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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: '130000' |
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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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# 130000 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.9987 |
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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: 0.0005 |
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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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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.92 | 3 | 7.0396 | |
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| No log | 1.85 | 6 | 6.5398 | |
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| No log | 2.77 | 9 | 6.3337 | |
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| 6.6916 | 4.0 | 13 | 6.3694 | |
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| 6.6916 | 4.92 | 16 | 6.2945 | |
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| 6.6916 | 5.85 | 19 | 6.3184 | |
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| 6.1092 | 6.77 | 22 | 6.3726 | |
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| 6.1092 | 8.0 | 26 | 6.2948 | |
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| 6.1092 | 8.92 | 29 | 6.3374 | |
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| 6.5151 | 9.85 | 32 | 6.3641 | |
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| 6.5151 | 10.77 | 35 | 6.2335 | |
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| 6.5151 | 12.0 | 39 | 6.1965 | |
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| 5.998 | 12.92 | 42 | 6.0595 | |
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| 5.998 | 13.85 | 45 | 6.0374 | |
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| 5.998 | 14.77 | 48 | 6.0562 | |
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| 5.6623 | 16.0 | 52 | 6.0128 | |
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| 5.6623 | 16.92 | 55 | 5.9999 | |
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| 5.6623 | 17.85 | 58 | 6.0008 | |
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| 5.611 | 18.77 | 61 | 5.9992 | |
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| 5.611 | 20.0 | 65 | 6.0017 | |
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| 5.611 | 20.92 | 68 | 6.0005 | |
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| 5.5519 | 21.85 | 71 | 5.9962 | |
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| 5.5519 | 22.77 | 74 | 5.9964 | |
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| 5.5519 | 24.0 | 78 | 5.9975 | |
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| 5.5841 | 24.92 | 81 | 5.9974 | |
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| 5.5841 | 25.85 | 84 | 6.0000 | |
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| 5.5841 | 26.77 | 87 | 6.0019 | |
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| 5.5582 | 28.0 | 91 | 6.0014 | |
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| 5.5582 | 28.92 | 94 | 6.0016 | |
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| 5.5582 | 29.85 | 97 | 5.9987 | |
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| 5.591 | 30.77 | 100 | 5.9992 | |
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| 5.591 | 32.0 | 104 | 5.9986 | |
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| 5.591 | 32.92 | 107 | 5.9982 | |
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| 5.5638 | 33.85 | 110 | 5.9983 | |
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| 5.5638 | 34.77 | 113 | 5.9987 | |
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| 5.5638 | 36.0 | 117 | 5.9989 | |
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| 5.5683 | 36.92 | 120 | 5.9992 | |
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| 5.5683 | 37.85 | 123 | 5.9995 | |
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| 5.5683 | 38.77 | 126 | 5.9991 | |
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| 5.5628 | 40.0 | 130 | 5.9992 | |
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| 5.5628 | 40.92 | 133 | 5.9992 | |
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| 5.5628 | 41.85 | 136 | 5.9991 | |
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| 5.5628 | 42.77 | 139 | 5.9989 | |
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| 5.5683 | 44.0 | 143 | 5.9987 | |
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| 5.5683 | 44.92 | 146 | 5.9987 | |
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| 5.5683 | 45.85 | 149 | 5.9987 | |
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| 5.5534 | 46.15 | 150 | 5.9987 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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