---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: BioMistral/BioMistral-7B
model-index:
- name: QA_Finetune_BioMistral
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# QA_Finetune_BioMistral

This model is a fine-tuned version of [BioMistral/BioMistral-7B](https://huggingface.co/BioMistral/BioMistral-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8514

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00025
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9391        | 0.0619 | 200  | 0.9290          |
| 0.9056        | 0.1238 | 400  | 0.9171          |
| 0.8717        | 0.1858 | 600  | 0.9138          |
| 0.822         | 0.2477 | 800  | 0.9174          |
| 0.8539        | 0.3096 | 1000 | 0.9075          |
| 0.8902        | 0.3715 | 1200 | 0.9061          |
| 0.936         | 0.4334 | 1400 | 0.9088          |
| 0.8572        | 0.4954 | 1600 | 0.8990          |
| 0.8669        | 0.5573 | 1800 | 0.8933          |
| 0.875         | 0.6192 | 2000 | 0.8868          |
| 0.8369        | 0.6811 | 2200 | 0.8801          |
| 0.8445        | 0.7430 | 2400 | 0.8772          |
| 0.8316        | 0.8050 | 2600 | 0.8692          |
| 0.8573        | 0.8669 | 2800 | 0.8614          |
| 0.8104        | 0.9288 | 3000 | 0.8542          |
| 0.8182        | 0.9907 | 3200 | 0.8488          |
| 0.5912        | 1.0526 | 3400 | 0.8659          |
| 0.5579        | 1.1146 | 3600 | 0.8557          |
| 0.5834        | 1.1765 | 3800 | 0.8608          |
| 0.547         | 1.2384 | 4000 | 0.8514          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1