testlink-class-3
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: 0.1443
- Precision: 0.5833
- Recall: 0.6550
- F1: 0.6171
- Accuracy: 0.9730
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: 7.5e-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: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 29 | 0.2830 | 0.0 | 0.0 | 0.0 | 0.9440 |
No log | 2.0 | 58 | 0.2789 | 0.0 | 0.0 | 0.0 | 0.9440 |
No log | 3.0 | 87 | 0.2388 | 0.0 | 0.0 | 0.0 | 0.9440 |
No log | 4.0 | 116 | 0.2080 | 0.0 | 0.0 | 0.0 | 0.9440 |
No log | 5.0 | 145 | 0.2335 | 0.0167 | 0.0058 | 0.0087 | 0.9322 |
No log | 6.0 | 174 | 0.1889 | 0.0 | 0.0 | 0.0 | 0.9440 |
No log | 7.0 | 203 | 0.1553 | 0.3469 | 0.1988 | 0.2528 | 0.9506 |
No log | 8.0 | 232 | 0.1491 | 0.5 | 0.2339 | 0.3187 | 0.9576 |
No log | 9.0 | 261 | 0.1604 | 0.4872 | 0.2222 | 0.3052 | 0.9605 |
No log | 10.0 | 290 | 0.1347 | 0.4733 | 0.3626 | 0.4106 | 0.9587 |
No log | 11.0 | 319 | 0.1391 | 0.5165 | 0.2749 | 0.3588 | 0.9605 |
No log | 12.0 | 348 | 0.1392 | 0.4848 | 0.3743 | 0.4224 | 0.9633 |
No log | 13.0 | 377 | 0.1306 | 0.4706 | 0.3743 | 0.4169 | 0.9636 |
No log | 14.0 | 406 | 0.1382 | 0.4774 | 0.4327 | 0.4540 | 0.9642 |
No log | 15.0 | 435 | 0.1368 | 0.4734 | 0.5205 | 0.4958 | 0.9655 |
No log | 16.0 | 464 | 0.1316 | 0.5052 | 0.5731 | 0.5370 | 0.9666 |
No log | 17.0 | 493 | 0.1333 | 0.4852 | 0.6725 | 0.5637 | 0.9660 |
0.1607 | 18.0 | 522 | 0.1379 | 0.56 | 0.5731 | 0.5665 | 0.9695 |
0.1607 | 19.0 | 551 | 0.1534 | 0.5941 | 0.5906 | 0.5924 | 0.9706 |
0.1607 | 20.0 | 580 | 0.1294 | 0.5606 | 0.6491 | 0.6016 | 0.9712 |
0.1607 | 21.0 | 609 | 0.1403 | 0.5231 | 0.6608 | 0.5840 | 0.9704 |
0.1607 | 22.0 | 638 | 0.1429 | 0.6044 | 0.6433 | 0.6232 | 0.9719 |
0.1607 | 23.0 | 667 | 0.1411 | 0.5825 | 0.6608 | 0.6192 | 0.9719 |
0.1607 | 24.0 | 696 | 0.1339 | 0.5631 | 0.6784 | 0.6154 | 0.9708 |
0.1607 | 25.0 | 725 | 0.1345 | 0.5825 | 0.6608 | 0.6192 | 0.9721 |
0.1607 | 26.0 | 754 | 0.1464 | 0.5833 | 0.6550 | 0.6171 | 0.9717 |
0.1607 | 27.0 | 783 | 0.1403 | 0.5672 | 0.6667 | 0.6129 | 0.9715 |
0.1607 | 28.0 | 812 | 0.1445 | 0.5934 | 0.6316 | 0.6119 | 0.9725 |
0.1607 | 29.0 | 841 | 0.1433 | 0.5588 | 0.6667 | 0.608 | 0.9715 |
0.1607 | 30.0 | 870 | 0.1443 | 0.5833 | 0.6550 | 0.6171 | 0.9730 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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