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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: baseline |
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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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# baseline |
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This model is a fine-tuned version of [](https://huggingface.co./) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6338 |
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- Exact Match: 0.142 |
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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: 0.001 |
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- train_batch_size: 32 |
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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 | Exact Match | |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------:| |
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| 2.6989 | 1.0 | 313 | 1.8586 | 0.0 | |
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| 1.834 | 2.0 | 626 | 1.5284 | 0.003 | |
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| 1.517 | 3.0 | 939 | 1.3632 | 0.005 | |
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| 1.2977 | 4.0 | 1252 | 1.2077 | 0.021 | |
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| 1.124 | 5.0 | 1565 | 1.1030 | 0.037 | |
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| 0.9885 | 6.0 | 1878 | 1.0607 | 0.05 | |
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| 0.8762 | 7.0 | 2191 | 1.0329 | 0.047 | |
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| 0.7698 | 8.0 | 2504 | 1.0087 | 0.063 | |
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| 0.6983 | 9.0 | 2817 | 0.9963 | 0.046 | |
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| 0.6297 | 10.0 | 3130 | 0.9754 | 0.076 | |
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| 0.5719 | 11.0 | 3443 | 0.9907 | 0.075 | |
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| 0.5247 | 12.0 | 3756 | 0.9777 | 0.069 | |
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| 0.4776 | 13.0 | 4069 | 0.9766 | 0.055 | |
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| 0.442 | 14.0 | 4382 | 0.9953 | 0.091 | |
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| 0.4081 | 15.0 | 4695 | 1.0005 | 0.098 | |
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| 0.3783 | 16.0 | 5008 | 1.0274 | 0.093 | |
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| 0.3545 | 17.0 | 5321 | 1.0516 | 0.087 | |
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| 0.3243 | 18.0 | 5634 | 1.0339 | 0.09 | |
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| 0.3045 | 19.0 | 5947 | 1.0419 | 0.078 | |
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| 0.2841 | 20.0 | 6260 | 1.0640 | 0.087 | |
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| 0.2692 | 21.0 | 6573 | 1.0839 | 0.105 | |
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| 0.2543 | 22.0 | 6886 | 1.1608 | 0.064 | |
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| 0.2346 | 23.0 | 7199 | 1.1046 | 0.113 | |
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| 0.2245 | 24.0 | 7512 | 1.1569 | 0.128 | |
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| 0.2135 | 25.0 | 7825 | 1.1242 | 0.108 | |
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| 0.2029 | 26.0 | 8138 | 1.1436 | 0.118 | |
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| 0.1902 | 27.0 | 8451 | 1.2023 | 0.095 | |
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| 0.1832 | 28.0 | 8764 | 1.1556 | 0.115 | |
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| 0.171 | 29.0 | 9077 | 1.2068 | 0.094 | |
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| 0.1639 | 30.0 | 9390 | 1.2101 | 0.151 | |
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| 0.1581 | 31.0 | 9703 | 1.2299 | 0.112 | |
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| 0.1504 | 32.0 | 10016 | 1.3153 | 0.1 | |
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| 0.1463 | 33.0 | 10329 | 1.2785 | 0.091 | |
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| 0.1405 | 34.0 | 10642 | 1.2662 | 0.111 | |
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| 0.1349 | 35.0 | 10955 | 1.2805 | 0.134 | |
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| 0.1291 | 36.0 | 11268 | 1.2516 | 0.137 | |
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| 0.126 | 37.0 | 11581 | 1.3312 | 0.141 | |
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| 0.1204 | 38.0 | 11894 | 1.2776 | 0.116 | |
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| 0.1163 | 39.0 | 12207 | 1.3203 | 0.11 | |
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| 0.114 | 40.0 | 12520 | 1.3212 | 0.129 | |
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| 0.1056 | 41.0 | 12833 | 1.3291 | 0.127 | |
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| 0.1033 | 42.0 | 13146 | 1.3010 | 0.125 | |
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| 0.1034 | 43.0 | 13459 | 1.3206 | 0.135 | |
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| 0.098 | 44.0 | 13772 | 1.3879 | 0.127 | |
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| 0.0951 | 45.0 | 14085 | 1.3693 | 0.111 | |
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| 0.089 | 46.0 | 14398 | 1.4261 | 0.124 | |
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| 0.0913 | 47.0 | 14711 | 1.3644 | 0.122 | |
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| 0.0863 | 48.0 | 15024 | 1.4392 | 0.108 | |
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| 0.0809 | 49.0 | 15337 | 1.3726 | 0.098 | |
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| 0.0795 | 50.0 | 15650 | 1.3791 | 0.084 | |
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| 0.0763 | 51.0 | 15963 | 1.3911 | 0.134 | |
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| 0.0768 | 52.0 | 16276 | 1.4202 | 0.104 | |
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| 0.076 | 53.0 | 16589 | 1.4594 | 0.122 | |
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| 0.0734 | 54.0 | 16902 | 1.4541 | 0.129 | |
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| 0.0714 | 55.0 | 17215 | 1.4032 | 0.133 | |
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| 0.0696 | 56.0 | 17528 | 1.4467 | 0.128 | |
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| 0.0674 | 57.0 | 17841 | 1.4952 | 0.103 | |
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| 0.0657 | 58.0 | 18154 | 1.4582 | 0.14 | |
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| 0.0658 | 59.0 | 18467 | 1.4619 | 0.121 | |
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| 0.061 | 60.0 | 18780 | 1.5447 | 0.111 | |
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| 0.0609 | 61.0 | 19093 | 1.4233 | 0.16 | |
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| 0.0596 | 62.0 | 19406 | 1.4705 | 0.134 | |
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| 0.058 | 63.0 | 19719 | 1.4721 | 0.144 | |
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| 0.0555 | 64.0 | 20032 | 1.4377 | 0.156 | |
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| 0.0532 | 65.0 | 20345 | 1.5016 | 0.125 | |
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| 0.0559 | 66.0 | 20658 | 1.5405 | 0.156 | |
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| 0.0517 | 67.0 | 20971 | 1.5166 | 0.133 | |
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| 0.0499 | 68.0 | 21284 | 1.4787 | 0.139 | |
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| 0.0477 | 69.0 | 21597 | 1.5063 | 0.124 | |
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| 0.0491 | 70.0 | 21910 | 1.5287 | 0.147 | |
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| 0.0464 | 71.0 | 22223 | 1.5428 | 0.131 | |
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| 0.0456 | 72.0 | 22536 | 1.5434 | 0.132 | |
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| 0.0449 | 73.0 | 22849 | 1.5364 | 0.116 | |
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| 0.0432 | 74.0 | 23162 | 1.5830 | 0.12 | |
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| 0.042 | 75.0 | 23475 | 1.5508 | 0.113 | |
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| 0.0403 | 76.0 | 23788 | 1.5146 | 0.134 | |
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| 0.0398 | 77.0 | 24101 | 1.5955 | 0.111 | |
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| 0.0412 | 78.0 | 24414 | 1.5759 | 0.132 | |
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| 0.0391 | 79.0 | 24727 | 1.5588 | 0.136 | |
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| 0.0383 | 80.0 | 25040 | 1.5580 | 0.141 | |
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| 0.0366 | 81.0 | 25353 | 1.5895 | 0.143 | |
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| 0.0365 | 82.0 | 25666 | 1.5637 | 0.148 | |
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| 0.035 | 83.0 | 25979 | 1.6012 | 0.155 | |
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| 0.0359 | 84.0 | 26292 | 1.6130 | 0.118 | |
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| 0.0343 | 85.0 | 26605 | 1.6038 | 0.158 | |
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| 0.0333 | 86.0 | 26918 | 1.6300 | 0.124 | |
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| 0.0318 | 87.0 | 27231 | 1.6259 | 0.145 | |
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| 0.0309 | 88.0 | 27544 | 1.6178 | 0.139 | |
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| 0.0303 | 89.0 | 27857 | 1.6166 | 0.143 | |
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| 0.0302 | 90.0 | 28170 | 1.6394 | 0.141 | |
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| 0.0293 | 91.0 | 28483 | 1.6408 | 0.154 | |
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| 0.0281 | 92.0 | 28796 | 1.6424 | 0.13 | |
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| 0.0288 | 93.0 | 29109 | 1.6426 | 0.136 | |
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| 0.0272 | 94.0 | 29422 | 1.6477 | 0.131 | |
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| 0.0278 | 95.0 | 29735 | 1.6288 | 0.142 | |
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| 0.0264 | 96.0 | 30048 | 1.6251 | 0.142 | |
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| 0.0268 | 97.0 | 30361 | 1.6340 | 0.142 | |
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| 0.0255 | 98.0 | 30674 | 1.6353 | 0.145 | |
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| 0.0263 | 99.0 | 30987 | 1.6333 | 0.143 | |
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| 0.0259 | 100.0 | 31300 | 1.6338 | 0.142 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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