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---
base_model: unsloth/qwen2-7b-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_metamath_default
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. -->
# Qwen2-7B_metamath_default
This model is a fine-tuned version of [unsloth/qwen2-7b-bnb-4bit](https://huggingface.co/unsloth/qwen2-7b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1552
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.2406 | 0.0211 | 13 | 0.1655 |
| 0.1558 | 0.0421 | 26 | 0.1578 |
| 0.1536 | 0.0632 | 39 | 0.1560 |
| 0.1467 | 0.0842 | 52 | 0.1547 |
| 0.1457 | 0.1053 | 65 | 0.1551 |
| 0.15 | 0.1264 | 78 | 0.1552 |
| 0.1547 | 0.1474 | 91 | 0.1548 |
| 0.1494 | 0.1685 | 104 | 0.1559 |
| 0.1543 | 0.1896 | 117 | 0.1563 |
| 0.1511 | 0.2106 | 130 | 0.1563 |
| 0.1545 | 0.2317 | 143 | 0.1567 |
| 0.148 | 0.2527 | 156 | 0.1576 |
| 0.1559 | 0.2738 | 169 | 0.1584 |
| 0.1497 | 0.2949 | 182 | 0.1579 |
| 0.1577 | 0.3159 | 195 | 0.1582 |
| 0.1505 | 0.3370 | 208 | 0.1585 |
| 0.152 | 0.3580 | 221 | 0.1583 |
| 0.1498 | 0.3791 | 234 | 0.1586 |
| 0.1522 | 0.4002 | 247 | 0.1581 |
| 0.1536 | 0.4212 | 260 | 0.1574 |
| 0.1614 | 0.4423 | 273 | 0.1583 |
| 0.1555 | 0.4633 | 286 | 0.1580 |
| 0.1605 | 0.4844 | 299 | 0.1573 |
| 0.1497 | 0.5055 | 312 | 0.1580 |
| 0.1477 | 0.5265 | 325 | 0.1579 |
| 0.1497 | 0.5476 | 338 | 0.1570 |
| 0.1539 | 0.5687 | 351 | 0.1573 |
| 0.1573 | 0.5897 | 364 | 0.1576 |
| 0.1535 | 0.6108 | 377 | 0.1570 |
| 0.146 | 0.6318 | 390 | 0.1562 |
| 0.1546 | 0.6529 | 403 | 0.1564 |
| 0.1554 | 0.6740 | 416 | 0.1564 |
| 0.1521 | 0.6950 | 429 | 0.1565 |
| 0.1557 | 0.7161 | 442 | 0.1557 |
| 0.1469 | 0.7371 | 455 | 0.1554 |
| 0.1513 | 0.7582 | 468 | 0.1558 |
| 0.153 | 0.7793 | 481 | 0.1557 |
| 0.1518 | 0.8003 | 494 | 0.1555 |
| 0.1482 | 0.8214 | 507 | 0.1554 |
| 0.1514 | 0.8424 | 520 | 0.1554 |
| 0.1533 | 0.8635 | 533 | 0.1553 |
| 0.1521 | 0.8846 | 546 | 0.1554 |
| 0.148 | 0.9056 | 559 | 0.1553 |
| 0.1473 | 0.9267 | 572 | 0.1553 |
| 0.1482 | 0.9478 | 585 | 0.1552 |
| 0.1498 | 0.9688 | 598 | 0.1553 |
| 0.155 | 0.9899 | 611 | 0.1552 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |