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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_default |
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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_default |
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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: 10.8086 |
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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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| 0.7172 | 0.0211 | 13 | 1.3535 | |
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| 1.2917 | 0.0421 | 26 | 1.8068 | |
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| 1.992 | 0.0632 | 39 | 3.1112 | |
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| 2.9907 | 0.0843 | 52 | 4.2249 | |
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| 4.8887 | 0.1053 | 65 | 11.0938 | |
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| 10.1689 | 0.1264 | 78 | 10.8044 | |
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| 10.1275 | 0.1474 | 91 | 10.8124 | |
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| 10.7459 | 0.1685 | 104 | 11.7846 | |
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| 11.8895 | 0.1896 | 117 | 12.0598 | |
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| 12.0118 | 0.2106 | 130 | 11.9669 | |
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| 11.9758 | 0.2317 | 143 | 11.9468 | |
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| 11.9457 | 0.2528 | 156 | 11.9325 | |
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| 11.8852 | 0.2738 | 169 | 11.7855 | |
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| 11.8173 | 0.2949 | 182 | 11.7749 | |
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| 11.7659 | 0.3159 | 195 | 11.7242 | |
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| 11.6916 | 0.3370 | 208 | 11.6713 | |
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| 11.7335 | 0.3581 | 221 | 11.6871 | |
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| 11.6317 | 0.3791 | 234 | 11.4314 | |
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| 11.4129 | 0.4002 | 247 | 11.2565 | |
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| 11.3691 | 0.4213 | 260 | 11.3368 | |
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| 11.5425 | 0.4423 | 273 | 11.5908 | |
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| 11.5115 | 0.4634 | 286 | 11.2716 | |
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| 11.398 | 0.4845 | 299 | 11.3439 | |
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| 11.3467 | 0.5055 | 312 | 11.3315 | |
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| 11.2106 | 0.5266 | 325 | 11.0557 | |
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| 11.3123 | 0.5476 | 338 | 11.2704 | |
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| 11.1559 | 0.5687 | 351 | 11.0238 | |
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| 10.996 | 0.5898 | 364 | 11.2103 | |
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| 11.1641 | 0.6108 | 377 | 10.9649 | |
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| 11.1403 | 0.6319 | 390 | 10.9743 | |
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| 10.9823 | 0.6530 | 403 | 11.0703 | |
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| 10.9891 | 0.6740 | 416 | 10.9547 | |
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| 10.932 | 0.6951 | 429 | 10.8953 | |
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| 11.0158 | 0.7162 | 442 | 10.9839 | |
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| 10.8677 | 0.7372 | 455 | 10.8881 | |
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| 10.9204 | 0.7583 | 468 | 10.9832 | |
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| 10.911 | 0.7793 | 481 | 10.9743 | |
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| 10.8973 | 0.8004 | 494 | 10.8108 | |
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| 10.7819 | 0.8215 | 507 | 10.9354 | |
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| 10.7843 | 0.8425 | 520 | 10.8324 | |
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| 10.8343 | 0.8636 | 533 | 10.9296 | |
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| 10.7756 | 0.8847 | 546 | 10.7629 | |
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| 10.781 | 0.9057 | 559 | 10.7852 | |
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| 10.806 | 0.9268 | 572 | 10.8285 | |
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| 10.7984 | 0.9478 | 585 | 10.7972 | |
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| 10.7722 | 0.9689 | 598 | 10.7924 | |
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| 10.7957 | 0.9900 | 611 | 10.8086 | |
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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 |
