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--- |
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base_model: unsloth/Qwen2-7B |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: Qwen2-7B_metamath_reverse |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Qwen2-7B_metamath_reverse |
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This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co/unsloth/Qwen2-7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2138 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.02 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.1753 | 0.0211 | 13 | 0.1875 | |
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| 0.2025 | 0.0421 | 26 | 0.2505 | |
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| 0.259 | 0.0632 | 39 | 0.2862 | |
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| 0.2849 | 0.0842 | 52 | 0.3049 | |
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| 0.2973 | 0.1053 | 65 | 0.3251 | |
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| 0.3177 | 0.1264 | 78 | 0.3333 | |
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| 0.325 | 0.1474 | 91 | 0.3354 | |
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| 0.3151 | 0.1685 | 104 | 0.3331 | |
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| 0.3285 | 0.1896 | 117 | 0.3399 | |
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| 0.3239 | 0.2106 | 130 | 0.3437 | |
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| 0.3332 | 0.2317 | 143 | 0.3472 | |
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| 0.334 | 0.2527 | 156 | 0.3382 | |
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| 0.3326 | 0.2738 | 169 | 0.3350 | |
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| 0.3218 | 0.2949 | 182 | 0.3350 | |
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| 0.3285 | 0.3159 | 195 | 0.3321 | |
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| 0.3155 | 0.3370 | 208 | 0.3288 | |
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| 0.3167 | 0.3580 | 221 | 0.3286 | |
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| 0.3139 | 0.3791 | 234 | 0.3219 | |
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| 0.3064 | 0.4002 | 247 | 0.3196 | |
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| 0.309 | 0.4212 | 260 | 0.3154 | |
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| 0.3138 | 0.4423 | 273 | 0.3132 | |
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| 0.298 | 0.4633 | 286 | 0.3069 | |
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| 0.3019 | 0.4844 | 299 | 0.2991 | |
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| 0.2823 | 0.5055 | 312 | 0.2951 | |
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| 0.2875 | 0.5265 | 325 | 0.2882 | |
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| 0.272 | 0.5476 | 338 | 0.2818 | |
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| 0.2697 | 0.5687 | 351 | 0.2770 | |
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| 0.2711 | 0.5897 | 364 | 0.2703 | |
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| 0.261 | 0.6108 | 377 | 0.2649 | |
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| 0.2515 | 0.6318 | 390 | 0.2592 | |
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| 0.253 | 0.6529 | 403 | 0.2546 | |
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| 0.2529 | 0.6740 | 416 | 0.2493 | |
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| 0.2424 | 0.6950 | 429 | 0.2447 | |
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| 0.2448 | 0.7161 | 442 | 0.2404 | |
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| 0.2278 | 0.7371 | 455 | 0.2340 | |
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| 0.2289 | 0.7582 | 468 | 0.2313 | |
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| 0.2315 | 0.7793 | 481 | 0.2279 | |
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| 0.225 | 0.8003 | 494 | 0.2246 | |
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| 0.2127 | 0.8214 | 507 | 0.2213 | |
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| 0.2199 | 0.8424 | 520 | 0.2191 | |
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| 0.2131 | 0.8635 | 533 | 0.2175 | |
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| 0.2107 | 0.8846 | 546 | 0.2160 | |
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| 0.2073 | 0.9056 | 559 | 0.2152 | |
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| 0.2062 | 0.9267 | 572 | 0.2147 | |
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| 0.214 | 0.9478 | 585 | 0.2143 | |
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| 0.2118 | 0.9688 | 598 | 0.2138 | |
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| 0.2107 | 0.9899 | 611 | 0.2138 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
