---
base_model: unsloth/mistral-7b-v0.3
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_metamath_default
  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-v0.3_metamath_default

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3](https://huggingface.co/unsloth/mistral-7b-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3239

## 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: 0.0003
- 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_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7439        | 0.0211 | 13   | 4.5181          |
| 8.6977        | 0.0421 | 26   | 6.6816          |
| 6.6139        | 0.0632 | 39   | 6.4690          |
| 6.3559        | 0.0842 | 52   | 6.4403          |
| 6.2844        | 0.1053 | 65   | 6.3007          |
| 6.1379        | 0.1264 | 78   | 6.0592          |
| 5.9506        | 0.1474 | 91   | 5.9143          |
| 5.8886        | 0.1685 | 104  | 5.9890          |
| 5.7387        | 0.1896 | 117  | 5.6559          |
| 5.672         | 0.2106 | 130  | 5.7240          |
| 5.5425        | 0.2317 | 143  | 5.5165          |
| 5.473         | 0.2527 | 156  | 5.4238          |
| 5.328         | 0.2738 | 169  | 5.3434          |
| 5.241         | 0.2949 | 182  | 5.2088          |
| 5.2491        | 0.3159 | 195  | 5.3291          |
| 5.2994        | 0.3370 | 208  | 5.1687          |
| 5.1595        | 0.3580 | 221  | 5.0797          |
| 5.0592        | 0.3791 | 234  | 5.0005          |
| 4.9674        | 0.4002 | 247  | 4.9525          |
| 4.9663        | 0.4212 | 260  | 4.9704          |
| 5.0169        | 0.4423 | 273  | 4.9718          |
| 4.9333        | 0.4633 | 286  | 4.8277          |
| 4.8687        | 0.4844 | 299  | 4.8131          |
| 4.7215        | 0.5055 | 312  | 4.7606          |
| 4.7602        | 0.5265 | 325  | 4.7049          |
| 4.7033        | 0.5476 | 338  | 4.7817          |
| 4.7179        | 0.5687 | 351  | 4.6428          |
| 4.6525        | 0.5897 | 364  | 4.5964          |
| 4.5923        | 0.6108 | 377  | 4.5608          |
| 4.5936        | 0.6318 | 390  | 4.5676          |
| 4.5142        | 0.6529 | 403  | 4.5016          |
| 4.4717        | 0.6740 | 416  | 4.4422          |
| 4.5539        | 0.6950 | 429  | 4.5177          |
| 4.5129        | 0.7161 | 442  | 4.5397          |
| 4.4162        | 0.7371 | 455  | 4.4050          |
| 4.4328        | 0.7582 | 468  | 4.4244          |
| 4.3949        | 0.7793 | 481  | 4.4013          |
| 4.3946        | 0.8003 | 494  | 4.3721          |
| 4.393         | 0.8214 | 507  | 4.3586          |
| 4.3872        | 0.8424 | 520  | 4.3552          |
| 4.3787        | 0.8635 | 533  | 4.4043          |
| 4.3477        | 0.8846 | 546  | 4.3537          |
| 4.3957        | 0.9056 | 559  | 4.3334          |
| 4.3634        | 0.9267 | 572  | 4.3088          |
| 4.2898        | 0.9478 | 585  | 4.3342          |
| 4.355         | 0.9688 | 598  | 4.3202          |
| 4.3331        | 0.9899 | 611  | 4.3239          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1