---
license: llama2
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: llama_2_7b_MetaMathQA_40K_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. -->

# llama_2_7b_MetaMathQA_40K_reverse

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5038

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8359        | 0.0211 | 13   | 0.6875          |
| 0.6478        | 0.0421 | 26   | 0.6519          |
| 0.6205        | 0.0632 | 39   | 0.6314          |
| 0.5969        | 0.0842 | 52   | 0.6175          |
| 0.5854        | 0.1053 | 65   | 0.6087          |
| 0.5693        | 0.1264 | 78   | 0.6002          |
| 0.577         | 0.1474 | 91   | 0.5936          |
| 0.5566        | 0.1685 | 104  | 0.5874          |
| 0.5817        | 0.1896 | 117  | 0.5830          |
| 0.5671        | 0.2106 | 130  | 0.5772          |
| 0.5488        | 0.2317 | 143  | 0.5731          |
| 0.5326        | 0.2527 | 156  | 0.5700          |
| 0.535         | 0.2738 | 169  | 0.5648          |
| 0.5342        | 0.2949 | 182  | 0.5593          |
| 0.5227        | 0.3159 | 195  | 0.5570          |
| 0.5319        | 0.3370 | 208  | 0.5515          |
| 0.5344        | 0.3580 | 221  | 0.5486          |
| 0.5282        | 0.3791 | 234  | 0.5451          |
| 0.5144        | 0.4002 | 247  | 0.5423          |
| 0.5182        | 0.4212 | 260  | 0.5402          |
| 0.5306        | 0.4423 | 273  | 0.5361          |
| 0.5152        | 0.4633 | 286  | 0.5349          |
| 0.5216        | 0.4844 | 299  | 0.5330          |
| 0.5222        | 0.5055 | 312  | 0.5290          |
| 0.5043        | 0.5265 | 325  | 0.5285          |
| 0.512         | 0.5476 | 338  | 0.5257          |
| 0.4953        | 0.5687 | 351  | 0.5240          |
| 0.5067        | 0.5897 | 364  | 0.5219          |
| 0.4957        | 0.6108 | 377  | 0.5210          |
| 0.5002        | 0.6318 | 390  | 0.5182          |
| 0.5028        | 0.6529 | 403  | 0.5170          |
| 0.5049        | 0.6740 | 416  | 0.5151          |
| 0.4981        | 0.6950 | 429  | 0.5129          |
| 0.4984        | 0.7161 | 442  | 0.5118          |
| 0.4901        | 0.7371 | 455  | 0.5100          |
| 0.4825        | 0.7582 | 468  | 0.5087          |
| 0.4981        | 0.7793 | 481  | 0.5082          |
| 0.4846        | 0.8003 | 494  | 0.5069          |
| 0.4774        | 0.8214 | 507  | 0.5059          |
| 0.4992        | 0.8424 | 520  | 0.5055          |
| 0.4948        | 0.8635 | 533  | 0.5050          |
| 0.4875        | 0.8846 | 546  | 0.5044          |
| 0.4889        | 0.9056 | 559  | 0.5040          |
| 0.4838        | 0.9267 | 572  | 0.5039          |
| 0.4891        | 0.9478 | 585  | 0.5039          |
| 0.485         | 0.9688 | 598  | 0.5039          |
| 0.4891        | 0.9899 | 611  | 0.5038          |


### Framework versions

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