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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: distilbert/distilgpt2 |
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model-index: |
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- name: MiniProject_Prescription_Chatbot |
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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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# MiniProject_Prescription_Chatbot |
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This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6475 |
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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: 2e-05 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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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 | 1.0 | 12 | 3.8781 | |
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| No log | 2.0 | 24 | 3.7741 | |
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| No log | 3.0 | 36 | 3.6911 | |
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| No log | 4.0 | 48 | 3.6233 | |
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| No log | 5.0 | 60 | 3.5601 | |
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| No log | 6.0 | 72 | 3.5104 | |
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| No log | 7.0 | 84 | 3.4804 | |
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| No log | 8.0 | 96 | 3.4457 | |
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| No log | 9.0 | 108 | 3.4133 | |
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| No log | 10.0 | 120 | 3.4018 | |
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| No log | 11.0 | 132 | 3.3834 | |
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| No log | 12.0 | 144 | 3.3487 | |
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| No log | 13.0 | 156 | 3.3486 | |
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| No log | 14.0 | 168 | 3.3230 | |
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| No log | 15.0 | 180 | 3.3198 | |
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| No log | 16.0 | 192 | 3.2984 | |
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| No log | 17.0 | 204 | 3.3169 | |
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| No log | 18.0 | 216 | 3.2786 | |
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| No log | 19.0 | 228 | 3.3034 | |
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| No log | 20.0 | 240 | 3.2695 | |
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| No log | 21.0 | 252 | 3.2597 | |
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| No log | 22.0 | 264 | 3.2644 | |
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| No log | 23.0 | 276 | 3.2610 | |
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| No log | 24.0 | 288 | 3.2862 | |
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| No log | 25.0 | 300 | 3.2750 | |
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| No log | 26.0 | 312 | 3.2505 | |
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| No log | 27.0 | 324 | 3.2844 | |
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| No log | 28.0 | 336 | 3.2729 | |
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| No log | 29.0 | 348 | 3.2894 | |
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| No log | 30.0 | 360 | 3.2875 | |
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| No log | 31.0 | 372 | 3.2735 | |
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| No log | 32.0 | 384 | 3.2998 | |
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| No log | 33.0 | 396 | 3.3070 | |
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| No log | 34.0 | 408 | 3.2893 | |
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| No log | 35.0 | 420 | 3.2935 | |
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| No log | 36.0 | 432 | 3.3057 | |
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| No log | 37.0 | 444 | 3.3028 | |
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| No log | 38.0 | 456 | 3.3239 | |
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| No log | 39.0 | 468 | 3.3158 | |
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| No log | 40.0 | 480 | 3.3249 | |
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| No log | 41.0 | 492 | 3.3595 | |
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| 2.5614 | 42.0 | 504 | 3.3610 | |
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| 2.5614 | 43.0 | 516 | 3.3546 | |
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| 2.5614 | 44.0 | 528 | 3.3815 | |
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| 2.5614 | 45.0 | 540 | 3.3620 | |
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| 2.5614 | 46.0 | 552 | 3.3823 | |
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| 2.5614 | 47.0 | 564 | 3.3800 | |
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| 2.5614 | 48.0 | 576 | 3.4000 | |
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| 2.5614 | 49.0 | 588 | 3.4191 | |
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| 2.5614 | 50.0 | 600 | 3.4093 | |
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| 2.5614 | 51.0 | 612 | 3.4162 | |
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| 2.5614 | 52.0 | 624 | 3.4197 | |
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| 2.5614 | 53.0 | 636 | 3.4370 | |
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| 2.5614 | 54.0 | 648 | 3.4442 | |
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| 2.5614 | 55.0 | 660 | 3.4767 | |
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| 2.5614 | 56.0 | 672 | 3.4642 | |
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| 2.5614 | 57.0 | 684 | 3.4780 | |
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| 2.5614 | 58.0 | 696 | 3.4808 | |
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| 2.5614 | 59.0 | 708 | 3.4712 | |
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| 2.5614 | 60.0 | 720 | 3.5279 | |
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| 2.5614 | 61.0 | 732 | 3.4993 | |
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| 2.5614 | 62.0 | 744 | 3.4865 | |
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| 2.5614 | 63.0 | 756 | 3.5209 | |
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| 2.5614 | 64.0 | 768 | 3.5196 | |
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| 2.5614 | 65.0 | 780 | 3.5359 | |
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| 2.5614 | 66.0 | 792 | 3.5089 | |
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| 2.5614 | 67.0 | 804 | 3.5489 | |
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| 2.5614 | 68.0 | 816 | 3.5528 | |
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| 2.5614 | 69.0 | 828 | 3.5587 | |
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| 2.5614 | 70.0 | 840 | 3.5606 | |
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| 2.5614 | 71.0 | 852 | 3.5719 | |
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| 2.5614 | 72.0 | 864 | 3.5776 | |
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| 2.5614 | 73.0 | 876 | 3.5700 | |
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| 2.5614 | 74.0 | 888 | 3.5825 | |
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| 2.5614 | 75.0 | 900 | 3.5779 | |
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| 2.5614 | 76.0 | 912 | 3.5934 | |
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| 2.5614 | 77.0 | 924 | 3.5878 | |
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| 2.5614 | 78.0 | 936 | 3.5850 | |
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| 2.5614 | 79.0 | 948 | 3.5936 | |
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| 2.5614 | 80.0 | 960 | 3.6018 | |
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| 2.5614 | 81.0 | 972 | 3.6096 | |
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| 2.5614 | 82.0 | 984 | 3.6155 | |
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| 2.5614 | 83.0 | 996 | 3.6183 | |
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| 1.4096 | 84.0 | 1008 | 3.6267 | |
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| 1.4096 | 85.0 | 1020 | 3.6292 | |
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| 1.4096 | 86.0 | 1032 | 3.6350 | |
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| 1.4096 | 87.0 | 1044 | 3.6347 | |
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| 1.4096 | 88.0 | 1056 | 3.6314 | |
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| 1.4096 | 89.0 | 1068 | 3.6300 | |
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| 1.4096 | 90.0 | 1080 | 3.6333 | |
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| 1.4096 | 91.0 | 1092 | 3.6452 | |
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| 1.4096 | 92.0 | 1104 | 3.6503 | |
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| 1.4096 | 93.0 | 1116 | 3.6501 | |
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| 1.4096 | 94.0 | 1128 | 3.6398 | |
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| 1.4096 | 95.0 | 1140 | 3.6374 | |
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| 1.4096 | 96.0 | 1152 | 3.6402 | |
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| 1.4096 | 97.0 | 1164 | 3.6443 | |
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| 1.4096 | 98.0 | 1176 | 3.6472 | |
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| 1.4096 | 99.0 | 1188 | 3.6479 | |
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| 1.4096 | 100.0 | 1200 | 3.6475 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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