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prueba2
This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1829
- Precision: 0.7232
- Recall: 0.6454
- F1: 0.6821
- Accuracy: 0.9744
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 32
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 29 | 0.1726 | 0.7014 | 0.5896 | 0.6407 | 0.9720 |
| No log | 2.0 | 58 | 0.1712 | 0.6090 | 0.6454 | 0.6267 | 0.9679 |
| No log | 3.0 | 87 | 0.1665 | 0.6746 | 0.6773 | 0.6759 | 0.9720 |
| No log | 4.0 | 116 | 0.1945 | 0.7042 | 0.5976 | 0.6466 | 0.9719 |
| No log | 5.0 | 145 | 0.1850 | 0.6927 | 0.6016 | 0.6439 | 0.9724 |
| No log | 6.0 | 174 | 0.1872 | 0.6570 | 0.6335 | 0.6450 | 0.9697 |
| No log | 7.0 | 203 | 0.2014 | 0.7527 | 0.5578 | 0.6407 | 0.9730 |
| No log | 8.0 | 232 | 0.1696 | 0.6706 | 0.6733 | 0.6720 | 0.9727 |
| No log | 9.0 | 261 | 0.1743 | 0.6820 | 0.6494 | 0.6653 | 0.9730 |
| No log | 10.0 | 290 | 0.1686 | 0.6735 | 0.6574 | 0.6653 | 0.9730 |
| No log | 11.0 | 319 | 0.1868 | 0.6934 | 0.5857 | 0.6350 | 0.9712 |
| No log | 12.0 | 348 | 0.1930 | 0.7089 | 0.6016 | 0.6509 | 0.9727 |
| No log | 13.0 | 377 | 0.1826 | 0.7087 | 0.6494 | 0.6778 | 0.9730 |
| No log | 14.0 | 406 | 0.1920 | 0.7103 | 0.6056 | 0.6538 | 0.9722 |
| No log | 15.0 | 435 | 0.1848 | 0.6402 | 0.6733 | 0.6563 | 0.9712 |
| No log | 16.0 | 464 | 0.1843 | 0.6822 | 0.6414 | 0.6612 | 0.9734 |
| No log | 17.0 | 493 | 0.1874 | 0.7009 | 0.6255 | 0.6611 | 0.9730 |
| 0.0016 | 18.0 | 522 | 0.1844 | 0.6736 | 0.6494 | 0.6613 | 0.9730 |
| 0.0016 | 19.0 | 551 | 0.1850 | 0.7273 | 0.6375 | 0.6794 | 0.9744 |
| 0.0016 | 20.0 | 580 | 0.1737 | 0.7179 | 0.6693 | 0.6928 | 0.9749 |
| 0.0016 | 21.0 | 609 | 0.1798 | 0.7376 | 0.6494 | 0.6907 | 0.9747 |
| 0.0016 | 22.0 | 638 | 0.1797 | 0.7174 | 0.6574 | 0.6861 | 0.9739 |
| 0.0016 | 23.0 | 667 | 0.1783 | 0.7046 | 0.6653 | 0.6844 | 0.9742 |
| 0.0016 | 24.0 | 696 | 0.1784 | 0.7301 | 0.6574 | 0.6918 | 0.9745 |
| 0.0016 | 25.0 | 725 | 0.1818 | 0.7352 | 0.6414 | 0.6851 | 0.9745 |
| 0.0016 | 26.0 | 754 | 0.1823 | 0.7419 | 0.6414 | 0.6880 | 0.9745 |
| 0.0016 | 27.0 | 783 | 0.1786 | 0.7205 | 0.6574 | 0.6875 | 0.9749 |
| 0.0016 | 28.0 | 812 | 0.1781 | 0.7051 | 0.6574 | 0.6804 | 0.9734 |
| 0.0016 | 29.0 | 841 | 0.1802 | 0.7181 | 0.6494 | 0.6820 | 0.9744 |
| 0.0016 | 30.0 | 870 | 0.1801 | 0.7174 | 0.6574 | 0.6861 | 0.9749 |
| 0.0016 | 31.0 | 899 | 0.1824 | 0.7232 | 0.6454 | 0.6821 | 0.9745 |
| 0.0016 | 32.0 | 928 | 0.1829 | 0.7232 | 0.6454 | 0.6821 | 0.9744 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
