---
base_model: mistralai/Mistral-7B-Instruct-v0.3
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: mistral-7b-peptide
  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. -->

# mistral-7b-peptide

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5836

## 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: 5e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7541        | 0.025 | 100  | 2.6109          |
| 2.2057        | 0.05  | 200  | 2.1101          |
| 1.9566        | 0.075 | 300  | 1.8904          |
| 1.8737        | 0.1   | 400  | 3.6582          |
| 1.8384        | 0.125 | 500  | 1.6622          |
| 1.6577        | 0.15  | 600  | 1.6209          |
| 5.0415        | 0.175 | 700  | 5.0107          |
| 4.8597        | 0.2   | 800  | 4.8365          |
| 4.7887        | 0.225 | 900  | 4.7727          |
| 4.7478        | 0.25  | 1000 | 4.7247          |
| 4.8828        | 0.275 | 1100 | 4.8448          |
| 4.5764        | 0.3   | 1200 | 4.4572          |
| 4.2131        | 0.325 | 1300 | 4.1309          |
| 3.8945        | 0.35  | 1400 | 3.7905          |
| 3.42          | 0.375 | 1500 | 3.2011          |
| 1.6361        | 0.4   | 1600 | 1.5822          |
| 1.4804        | 0.425 | 1700 | 1.5127          |
| 1.3574        | 0.45  | 1800 | 1.5037          |
| 1.2675        | 0.475 | 1900 | 1.4394          |
| 1.2611        | 0.5   | 2000 | 1.3705          |
| 1.1509        | 0.525 | 2100 | 1.3520          |
| 1.0144        | 0.55  | 2200 | 1.3529          |
| 1.3122        | 0.575 | 2300 | 1.2730          |
| 1.0257        | 0.6   | 2400 | 1.2805          |
| 0.7651        | 0.625 | 2500 | 1.3131          |
| 0.5841        | 0.65  | 2600 | 1.3736          |
| 0.4848        | 0.675 | 2700 | 1.4138          |
| 0.6076        | 0.7   | 2800 | 1.3322          |
| 0.4255        | 0.725 | 2900 | 1.4169          |
| 0.3276        | 0.75  | 3000 | 1.4631          |
| 0.6833        | 0.775 | 3100 | 1.2651          |
| 0.385         | 0.8   | 3200 | 1.3994          |
| 0.1845        | 0.825 | 3300 | 1.4685          |
| 0.1408        | 0.85  | 3400 | 1.5640          |
| 0.1213        | 0.875 | 3500 | 1.5984          |
| 0.1735        | 0.9   | 3600 | 1.5952          |
| 0.1161        | 0.925 | 3700 | 1.6201          |
| 0.1079        | 0.95  | 3800 | 1.6238          |
| 0.3046        | 0.975 | 3900 | 1.6070          |
| 0.1477        | 1.0   | 4000 | 1.5836          |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1