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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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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: prueba |
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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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# prueba |
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This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1440 |
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- Precision: 0.6923 |
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- Recall: 0.6096 |
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- F1: 0.6483 |
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- Accuracy: 0.9719 |
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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: 2.5e-05 |
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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: 32 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 29 | 0.3513 | 0.0 | 0.0 | 0.0 | 0.9259 | |
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| No log | 2.0 | 58 | 0.2696 | 0.0 | 0.0 | 0.0 | 0.9259 | |
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| No log | 3.0 | 87 | 0.2879 | 0.0 | 0.0 | 0.0 | 0.9259 | |
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| No log | 4.0 | 116 | 0.2318 | 0.0714 | 0.0080 | 0.0143 | 0.9361 | |
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| No log | 5.0 | 145 | 0.2055 | 0.2222 | 0.0558 | 0.0892 | 0.9376 | |
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| No log | 6.0 | 174 | 0.2076 | 0.3793 | 0.0876 | 0.1424 | 0.9464 | |
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| No log | 7.0 | 203 | 0.1630 | 0.4831 | 0.2271 | 0.3089 | 0.9525 | |
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| No log | 8.0 | 232 | 0.1529 | 0.5515 | 0.3625 | 0.4375 | 0.9573 | |
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| No log | 9.0 | 261 | 0.1519 | 0.5972 | 0.3426 | 0.4354 | 0.9603 | |
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| No log | 10.0 | 290 | 0.1399 | 0.6272 | 0.4223 | 0.5048 | 0.9639 | |
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| No log | 11.0 | 319 | 0.1412 | 0.6096 | 0.4542 | 0.5205 | 0.9641 | |
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| No log | 12.0 | 348 | 0.1320 | 0.5969 | 0.4661 | 0.5235 | 0.9646 | |
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| No log | 13.0 | 377 | 0.1311 | 0.6515 | 0.5139 | 0.5746 | 0.9671 | |
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| No log | 14.0 | 406 | 0.1300 | 0.6329 | 0.5219 | 0.5721 | 0.9656 | |
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| No log | 15.0 | 435 | 0.1346 | 0.6345 | 0.4980 | 0.5580 | 0.9672 | |
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| No log | 16.0 | 464 | 0.1361 | 0.6329 | 0.5219 | 0.5721 | 0.9669 | |
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| No log | 17.0 | 493 | 0.1312 | 0.6532 | 0.5777 | 0.6131 | 0.9689 | |
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| 0.1181 | 18.0 | 522 | 0.1327 | 0.6756 | 0.6056 | 0.6387 | 0.9694 | |
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| 0.1181 | 19.0 | 551 | 0.1495 | 0.7234 | 0.5418 | 0.6196 | 0.9704 | |
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| 0.1181 | 20.0 | 580 | 0.1328 | 0.6872 | 0.5777 | 0.6277 | 0.9707 | |
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| 0.1181 | 21.0 | 609 | 0.1363 | 0.6667 | 0.6215 | 0.6433 | 0.9710 | |
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| 0.1181 | 22.0 | 638 | 0.1392 | 0.6884 | 0.5896 | 0.6352 | 0.9712 | |
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| 0.1181 | 23.0 | 667 | 0.1377 | 0.6437 | 0.6335 | 0.6386 | 0.9704 | |
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| 0.1181 | 24.0 | 696 | 0.1434 | 0.6504 | 0.5857 | 0.6164 | 0.9697 | |
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| 0.1181 | 25.0 | 725 | 0.1418 | 0.6944 | 0.5976 | 0.6424 | 0.9710 | |
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| 0.1181 | 26.0 | 754 | 0.1426 | 0.6739 | 0.6175 | 0.6445 | 0.9715 | |
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| 0.1181 | 27.0 | 783 | 0.1447 | 0.7085 | 0.6295 | 0.6667 | 0.9734 | |
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| 0.1181 | 28.0 | 812 | 0.1432 | 0.6903 | 0.6215 | 0.6541 | 0.9727 | |
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| 0.1181 | 29.0 | 841 | 0.1421 | 0.7162 | 0.6335 | 0.6723 | 0.9729 | |
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| 0.1181 | 30.0 | 870 | 0.1431 | 0.6875 | 0.6135 | 0.6484 | 0.9720 | |
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| 0.1181 | 31.0 | 899 | 0.1431 | 0.6844 | 0.6135 | 0.6471 | 0.9717 | |
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| 0.1181 | 32.0 | 928 | 0.1440 | 0.6923 | 0.6096 | 0.6483 | 0.9719 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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