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---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: Qwen/Qwen2-7B
model-index:
- name: qwen2_MetaMathQA_40K_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. -->
# qwen2_MetaMathQA_40K_ortho
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: 0.1523
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.1742 | 0.0211 | 13 | 0.1537 |
| 0.1454 | 0.0421 | 26 | 0.1536 |
| 0.1508 | 0.0632 | 39 | 0.1538 |
| 0.1453 | 0.0843 | 52 | 0.1541 |
| 0.1475 | 0.1053 | 65 | 0.1551 |
| 0.1506 | 0.1264 | 78 | 0.1554 |
| 0.1562 | 0.1474 | 91 | 0.1569 |
| 0.1516 | 0.1685 | 104 | 0.1574 |
| 0.1558 | 0.1896 | 117 | 0.1583 |
| 0.1565 | 0.2106 | 130 | 0.1594 |
| 0.1577 | 0.2317 | 143 | 0.1601 |
| 0.1498 | 0.2528 | 156 | 0.1598 |
| 0.1578 | 0.2738 | 169 | 0.1602 |
| 0.1532 | 0.2949 | 182 | 0.1604 |
| 0.1593 | 0.3159 | 195 | 0.1605 |
| 0.151 | 0.3370 | 208 | 0.1598 |
| 0.1532 | 0.3581 | 221 | 0.1596 |
| 0.1519 | 0.3791 | 234 | 0.1593 |
| 0.1531 | 0.4002 | 247 | 0.1594 |
| 0.1545 | 0.4213 | 260 | 0.1590 |
| 0.1619 | 0.4423 | 273 | 0.1595 |
| 0.1561 | 0.4634 | 286 | 0.1589 |
| 0.1605 | 0.4845 | 299 | 0.1578 |
| 0.1495 | 0.5055 | 312 | 0.1584 |
| 0.1473 | 0.5266 | 325 | 0.1579 |
| 0.1505 | 0.5476 | 338 | 0.1568 |
| 0.1525 | 0.5687 | 351 | 0.1564 |
| 0.1565 | 0.5898 | 364 | 0.1560 |
| 0.1514 | 0.6108 | 377 | 0.1557 |
| 0.1459 | 0.6319 | 390 | 0.1550 |
| 0.1537 | 0.6530 | 403 | 0.1544 |
| 0.1539 | 0.6740 | 416 | 0.1545 |
| 0.1512 | 0.6951 | 429 | 0.1546 |
| 0.1536 | 0.7162 | 442 | 0.1540 |
| 0.1468 | 0.7372 | 455 | 0.1532 |
| 0.1504 | 0.7583 | 468 | 0.1532 |
| 0.1509 | 0.7793 | 481 | 0.1532 |
| 0.1506 | 0.8004 | 494 | 0.1530 |
| 0.147 | 0.8215 | 507 | 0.1527 |
| 0.1473 | 0.8425 | 520 | 0.1526 |
| 0.1505 | 0.8636 | 533 | 0.1526 |
| 0.1503 | 0.8847 | 546 | 0.1525 |
| 0.1474 | 0.9057 | 559 | 0.1524 |
| 0.1461 | 0.9268 | 572 | 0.1525 |
| 0.1459 | 0.9478 | 585 | 0.1523 |
| 0.1458 | 0.9689 | 598 | 0.1524 |
| 0.1523 | 0.9900 | 611 | 0.1523 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |