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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_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. -->
# Qwen2-7B_metamath_reverse
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: 0.2138
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.1753 | 0.0211 | 13 | 0.1875 |
| 0.2025 | 0.0421 | 26 | 0.2505 |
| 0.259 | 0.0632 | 39 | 0.2862 |
| 0.2849 | 0.0842 | 52 | 0.3049 |
| 0.2973 | 0.1053 | 65 | 0.3251 |
| 0.3177 | 0.1264 | 78 | 0.3333 |
| 0.325 | 0.1474 | 91 | 0.3354 |
| 0.3151 | 0.1685 | 104 | 0.3331 |
| 0.3285 | 0.1896 | 117 | 0.3399 |
| 0.3239 | 0.2106 | 130 | 0.3437 |
| 0.3332 | 0.2317 | 143 | 0.3472 |
| 0.334 | 0.2527 | 156 | 0.3382 |
| 0.3326 | 0.2738 | 169 | 0.3350 |
| 0.3218 | 0.2949 | 182 | 0.3350 |
| 0.3285 | 0.3159 | 195 | 0.3321 |
| 0.3155 | 0.3370 | 208 | 0.3288 |
| 0.3167 | 0.3580 | 221 | 0.3286 |
| 0.3139 | 0.3791 | 234 | 0.3219 |
| 0.3064 | 0.4002 | 247 | 0.3196 |
| 0.309 | 0.4212 | 260 | 0.3154 |
| 0.3138 | 0.4423 | 273 | 0.3132 |
| 0.298 | 0.4633 | 286 | 0.3069 |
| 0.3019 | 0.4844 | 299 | 0.2991 |
| 0.2823 | 0.5055 | 312 | 0.2951 |
| 0.2875 | 0.5265 | 325 | 0.2882 |
| 0.272 | 0.5476 | 338 | 0.2818 |
| 0.2697 | 0.5687 | 351 | 0.2770 |
| 0.2711 | 0.5897 | 364 | 0.2703 |
| 0.261 | 0.6108 | 377 | 0.2649 |
| 0.2515 | 0.6318 | 390 | 0.2592 |
| 0.253 | 0.6529 | 403 | 0.2546 |
| 0.2529 | 0.6740 | 416 | 0.2493 |
| 0.2424 | 0.6950 | 429 | 0.2447 |
| 0.2448 | 0.7161 | 442 | 0.2404 |
| 0.2278 | 0.7371 | 455 | 0.2340 |
| 0.2289 | 0.7582 | 468 | 0.2313 |
| 0.2315 | 0.7793 | 481 | 0.2279 |
| 0.225 | 0.8003 | 494 | 0.2246 |
| 0.2127 | 0.8214 | 507 | 0.2213 |
| 0.2199 | 0.8424 | 520 | 0.2191 |
| 0.2131 | 0.8635 | 533 | 0.2175 |
| 0.2107 | 0.8846 | 546 | 0.2160 |
| 0.2073 | 0.9056 | 559 | 0.2152 |
| 0.2062 | 0.9267 | 572 | 0.2147 |
| 0.214 | 0.9478 | 585 | 0.2143 |
| 0.2118 | 0.9688 | 598 | 0.2138 |
| 0.2107 | 0.9899 | 611 | 0.2138 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |