---
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_ortho
  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_ortho

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: 3.8319

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7761        | 0.0211 | 13   | 0.8475          |
| 5.7285        | 0.0421 | 26   | 7.1242          |
| 6.6463        | 0.0632 | 39   | 6.4624          |
| 6.3183        | 0.0842 | 52   | 6.2700          |
| 6.3056        | 0.1053 | 65   | 6.3511          |
| 6.2849        | 0.1264 | 78   | 6.2801          |
| 6.2952        | 0.1474 | 91   | 6.3205          |
| 6.2939        | 0.1685 | 104  | 6.3566          |
| 6.2779        | 0.1896 | 117  | 6.2580          |
| 6.087         | 0.2106 | 130  | 5.9797          |
| 5.8495        | 0.2317 | 143  | 5.8683          |
| 5.6782        | 0.2527 | 156  | 5.5177          |
| 5.4335        | 0.2738 | 169  | 5.3885          |
| 5.4451        | 0.2949 | 182  | 5.7948          |
| 5.5833        | 0.3159 | 195  | 5.2887          |
| 5.2684        | 0.3370 | 208  | 5.3036          |
| 5.1159        | 0.3580 | 221  | 5.1110          |
| 5.0046        | 0.3791 | 234  | 4.9806          |
| 4.9134        | 0.4002 | 247  | 4.9382          |
| 4.9145        | 0.4212 | 260  | 4.9544          |
| 4.7976        | 0.4423 | 273  | 4.7954          |
| 4.7328        | 0.4633 | 286  | 4.6897          |
| 4.6799        | 0.4844 | 299  | 4.5793          |
| 4.5047        | 0.5055 | 312  | 4.6603          |
| 4.529         | 0.5265 | 325  | 4.4405          |
| 4.3835        | 0.5476 | 338  | 4.3916          |
| 4.4279        | 0.5687 | 351  | 4.2860          |
| 4.3177        | 0.5897 | 364  | 4.3171          |
| 4.39          | 0.6108 | 377  | 4.3272          |
| 4.3138        | 0.6318 | 390  | 4.3753          |
| 4.2269        | 0.6529 | 403  | 4.3339          |
| 4.1075        | 0.6740 | 416  | 4.1693          |
| 4.2285        | 0.6950 | 429  | 4.1187          |
| 4.1297        | 0.7161 | 442  | 4.1251          |
| 4.0021        | 0.7371 | 455  | 4.0365          |
| 4.0089        | 0.7582 | 468  | 4.0025          |
| 3.9458        | 0.7793 | 481  | 3.9924          |
| 3.9405        | 0.8003 | 494  | 3.9254          |
| 3.9594        | 0.8214 | 507  | 3.8890          |
| 3.9056        | 0.8424 | 520  | 3.8774          |
| 3.8639        | 0.8635 | 533  | 3.8758          |
| 3.8543        | 0.8846 | 546  | 3.8680          |
| 3.9097        | 0.9056 | 559  | 3.8502          |
| 3.8503        | 0.9267 | 572  | 3.8287          |
| 3.789         | 0.9478 | 585  | 3.8357          |
| 3.7923        | 0.9688 | 598  | 3.8299          |
| 3.8071        | 0.9899 | 611  | 3.8319          |


### Framework versions

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