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--- |
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base_model: unsloth/gemma-2-9b |
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library_name: peft |
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license: gemma |
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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: gemma-2-9b_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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# gemma-2-9b_metamath_reverse |
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This model is a fine-tuned version of [unsloth/gemma-2-9b](https://huggingface.co./unsloth/gemma-2-9b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 10.7771 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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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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| 0.7164 | 0.0211 | 13 | 0.9526 | |
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| 1.4875 | 0.0421 | 26 | 1.7775 | |
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| 1.8093 | 0.0632 | 39 | 2.4866 | |
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| 2.9457 | 0.0843 | 52 | 3.1388 | |
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| 4.2957 | 0.1053 | 65 | 4.3648 | |
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| 7.9729 | 0.1264 | 78 | 11.0147 | |
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| 10.8099 | 0.1474 | 91 | 9.4330 | |
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| 9.8556 | 0.1685 | 104 | 11.2095 | |
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| 11.4575 | 0.1896 | 117 | 11.8836 | |
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| 11.9399 | 0.2106 | 130 | 11.9231 | |
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| 11.9626 | 0.2317 | 143 | 11.9768 | |
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| 11.9547 | 0.2528 | 156 | 11.8762 | |
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| 11.9008 | 0.2738 | 169 | 11.9031 | |
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| 11.8209 | 0.2949 | 182 | 11.7070 | |
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| 11.7717 | 0.3159 | 195 | 11.8161 | |
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| 11.7063 | 0.3370 | 208 | 11.6304 | |
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| 11.5787 | 0.3581 | 221 | 11.7282 | |
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| 11.6212 | 0.3791 | 234 | 11.4066 | |
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| 11.4214 | 0.4002 | 247 | 11.2306 | |
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| 11.397 | 0.4213 | 260 | 11.3492 | |
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| 11.5241 | 0.4423 | 273 | 11.6393 | |
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| 11.5238 | 0.4634 | 286 | 11.2219 | |
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| 11.3261 | 0.4845 | 299 | 11.2667 | |
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| 11.3066 | 0.5055 | 312 | 11.2729 | |
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| 11.227 | 0.5266 | 325 | 11.0665 | |
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| 11.2074 | 0.5476 | 338 | 11.1924 | |
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| 11.0554 | 0.5687 | 351 | 11.0311 | |
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| 11.0567 | 0.5898 | 364 | 11.1885 | |
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| 11.1251 | 0.6108 | 377 | 10.8923 | |
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| 11.1682 | 0.6319 | 390 | 11.0041 | |
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| 10.9569 | 0.6530 | 403 | 11.0336 | |
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| 10.9747 | 0.6740 | 416 | 10.7973 | |
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| 10.9086 | 0.6951 | 429 | 10.8775 | |
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| 10.9555 | 0.7162 | 442 | 11.0885 | |
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| 10.8633 | 0.7372 | 455 | 10.9284 | |
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| 10.9128 | 0.7583 | 468 | 11.0310 | |
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| 10.9266 | 0.7793 | 481 | 11.0151 | |
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| 10.8317 | 0.8004 | 494 | 10.8168 | |
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| 10.7392 | 0.8215 | 507 | 10.8803 | |
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| 10.7123 | 0.8425 | 520 | 10.7858 | |
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| 10.8527 | 0.8636 | 533 | 10.8239 | |
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| 10.8007 | 0.8847 | 546 | 10.7503 | |
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| 10.7274 | 0.9057 | 559 | 10.7407 | |
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| 10.7662 | 0.9268 | 572 | 10.7765 | |
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| 10.7403 | 0.9478 | 585 | 10.7477 | |
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| 10.7315 | 0.9689 | 598 | 10.7644 | |
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| 10.7675 | 0.9900 | 611 | 10.7771 | |
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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 |
