "Document ID: 450\n", + "Score: 2.0\n", + "Scores: [2, 1, 3]\n", + "========================================================================================================\n", + "Document ID: 451\n", + "Score: 1.0\n", + "Scores: [1, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 452\n", + "Score: 1.0\n", + "Scores: [1, 2, 0]\n", + "========================================================================================================\n", + "Document ID: 453\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 454\n", + "Score: 3.0\n", + "Scores: [3, 2, 3]\n", + "========================================================================================================\n", + "Document ID: 455\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 456\n", + "Score: 1.0\n", + "Scores: [1, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 457\n", + "Score: 2.6666666666666665\n", + "Scores: [4, 3, 1]\n", + "========================================================================================================\n", + "Document ID: 458\n", + "Score: 2.0\n", + "Scores: [2, 1, 3]\n", + "========================================================================================================\n", + "Document ID: 459\n", + "Score: 3.0\n", + "Scores: [3, 2, 4]\n", + "========================================================================================================\n", + "Document ID: 460\n", + "Score: 0.0\n", + "Scores: [3, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 461\n", + "Score: 3.0\n", + "Scores: [3, 3, 0]\n", + "========================================================================================================\n", + "Document ID: 462\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 463\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 464\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 465\n", + "Score: 3.0\n", + "Scores: [3, 4, 3]\n", + "========================================================================================================\n", + "Document ID: 466\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 467\n", + "Score: 3.0\n", + "Scores: [3, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 468\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 469\n", + "Score: 1.0\n", + "Scores: [1, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 470\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 471\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 472\n", + "Score: 1.0\n", + "Scores: [0, 2, 1]\n", + "========================================================================================================\n", + "Document ID: 473\n", + "Score: 1.0\n", + "Scores: [2, 0, 1]\n", + "========================================================================================================\n", + "Document ID: 474\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 475\n", + "Score: 2.0\n", + "Scores: [2, 2, 0]\n", + "========================================================================================================\n", + "Document ID: 476\n", + "Score: 4.0\n", + "Scores: [4, 2, 4]\n", + "========================================================================================================\n", + "Document ID: 477\n", + "Score: 1.0\n", + "Scores: [1, 1, 4]\n", + "========================================================================================================\n", + "Document ID: 478\n", + "Score: 2.3333333333333335\n", + "Scores: [1, 4, 2]\n", + "========================================================================================================\n", + "Document ID: 479\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 480\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 481\n", + "Score: 3.0\n", + "Scores: [3, 3, 1]\n", + "========================================================================================================\n", + "Document ID: 482\n", + "Score: 2.0\n", + "Scores: [2, 2, 3]\n", + "========================================================================================================\n", + "Document ID: 483\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 484\n", + "Score: 2.0\n", + "Scores: [2, 0, 2]\n", + "========================================================================================================\n", + "Document ID: 485\n", + "Score: 3.0\n", + "Scores: [2, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 486\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 487\n", + "Score: 1.0\n", + "Scores: [1, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 488\n", + "Score: 3.0\n", + "Scores: [4, 3, 2]\n", + "========================================================================================================\n", + "Document ID: 489\n", + "Score: 1.0\n", + "Scores: [2, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 490\n", + "Score: 3.0\n", + "Scores: [3, 4, 2]\n", + "========================================================================================================\n", + "Document ID: 491\n", + "Score: 1.0\n", + "Scores: [2, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 492\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 493\n", + "Score: 1.0\n", + "Scores: [2, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 494\n", + "Score: 1.0\n", + "Scores: [0, 1, 2]\n", + "========================================================================================================\n", + "Document ID: 495\n", + "Score: 0.0\n", + "Scores: [0, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 496\n", + "Score: 3.0\n", + "Scores: [1, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 497\n", + "Score: 1.0\n", + "Scores: [1, 1, 0]\n", + "========================================================================================================\n", + "Document ID: 498\n", + "Score: 2.0\n", + "Scores: [2, 2, 0]\n", + "========================================================================================================\n", + "Document ID: 499\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 500\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 501\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 502\n", + "Score: 2.3333333333333335\n", + "Scores: [4, 3, 0]\n", + "========================================================================================================\n", + "Document ID: 503\n", + "Score: 0.0\n", + "Scores: [0, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 504\n", + "Score: 1.0\n", + "Scores: [1, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 505\n", + "Score: 3.0\n", + "Scores: [1, 3, 3]\n", + "========================================================================================================\n", + "Document ID: 506\n", + "Score: 0.0\n", + "Scores: [1, 0, 0]\n", + "========================================================================================================\n", + "Document ID: 507\n", + "Score: 1.0\n", + "Scores: [1, 1, 1]\n", + "========================================================================================================\n", + "Document ID: 508\n", + "Score: 3.0\n", + "Scores: [3, 3, 1]\n", + "========================================================================================================\n", + "Document ID: 509\n", + "Score: 3.0\n", + "Scores: [2, 3, 4]\n", + "========================================================================================================\n", + "Document ID: 510\n", + "Score: 2.0\n", + "Scores: [2, 1, 2]\n", + "========================================================================================================\n", + "Number of documents with non-integer scores: 46\n" + ] + } + ], + "source": [ + "\n", + "\n", + "from ml_filter.analysis.utils import most_frequent_average\n", + "\n", + "non_int_counter = 0\n", + "for d1, d2, d3 in zip(en_511_list, de_511_list, en_non_agg_list):\n", + " assert d1[\"document_id\"] == d2[\"document_id\"]\n", + " assert d1[\"score\"] == d2[\"score\"]\n", + " d3_scores = [int(x) for x in d3[\"scores\"]]\n", + " assert most_frequent_average(d3_scores) == d1[\"score\"]\n", + " if not isinstance(d1[\"score\"], int):\n", + " non_int_counter += not d2[\"score\"].is_integer()\n", + " print(f\"Document ID: {d1['document_id']}\")\n", + " print(f\"Score: {d1['score']}\")\n", + " print(f\"Scores: {d3_scores}\")\n", + " print(\"========================================================================================================\")\n", + "print (f\"Number of documents with non-integer scores: {non_int_counter}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "00d16f23", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "c153a2c2", + "metadata": {}, + "source": [ + "## LLM annotations without integer scores\n", + "\n", + "these are jsut some consistency checks!" + ] + }, + { + "cell_type": "markdown", + "id": "d69dd482", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "6ebedb78", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_llm_as_a_judge/raw_annotations/Llama-3.1-8B-Instruct/bg/annotations__educational_content__bg__Llama-3.1-8B-Instruct.jsonl'),\n", + " PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_llm_as_a_judge/raw_annotations/Llama-3.1-8B-Instruct/nn/annotations__educational_content__nn__Llama-3.1-8B-Instruct.jsonl'),\n", + " 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PosixPath('/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_llm_as_a_judge/raw_annotations/gemma-2-9b-it/en/annotations__educational_content__en__gemma-2-9b-it.jsonl')]" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "score_path = Path(\"/raid/s3/opengptx/max_lue/repositories/ml_filter/ml_filter_paper/data/edu_content/predictions/511_test_documents_educational_content_llm_as_a_judge/raw_annotations\")\n", + "score_paths = list(score_path.glob(\"**/*.jsonl\"))\n", + "score_paths" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "1b122cb3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total samples: 226392\n", + "Total non-integer scores: 5059\n", + "Total invalid scores: 10436\n", + "Non-integer ratio: 0.022\n", + "Invalid ratio: 0.046\n" + ] + } + ], + "source": [ + "total_samples = 0\n", + "total_non_int = 0\n", + "total_invalid = 0 \n", + "for path in score_paths:\n", + " with open(path, 'r') as f:\n", + " for line in f:\n", + " json_line = json.loads(line)\n", + " scores = [score for score in json_line[\"scores\"] if score is not None and score.is_integer()]\n", + " if len(scores) == 0: \n", + " total_invalid += 1\n", + " total_samples += 1\n", + " continue\n", + " score = most_frequent_average(scores)\n", + " if not score.is_integer():\n", + " total_non_int += 1\n", + " total_samples += 1\n", + "print(f\"Total samples: {total_samples}\")\n", + "print(f\"Total non-integer scores: {total_non_int}\")\n", + "print(f\"Total invalid scores: {total_invalid}\")\n", + "print(f\"Non-integer ratio: {total_non_int / total_samples:.3f}\")\n", + "print(f\"Invalid ratio: {total_invalid / total_samples:.3f}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "530cf387", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 66f2dc9a841bf0ad45dfc4cd1a66af92c2ed8848 Mon Sep 17 00:00:00 2001 From: Max Luebbering <2804731+le1nux@users.noreply.github.com> Date: Sun, 18 May 2025 17:07:44 +0200 Subject: [PATCH 7/7] feat: model correlation claculation and confusion matrix refactoring --- src/ml_filter/__main__.py | 14 +++++- .../evaluate_predicted_annotations.py | 43 ++++++++++++++++++- .../analysis/interrater_reliability.py | 2 +- .../analysis/plot_score_distributions.py | 23 +++++++--- src/ml_filter/analysis/utils.py | 4 +- 5 files changed, 76 insertions(+), 10 deletions(-) diff --git a/src/ml_filter/__main__.py b/src/ml_filter/__main__.py index 7e8ca271..e2c44228 100644 --- a/src/ml_filter/__main__.py +++ b/src/ml_filter/__main__.py @@ -10,7 +10,10 @@ from ml_filter.analysis.aggregate_scores import aggregate_human_annotations, aggregate_scores from ml_filter.analysis.collect_ir_metrics import collect_ir_metrics -from ml_filter.analysis.evaluate_predicted_annotations import evaluate_predicted_annotations +from ml_filter.analysis.evaluate_predicted_annotations import ( + evaluate_predicted_annotations, + evaluate_prediction_correlation, +) from ml_filter.analysis.plot_score_distributions import plot_differences_in_scores, plot_scores from ml_filter.compare_experiments import compare_experiments from ml_filter.data_processing.deduplication import deduplicate_jsonl @@ -287,6 +290,15 @@ def evaluate_predicted_annotations_cli( ) +@main.command(name="evaluate_prediction_correlation") +@input_directory_option +def evaluate_prediction_correlation_cli( + input_directory: Path, +) -> None: + model_filters = ["gemma-3-27b-it", "Llama-3.3-70B-Instruct", "Mistral-Small-3.1-24B-Instruct-2503"] + evaluate_prediction_correlation(input_directory=input_directory, model_filters=model_filters) + + @main.command(name="aggregate_scores") @input_directory_option @output_directory_option diff --git a/src/ml_filter/analysis/evaluate_predicted_annotations.py b/src/ml_filter/analysis/evaluate_predicted_annotations.py index 5b5bb8de..fcaa04e9 100644 --- a/src/ml_filter/analysis/evaluate_predicted_annotations.py +++ b/src/ml_filter/analysis/evaluate_predicted_annotations.py @@ -1,7 +1,9 @@ +import itertools import logging from pathlib import Path -from ml_filter.analysis.interrater_reliability import compute_interrater_reliability_metrics +from ml_filter.analysis.interrater_reliability import compute_interrater_reliability_metrics, compute_metrics +from ml_filter.analysis.utils import get_common_docs, get_document_scores_df from ml_filter.utils.logging import get_logger logger = get_logger(name=__name__, level=logging.INFO) # Set up logging @@ -75,3 +77,42 @@ def evaluate_predicted_annotations( lang=lang, ) logger.info(f"Metrics successfully written to {lang_dir}") + + +def evaluate_prediction_correlation( + input_directory: Path, + model_filters: list[str], +) -> None: + # Find all files matching the pattern in the directory and subdirectories + files = list(input_directory.rglob("annotations_*.jsonl")) + + # Check if there is at least one file + if len(files) < 2: + raise ValueError(f"No annotation files found in {input_directory} or its subdirectories.") + + filtered_file_paths = [ + file_path for file_path in files if any(model_filter in str(file_path) for model_filter in model_filters) + ] + + scores_df = get_document_scores_df( + input_file_paths=filtered_file_paths, + aggregation_strategy="majority", + valid_labels=[0, 1, 2, 3, 4, 5], + ) + + # create all pairs + model_pairs = list(itertools.combinations(model_filters, 2)) + for model_pair in model_pairs: + model_1, model_2 = model_pair + common_docs_df = get_common_docs(scores_df, model_1, model_2) + valid_docs_df = common_docs_df[ + (common_docs_df["score_0"] != "invalid") & (common_docs_df["score_1"] != "invalid") + ] + valid_docs_df = valid_docs_df[valid_docs_df["prompt_lang"] != "en"] + + metrics = compute_metrics( + num_total_docs=len(common_docs_df), + valid_docs_df=valid_docs_df, + thresholds=[1], + ) + print(float(metrics["metrics"]["Spearman"])) diff --git a/src/ml_filter/analysis/interrater_reliability.py b/src/ml_filter/analysis/interrater_reliability.py index 725755fa..af112603 100644 --- a/src/ml_filter/analysis/interrater_reliability.py +++ b/src/ml_filter/analysis/interrater_reliability.py @@ -428,7 +428,7 @@ def compare_annotator_to_gt( plot_confusion_matrix( cm_dict=cm, annotator_name=annotator_name, - output_file_path=output_dir / f"confusion_matrix_{annotator_name}_gt.png", + output_file_path=output_dir / f"confusion_matrix_{annotator_name}_gt_{lang}.pdf", valid_labels=[int(valid_label) for valid_label in valid_labels], language=lang, ) diff --git a/src/ml_filter/analysis/plot_score_distributions.py b/src/ml_filter/analysis/plot_score_distributions.py index 277f54dc..12d270f2 100644 --- a/src/ml_filter/analysis/plot_score_distributions.py +++ b/src/ml_filter/analysis/plot_score_distributions.py @@ -177,14 +177,25 @@ def plot_confusion_matrix( cm_array = np.array(cm_array) # Plot the confusion matrix - plt.figure(figsize=(10, 6)) + plt.figure(figsize=(6.66, 4)) # Normalize the confusion matrix cm_normalized = cm_array.astype("float") / cm_array.sum(axis=1)[:, np.newaxis] xlabels = [label if label != -1 else "invalid" for label in all_labels] - sns.heatmap(cm_normalized, annot=True, fmt=".2f", cmap="Blues", xticklabels=xlabels, yticklabels=valid_labels) - plt.xlabel("Predicted") - plt.ylabel("True") - plt.title(f"Confusion Matrix for {annotator_name} and language {language}.") - plt.savefig(output_file_path) + sns.heatmap( + cm_normalized, + annot=True, + fmt=".2f", + cmap="Blues", + xticklabels=xlabels, + yticklabels=valid_labels, + annot_kws={"size": 14}, + ) + plt.xlabel("Predicted", fontsize=16) + plt.ylabel("True", fontsize=16) + plt.xticks(fontsize=14) + plt.yticks(fontsize=14) + # plt.title(f"Confusion Matrix for {annotator_name} and language {language}.") + plt.tight_layout() + plt.savefig(output_file_path, format="pdf", bbox_inches="tight") plt.show() diff --git a/src/ml_filter/analysis/utils.py b/src/ml_filter/analysis/utils.py index 06504586..e9022b8e 100644 --- a/src/ml_filter/analysis/utils.py +++ b/src/ml_filter/analysis/utils.py @@ -190,7 +190,9 @@ def get_common_docs(document_scores_df: pd.DataFrame, annotator_0: str, annotato f"while annotator {annotator_1} has {len(annotator_1_df)} documents." ) # only consider documents that are annotated by both annotators and have valid scores - common_docs_df = pd.merge(annotator_0_df, annotator_1_df, on=["doc_id", "prompt"], suffixes=("_0", "_1")) + common_docs_df = pd.merge( + annotator_0_df, annotator_1_df, on=["doc_id", "prompt_lang", "prompt"], suffixes=("_0", "_1") + ) if len(common_docs_df) * 2 != len(document_scores_df): get_logger(name="main").warning("Not all documents can be matched on columns doc_id and prompt.")