---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_MetaMathQA_40K
  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. -->

# qwen2_MetaMathQA_40K

This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co./Qwen/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1551

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.1756        | 0.0211 | 13   | 0.1624          |
| 0.1538        | 0.0421 | 26   | 0.1650          |
| 0.1596        | 0.0632 | 39   | 0.1662          |
| 0.1579        | 0.0842 | 52   | 0.1680          |
| 0.1577        | 0.1053 | 65   | 0.1701          |
| 0.1644        | 0.1264 | 78   | 0.1703          |
| 0.1691        | 0.1474 | 91   | 0.1722          |
| 0.1648        | 0.1685 | 104  | 0.1739          |
| 0.1707        | 0.1896 | 117  | 0.1749          |
| 0.1679        | 0.2106 | 130  | 0.1755          |
| 0.1715        | 0.2317 | 143  | 0.1761          |
| 0.1632        | 0.2527 | 156  | 0.1757          |
| 0.1706        | 0.2738 | 169  | 0.1760          |
| 0.1664        | 0.2949 | 182  | 0.1755          |
| 0.1713        | 0.3159 | 195  | 0.1743          |
| 0.1633        | 0.3370 | 208  | 0.1736          |
| 0.1652        | 0.3580 | 221  | 0.1737          |
| 0.1627        | 0.3791 | 234  | 0.1724          |
| 0.1646        | 0.4002 | 247  | 0.1723          |
| 0.1655        | 0.4212 | 260  | 0.1698          |
| 0.1727        | 0.4423 | 273  | 0.1692          |
| 0.1649        | 0.4633 | 286  | 0.1687          |
| 0.1715        | 0.4844 | 299  | 0.1687          |
| 0.1596        | 0.5055 | 312  | 0.1672          |
| 0.156         | 0.5265 | 325  | 0.1661          |
| 0.1577        | 0.5476 | 338  | 0.1655          |
| 0.1589        | 0.5687 | 351  | 0.1646          |
| 0.1621        | 0.5897 | 364  | 0.1635          |
| 0.1589        | 0.6108 | 377  | 0.1627          |
| 0.1514        | 0.6318 | 390  | 0.1616          |
| 0.1584        | 0.6529 | 403  | 0.1610          |
| 0.1592        | 0.6740 | 416  | 0.1599          |
| 0.1568        | 0.6950 | 429  | 0.1597          |
| 0.1584        | 0.7161 | 442  | 0.1587          |
| 0.1503        | 0.7371 | 455  | 0.1575          |
| 0.153         | 0.7582 | 468  | 0.1575          |
| 0.1549        | 0.7793 | 481  | 0.1569          |
| 0.1514        | 0.8003 | 494  | 0.1568          |
| 0.1485        | 0.8214 | 507  | 0.1564          |
| 0.1507        | 0.8424 | 520  | 0.1557          |
| 0.1536        | 0.8635 | 533  | 0.1557          |
| 0.1526        | 0.8846 | 546  | 0.1556          |
| 0.149         | 0.9056 | 559  | 0.1555          |
| 0.1461        | 0.9267 | 572  | 0.1552          |
| 0.1471        | 0.9478 | 585  | 0.1552          |
| 0.1484        | 0.9688 | 598  | 0.1552          |
| 0.1542        | 0.9899 | 611  | 0.1551          |


### Framework versions

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