---
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_reverse
  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_reverse

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: 4.4478

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7436        | 0.0211 | 13   | 7.4054          |
| 9.1068        | 0.0421 | 26   | 6.9800          |
| 6.6988        | 0.0632 | 39   | 6.4271          |
| 6.4684        | 0.0842 | 52   | 6.2893          |
| 6.1245        | 0.1053 | 65   | 6.1245          |
| 5.9117        | 0.1264 | 78   | 5.8770          |
| 5.8448        | 0.1474 | 91   | 5.7834          |
| 5.742         | 0.1685 | 104  | 5.8941          |
| 5.6054        | 0.1896 | 117  | 6.0972          |
| 5.6465        | 0.2106 | 130  | 5.4808          |
| 5.5659        | 0.2317 | 143  | 5.5371          |
| 5.4175        | 0.2527 | 156  | 5.5688          |
| 5.3148        | 0.2738 | 169  | 5.3646          |
| 5.2376        | 0.2949 | 182  | 5.2052          |
| 5.2313        | 0.3159 | 195  | 5.1473          |
| 5.1381        | 0.3370 | 208  | 5.2471          |
| 5.0545        | 0.3580 | 221  | 5.0579          |
| 5.0218        | 0.3791 | 234  | 5.0434          |
| 5.1901        | 0.4002 | 247  | 5.1862          |
| 5.0809        | 0.4212 | 260  | 5.0103          |
| 5.0357        | 0.4423 | 273  | 5.0488          |
| 5.0375        | 0.4633 | 286  | 5.0026          |
| 5.0348        | 0.4844 | 299  | 5.0081          |
| 4.8927        | 0.5055 | 312  | 4.8912          |
| 4.878         | 0.5265 | 325  | 4.8665          |
| 4.8092        | 0.5476 | 338  | 4.8402          |
| 4.8342        | 0.5687 | 351  | 4.7689          |
| 4.7834        | 0.5897 | 364  | 4.7842          |
| 4.7428        | 0.6108 | 377  | 4.7396          |
| 4.7318        | 0.6318 | 390  | 4.6987          |
| 4.6442        | 0.6529 | 403  | 4.6854          |
| 4.6454        | 0.6740 | 416  | 4.6917          |
| 4.7075        | 0.6950 | 429  | 4.6419          |
| 4.6744        | 0.7161 | 442  | 4.5826          |
| 4.5861        | 0.7371 | 455  | 4.5793          |
| 4.5707        | 0.7582 | 468  | 4.5944          |
| 4.5675        | 0.7793 | 481  | 4.5611          |
| 4.5286        | 0.8003 | 494  | 4.5216          |
| 4.5302        | 0.8214 | 507  | 4.5140          |
| 4.5191        | 0.8424 | 520  | 4.5084          |
| 4.5023        | 0.8635 | 533  | 4.4878          |
| 4.4661        | 0.8846 | 546  | 4.4593          |
| 4.4942        | 0.9056 | 559  | 4.4660          |
| 4.4691        | 0.9267 | 572  | 4.4433          |
| 4.4153        | 0.9478 | 585  | 4.4531          |
| 4.4609        | 0.9688 | 598  | 4.4450          |
| 4.4444        | 0.9899 | 611  | 4.4478          |


### Framework versions

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