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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: calculator_model_test |
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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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# calculator_model_test |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7800 |
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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: 512 |
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- eval_batch_size: 512 |
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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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- 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 | 1.0 | 6 | 6.5672 | |
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| No log | 2.0 | 12 | 5.9069 | |
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| No log | 3.0 | 18 | 5.4671 | |
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| No log | 4.0 | 24 | 5.0855 | |
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| No log | 5.0 | 30 | 4.7085 | |
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| No log | 6.0 | 36 | 4.3935 | |
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| No log | 7.0 | 42 | 4.1354 | |
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| No log | 8.0 | 48 | 3.9330 | |
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| No log | 9.0 | 54 | 3.7647 | |
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| No log | 10.0 | 60 | 3.6286 | |
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| No log | 11.0 | 66 | 3.5173 | |
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| No log | 12.0 | 72 | 3.4148 | |
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| No log | 13.0 | 78 | 3.3148 | |
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| No log | 14.0 | 84 | 3.2218 | |
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| No log | 15.0 | 90 | 3.1353 | |
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| No log | 16.0 | 96 | 3.0524 | |
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| No log | 17.0 | 102 | 2.9751 | |
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| No log | 18.0 | 108 | 2.9017 | |
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| No log | 19.0 | 114 | 2.8277 | |
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| No log | 20.0 | 120 | 2.7534 | |
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| No log | 21.0 | 126 | 2.6865 | |
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| No log | 22.0 | 132 | 2.6260 | |
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| No log | 23.0 | 138 | 2.5597 | |
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| No log | 24.0 | 144 | 2.4913 | |
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| No log | 25.0 | 150 | 2.4295 | |
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| No log | 26.0 | 156 | 2.3668 | |
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| No log | 27.0 | 162 | 2.3040 | |
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| No log | 28.0 | 168 | 2.2391 | |
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| No log | 29.0 | 174 | 2.1745 | |
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| No log | 30.0 | 180 | 2.1036 | |
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| No log | 31.0 | 186 | 2.0443 | |
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| No log | 32.0 | 192 | 1.9919 | |
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| No log | 33.0 | 198 | 1.9321 | |
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| No log | 34.0 | 204 | 1.8771 | |
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| No log | 35.0 | 210 | 1.8386 | |
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| No log | 36.0 | 216 | 1.7951 | |
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| No log | 37.0 | 222 | 1.7460 | |
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| No log | 38.0 | 228 | 1.6974 | |
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| No log | 39.0 | 234 | 1.6576 | |
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| No log | 40.0 | 240 | 1.6112 | |
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| No log | 41.0 | 246 | 1.5811 | |
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| No log | 42.0 | 252 | 1.5540 | |
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| No log | 43.0 | 258 | 1.5268 | |
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| No log | 44.0 | 264 | 1.4873 | |
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| No log | 45.0 | 270 | 1.4500 | |
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| No log | 46.0 | 276 | 1.4161 | |
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| No log | 47.0 | 282 | 1.3738 | |
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| No log | 48.0 | 288 | 1.3495 | |
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| No log | 49.0 | 294 | 1.3182 | |
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| No log | 50.0 | 300 | 1.2899 | |
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| No log | 51.0 | 306 | 1.2610 | |
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| No log | 52.0 | 312 | 1.2478 | |
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| No log | 53.0 | 318 | 1.2238 | |
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| No log | 54.0 | 324 | 1.2060 | |
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| No log | 55.0 | 330 | 1.1794 | |
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| No log | 56.0 | 336 | 1.1774 | |
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| No log | 57.0 | 342 | 1.1425 | |
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| No log | 58.0 | 348 | 1.1166 | |
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| No log | 59.0 | 354 | 1.1044 | |
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| No log | 60.0 | 360 | 1.0913 | |
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| No log | 61.0 | 366 | 1.0775 | |
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| No log | 62.0 | 372 | 1.0694 | |
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| No log | 63.0 | 378 | 1.0311 | |
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| No log | 64.0 | 384 | 1.0272 | |
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| No log | 65.0 | 390 | 1.0249 | |
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| No log | 66.0 | 396 | 0.9923 | |
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| No log | 67.0 | 402 | 0.9892 | |
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| No log | 68.0 | 408 | 0.9762 | |
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| No log | 69.0 | 414 | 0.9704 | |
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| No log | 70.0 | 420 | 0.9405 | |
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| No log | 71.0 | 426 | 0.9394 | |
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| No log | 72.0 | 432 | 0.9237 | |
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| No log | 73.0 | 438 | 0.9180 | |
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| No log | 74.0 | 444 | 0.8926 | |
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| No log | 75.0 | 450 | 0.9081 | |
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| No log | 76.0 | 456 | 0.8778 | |
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| No log | 77.0 | 462 | 0.8785 | |
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| No log | 78.0 | 468 | 0.8580 | |
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| No log | 79.0 | 474 | 0.8593 | |
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| No log | 80.0 | 480 | 0.8553 | |
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| No log | 81.0 | 486 | 0.8671 | |
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| No log | 82.0 | 492 | 0.8422 | |
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| No log | 83.0 | 498 | 0.8403 | |
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| 2.0956 | 84.0 | 504 | 0.8355 | |
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| 2.0956 | 85.0 | 510 | 0.8188 | |
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| 2.0956 | 86.0 | 516 | 0.8149 | |
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| 2.0956 | 87.0 | 522 | 0.8285 | |
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| 2.0956 | 88.0 | 528 | 0.8063 | |
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| 2.0956 | 89.0 | 534 | 0.8166 | |
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| 2.0956 | 90.0 | 540 | 0.8008 | |
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| 2.0956 | 91.0 | 546 | 0.8127 | |
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| 2.0956 | 92.0 | 552 | 0.7921 | |
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| 2.0956 | 93.0 | 558 | 0.8015 | |
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| 2.0956 | 94.0 | 564 | 0.7882 | |
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| 2.0956 | 95.0 | 570 | 0.7844 | |
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| 2.0956 | 96.0 | 576 | 0.7862 | |
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| 2.0956 | 97.0 | 582 | 0.7810 | |
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| 2.0956 | 98.0 | 588 | 0.7808 | |
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| 2.0956 | 99.0 | 594 | 0.7810 | |
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| 2.0956 | 100.0 | 600 | 0.7800 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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