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---
base_model: unsloth/Qwen2-7B
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Qwen2-7B_metamath_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. -->
# Qwen2-7B_metamath_ortho
This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co./unsloth/Qwen2-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2061
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.1901 | 0.0211 | 13 | 0.1752 |
| 0.1801 | 0.0421 | 26 | 0.2122 |
| 0.2158 | 0.0632 | 39 | 0.2351 |
| 0.2309 | 0.0842 | 52 | 0.2526 |
| 0.242 | 0.1053 | 65 | 0.2650 |
| 0.2587 | 0.1264 | 78 | 0.2717 |
| 0.2671 | 0.1474 | 91 | 0.2770 |
| 0.2594 | 0.1685 | 104 | 0.2786 |
| 0.2707 | 0.1896 | 117 | 0.2831 |
| 0.2661 | 0.2106 | 130 | 0.2895 |
| 0.2795 | 0.2317 | 143 | 0.2919 |
| 0.2747 | 0.2527 | 156 | 0.2873 |
| 0.2824 | 0.2738 | 169 | 0.2873 |
| 0.2717 | 0.2949 | 182 | 0.2873 |
| 0.2801 | 0.3159 | 195 | 0.2838 |
| 0.2713 | 0.3370 | 208 | 0.2821 |
| 0.2678 | 0.3580 | 221 | 0.2797 |
| 0.2692 | 0.3791 | 234 | 0.2787 |
| 0.2671 | 0.4002 | 247 | 0.2769 |
| 0.268 | 0.4212 | 260 | 0.2742 |
| 0.2713 | 0.4423 | 273 | 0.2729 |
| 0.26 | 0.4633 | 286 | 0.2679 |
| 0.2677 | 0.4844 | 299 | 0.2628 |
| 0.248 | 0.5055 | 312 | 0.2594 |
| 0.2481 | 0.5265 | 325 | 0.2574 |
| 0.2381 | 0.5476 | 338 | 0.2521 |
| 0.2427 | 0.5687 | 351 | 0.2501 |
| 0.2463 | 0.5897 | 364 | 0.2442 |
| 0.2339 | 0.6108 | 377 | 0.2396 |
| 0.2304 | 0.6318 | 390 | 0.2343 |
| 0.2291 | 0.6529 | 403 | 0.2309 |
| 0.2308 | 0.6740 | 416 | 0.2291 |
| 0.224 | 0.6950 | 429 | 0.2254 |
| 0.2248 | 0.7161 | 442 | 0.2224 |
| 0.2122 | 0.7371 | 455 | 0.2184 |
| 0.2135 | 0.7582 | 468 | 0.2162 |
| 0.2181 | 0.7793 | 481 | 0.2154 |
| 0.213 | 0.8003 | 494 | 0.2133 |
| 0.2022 | 0.8214 | 507 | 0.2115 |
| 0.2084 | 0.8424 | 520 | 0.2093 |
| 0.206 | 0.8635 | 533 | 0.2080 |
| 0.201 | 0.8846 | 546 | 0.2074 |
| 0.1971 | 0.9056 | 559 | 0.2069 |
| 0.1986 | 0.9267 | 572 | 0.2065 |
| 0.2049 | 0.9478 | 585 | 0.2064 |
| 0.2034 | 0.9688 | 598 | 0.2061 |
| 0.2044 | 0.9899 | 611 | 0.2061 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |