Question about dataset and fine-tuning details

[ckemmler]

Hi! And thanks for sharing these models and the ebook-summary project — I find it very useful.

I have a question about the training of the obook_summary and obook_title models. From the documentation I understand they are LoRA fine-tunes of Mistral-7B-Instruct v0.2, using TRL and Unsloth. Could you share a bit more detail about:
• The approximate dataset size and composition (e.g. number of texts / chapters, whether based on public domain ebooks, technical texts, etc.)
• Any evaluation process or benchmarks you used to check summarization quality (ROUGE, human eval, etc.)
• Whether human feedback / curation was part of the training (e.g. cleaning the data, adjusting style)
• If possible, the hyperparameters you found important (epochs, learning rate, context length, etc.)

I realize not all details may be public, but even a high-level overview would be very helpful for understanding the strengths and limitations of the models.

Thanks again for the great work!