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--- |
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license: apache-2.0 |
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base_model: EleutherAI/pythia-70m-deduped |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [EleutherAI/pythia-70m-deduped](https://huggingface.co./EleutherAI/pythia-70m-deduped) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2691 |
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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: 5e-05 |
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- train_batch_size: 100 |
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- eval_batch_size: 100 |
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- seed: 42 |
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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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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.852 | 0.1 | 1 | 3.1074 | |
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| 3.0923 | 0.2 | 2 | 2.3879 | |
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| 2.3371 | 0.3 | 3 | 2.1025 | |
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| 2.1166 | 0.4 | 4 | 1.9761 | |
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| 2.0538 | 0.5 | 5 | 1.8446 | |
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| 1.8972 | 0.6 | 6 | 1.7470 | |
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| 1.8356 | 0.7 | 7 | 1.6615 | |
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| 1.702 | 0.8 | 8 | 1.6187 | |
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| 1.6907 | 0.9 | 9 | 1.6626 | |
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| 1.5877 | 1.0 | 10 | 1.6192 | |
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| 1.6332 | 1.1 | 11 | 1.5464 | |
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| 1.4906 | 1.2 | 12 | 1.5091 | |
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| 1.5267 | 1.3 | 13 | 1.4850 | |
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| 1.4857 | 1.4 | 14 | 1.4572 | |
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| 1.4247 | 1.5 | 15 | 1.4319 | |
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| 1.4815 | 1.6 | 16 | 1.4207 | |
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| 1.3584 | 1.7 | 17 | 1.4092 | |
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| 1.4812 | 1.8 | 18 | 1.4196 | |
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| 1.4381 | 1.9 | 19 | 1.4021 | |
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| 1.453 | 2.0 | 20 | 1.4013 | |
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| 1.3468 | 2.1 | 21 | 1.3781 | |
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| 1.3327 | 2.2 | 22 | 1.3598 | |
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| 1.3623 | 2.3 | 23 | 1.3516 | |
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| 1.2876 | 2.4 | 24 | 1.3384 | |
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| 1.374 | 2.5 | 25 | 1.3366 | |
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| 1.3863 | 2.6 | 26 | 1.3265 | |
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| 1.3327 | 2.7 | 27 | 1.3186 | |
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| 1.2886 | 2.8 | 28 | 1.3130 | |
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| 1.3842 | 2.9 | 29 | 1.3024 | |
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| 1.3105 | 3.0 | 30 | 1.2986 | |
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| 1.2331 | 3.1 | 31 | 1.2966 | |
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| 1.3227 | 3.2 | 32 | 1.2954 | |
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| 1.2923 | 3.3 | 33 | 1.2928 | |
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| 1.2976 | 3.4 | 34 | 1.2901 | |
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| 1.3207 | 3.5 | 35 | 1.2879 | |
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| 1.2455 | 3.6 | 36 | 1.2834 | |
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| 1.2546 | 3.7 | 37 | 1.2779 | |
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| 1.2999 | 3.8 | 38 | 1.2744 | |
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| 1.2484 | 3.9 | 39 | 1.2723 | |
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| 1.281 | 4.0 | 40 | 1.2720 | |
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| 1.2134 | 4.1 | 41 | 1.2722 | |
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| 1.214 | 4.2 | 42 | 1.2721 | |
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| 1.3031 | 4.3 | 43 | 1.2715 | |
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| 1.2174 | 4.4 | 44 | 1.2708 | |
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| 1.2359 | 4.5 | 45 | 1.2703 | |
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| 1.2578 | 4.6 | 46 | 1.2699 | |
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| 1.2815 | 4.7 | 47 | 1.2695 | |
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| 1.2866 | 4.8 | 48 | 1.2693 | |
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| 1.2878 | 4.9 | 49 | 1.2691 | |
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| 1.2214 | 5.0 | 50 | 1.2691 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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