BioMistral_DS_fine_tuned

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BioMistral_DS_fine_tuned

This model is a fine-tuned version of BioMistral/BioMistral-7B on the daphne604/Mic_mortality_reason dataset. It achieves the following results on the evaluation set:

• Loss: 0.5240

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 4
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• num_epochs: 6

Training results

Framework versions

• PEFT 0.13.2
• Transformers 4.46.3
• Pytorch 2.5.0
• Datasets 3.0.1
• Tokenizers 0.20.1

Cite TRL as:

@misc{BioMistral_fine_tuned,
	title = {daphne604/{B}io{M}istral\_{D}{S}\_fine\_tuned · {H}ugging {F}ace --- huggingface.co},
	author       = {Daphne},
	year = {2024},
    publisher = {Hugging Face},
    journal = {Hugging Face repository},
    howpublished =  {\url{https://huggingface.co/daphne604/BioMistral_DS_fine_tuned}}
}

@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}