---
base_model: unsloth/llama-3-8b
library_name: peft
license: llama3
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B_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. -->

# Meta-Llama-3-8B_metamath_reverse

This model is a fine-tuned version of [unsloth/llama-3-8b](https://huggingface.co/unsloth/llama-3-8b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5067

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8667        | 0.0211 | 13   | 0.7332          |
| 0.7009        | 0.0421 | 26   | 0.7322          |
| 0.7161        | 0.0632 | 39   | 0.7229          |
| 0.6909        | 0.0842 | 52   | 0.7190          |
| 0.6541        | 0.1053 | 65   | 0.7083          |
| 0.6704        | 0.1264 | 78   | 0.7014          |
| 0.6806        | 0.1474 | 91   | 0.6999          |
| 0.6735        | 0.1685 | 104  | 0.6932          |
| 0.6509        | 0.1896 | 117  | 0.6962          |
| 0.6537        | 0.2106 | 130  | 0.6907          |
| 0.6508        | 0.2317 | 143  | 0.6892          |
| 0.6594        | 0.2527 | 156  | 0.6816          |
| 0.6534        | 0.2738 | 169  | 0.6734          |
| 0.6559        | 0.2949 | 182  | 0.6744          |
| 0.6391        | 0.3159 | 195  | 0.6739          |
| 0.6115        | 0.3370 | 208  | 0.6628          |
| 0.6261        | 0.3580 | 221  | 0.6548          |
| 0.6288        | 0.3791 | 234  | 0.6545          |
| 0.6377        | 0.4002 | 247  | 0.6510          |
| 0.6106        | 0.4212 | 260  | 0.6465          |
| 0.6203        | 0.4423 | 273  | 0.6377          |
| 0.6196        | 0.4633 | 286  | 0.6276          |
| 0.6146        | 0.4844 | 299  | 0.6216          |
| 0.5931        | 0.5055 | 312  | 0.6187          |
| 0.5926        | 0.5265 | 325  | 0.6058          |
| 0.5807        | 0.5476 | 338  | 0.6018          |
| 0.5738        | 0.5687 | 351  | 0.5915          |
| 0.5509        | 0.5897 | 364  | 0.5852          |
| 0.5641        | 0.6108 | 377  | 0.5815          |
| 0.5606        | 0.6318 | 390  | 0.5723          |
| 0.5478        | 0.6529 | 403  | 0.5653          |
| 0.5451        | 0.6740 | 416  | 0.5613          |
| 0.5362        | 0.6950 | 429  | 0.5556          |
| 0.5328        | 0.7161 | 442  | 0.5474          |
| 0.5185        | 0.7371 | 455  | 0.5413          |
| 0.5127        | 0.7582 | 468  | 0.5359          |
| 0.5036        | 0.7793 | 481  | 0.5299          |
| 0.4922        | 0.8003 | 494  | 0.5265          |
| 0.5246        | 0.8214 | 507  | 0.5219          |
| 0.5088        | 0.8424 | 520  | 0.5175          |
| 0.4908        | 0.8635 | 533  | 0.5150          |
| 0.5091        | 0.8846 | 546  | 0.5120          |
| 0.4902        | 0.9056 | 559  | 0.5096          |
| 0.4865        | 0.9267 | 572  | 0.5083          |
| 0.5007        | 0.9478 | 585  | 0.5072          |
| 0.5001        | 0.9688 | 598  | 0.5068          |
| 0.4989        | 0.9899 | 611  | 0.5067          |


### Framework versions

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