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This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1790
- Precision: 0.5417
- Recall: 0.5617
- F1: 0.5515
- Accuracy: 0.9711
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: 5.25e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | 0.2546 | 0.0 | 0.0 | 0.0 | 0.9475 |
| No log | 2.0 | 58 | 0.2270 | 0.0 | 0.0 | 0.0 | 0.9475 |
| No log | 3.0 | 87 | 0.2095 | 0.0 | 0.0 | 0.0 | 0.9475 |
| No log | 4.0 | 116 | 0.1961 | 0.0 | 0.0 | 0.0 | 0.9462 |
| No log | 5.0 | 145 | 0.1666 | 0.1786 | 0.0309 | 0.0526 | 0.9537 |
| No log | 6.0 | 174 | 0.1471 | 0.5385 | 0.1296 | 0.2090 | 0.9606 |
| No log | 7.0 | 203 | 0.1391 | 0.4085 | 0.1790 | 0.2489 | 0.9628 |
| No log | 8.0 | 232 | 0.1338 | 0.4576 | 0.3333 | 0.3857 | 0.9653 |
| No log | 9.0 | 261 | 0.1359 | 0.4 | 0.3704 | 0.3846 | 0.9656 |
| No log | 10.0 | 290 | 0.1429 | 0.47 | 0.2901 | 0.3588 | 0.9675 |
| No log | 11.0 | 319 | 0.1299 | 0.4872 | 0.4691 | 0.4780 | 0.9692 |
| No log | 12.0 | 348 | 0.1380 | 0.3938 | 0.5494 | 0.4588 | 0.9625 |
| No log | 13.0 | 377 | 0.1426 | 0.4970 | 0.5123 | 0.5046 | 0.9696 |
| No log | 14.0 | 406 | 0.1492 | 0.4378 | 0.5432 | 0.4848 | 0.9651 |
| No log | 15.0 | 435 | 0.1460 | 0.4286 | 0.5370 | 0.4767 | 0.9656 |
| No log | 16.0 | 464 | 0.1479 | 0.5380 | 0.5247 | 0.5312 | 0.9699 |
| No log | 17.0 | 493 | 0.1558 | 0.4673 | 0.5741 | 0.5152 | 0.9679 |
| 0.1212 | 18.0 | 522 | 0.1617 | 0.5442 | 0.4938 | 0.5178 | 0.9712 |
| 0.1212 | 19.0 | 551 | 0.1672 | 0.4686 | 0.5988 | 0.5257 | 0.9662 |
| 0.1212 | 20.0 | 580 | 0.1634 | 0.4943 | 0.5309 | 0.5119 | 0.9692 |
| 0.1212 | 21.0 | 609 | 0.1673 | 0.5054 | 0.5802 | 0.5402 | 0.9684 |
| 0.1212 | 22.0 | 638 | 0.1677 | 0.5130 | 0.4877 | 0.5 | 0.9703 |
| 0.1212 | 23.0 | 667 | 0.1628 | 0.5687 | 0.5617 | 0.5652 | 0.9720 |
| 0.1212 | 24.0 | 696 | 0.1704 | 0.4865 | 0.5556 | 0.5187 | 0.9692 |
| 0.1212 | 25.0 | 725 | 0.1704 | 0.5660 | 0.5556 | 0.5607 | 0.9720 |
| 0.1212 | 26.0 | 754 | 0.1710 | 0.5644 | 0.5679 | 0.5662 | 0.9718 |
| 0.1212 | 27.0 | 783 | 0.1757 | 0.5380 | 0.5679 | 0.5526 | 0.9709 |
| 0.1212 | 28.0 | 812 | 0.1767 | 0.5112 | 0.5617 | 0.5353 | 0.9703 |
| 0.1212 | 29.0 | 841 | 0.1745 | 0.5588 | 0.5864 | 0.5723 | 0.9714 |
| 0.1212 | 30.0 | 870 | 0.1770 | 0.5515 | 0.5617 | 0.5566 | 0.9711 |
| 0.1212 | 31.0 | 899 | 0.1789 | 0.5417 | 0.5617 | 0.5515 | 0.9711 |
| 0.1212 | 32.0 | 928 | 0.1790 | 0.5417 | 0.5617 | 0.5515 | 0.9711 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
