---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.3
model-index:
- name: mistral_7b_v_MetaMathQA_40K
  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_v_MetaMathQA_40K

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0534

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8546        | 0.0211 | 13   | 9.0448          |
| 8.7033        | 0.0421 | 26   | 6.8246          |
| 7.1208        | 0.0632 | 39   | 6.6756          |
| 6.5364        | 0.0842 | 52   | 6.5704          |
| 6.4506        | 0.1053 | 65   | 6.4165          |
| 6.3651        | 0.1264 | 78   | 6.4591          |
| 6.4236        | 0.1474 | 91   | 6.3382          |
| 6.3751        | 0.1685 | 104  | 6.3491          |
| 6.29          | 0.1896 | 117  | 6.3231          |
| 6.1703        | 0.2106 | 130  | 6.1876          |
| 5.9486        | 0.2317 | 143  | 5.8240          |
| 5.7357        | 0.2527 | 156  | 5.6677          |
| 5.5395        | 0.2738 | 169  | 5.7816          |
| 5.4509        | 0.2949 | 182  | 5.4254          |
| 5.4296        | 0.3159 | 195  | 5.2703          |
| 5.3284        | 0.3370 | 208  | 5.1638          |
| 5.2125        | 0.3580 | 221  | 5.1691          |
| 5.0807        | 0.3791 | 234  | 5.0448          |
| 4.9527        | 0.4002 | 247  | 4.9290          |
| 4.929         | 0.4212 | 260  | 4.9626          |
| 4.9299        | 0.4423 | 273  | 4.8930          |
| 4.8363        | 0.4633 | 286  | 4.6863          |
| 4.6998        | 0.4844 | 299  | 4.6888          |
| 4.6004        | 0.5055 | 312  | 4.6411          |
| 4.6229        | 0.5265 | 325  | 4.5178          |
| 4.4437        | 0.5476 | 338  | 4.4411          |
| 4.4564        | 0.5687 | 351  | 4.4293          |
| 4.4144        | 0.5897 | 364  | 4.3946          |
| 4.3888        | 0.6108 | 377  | 4.3527          |
| 4.3296        | 0.6318 | 390  | 4.2652          |
| 4.2489        | 0.6529 | 403  | 4.2610          |
| 4.2046        | 0.6740 | 416  | 4.2029          |
| 4.2525        | 0.6950 | 429  | 4.1885          |
| 4.2439        | 0.7161 | 442  | 4.1833          |
| 4.141         | 0.7371 | 455  | 4.1576          |
| 4.1417        | 0.7582 | 468  | 4.1388          |
| 4.1334        | 0.7793 | 481  | 4.1094          |
| 4.1319        | 0.8003 | 494  | 4.0910          |
| 4.1122        | 0.8214 | 507  | 4.1114          |
| 4.0976        | 0.8424 | 520  | 4.0905          |
| 4.0836        | 0.8635 | 533  | 4.0963          |
| 4.061         | 0.8846 | 546  | 4.0767          |
| 4.1107        | 0.9056 | 559  | 4.0573          |
| 4.0673        | 0.9267 | 572  | 4.0522          |
| 4.0283        | 0.9478 | 585  | 4.0558          |
| 4.045         | 0.9688 | 598  | 4.0532          |
| 4.0369        | 0.9899 | 611  | 4.0534          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1