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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: testlink |
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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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# testlink |
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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: 0.2031 |
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- Precision: 0.5065 |
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- Recall: 0.6359 |
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- F1: 0.5639 |
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- Accuracy: 0.9658 |
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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: 2.75e-05 |
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- train_batch_size: 16 |
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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: 30 |
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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 | 57 | 0.2133 | 0.0 | 0.0 | 0.0 | 0.9516 | |
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| No log | 2.0 | 114 | 0.1757 | 0.2 | 0.0163 | 0.0302 | 0.9550 | |
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| No log | 3.0 | 171 | 0.1591 | 0.2893 | 0.1902 | 0.2295 | 0.9535 | |
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| No log | 4.0 | 228 | 0.1386 | 0.3433 | 0.25 | 0.2893 | 0.9582 | |
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| No log | 5.0 | 285 | 0.1349 | 0.4345 | 0.3967 | 0.4148 | 0.9600 | |
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| No log | 6.0 | 342 | 0.1311 | 0.5352 | 0.4130 | 0.4663 | 0.9646 | |
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| No log | 7.0 | 399 | 0.1402 | 0.4264 | 0.5978 | 0.4977 | 0.9590 | |
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| No log | 8.0 | 456 | 0.1377 | 0.4858 | 0.5598 | 0.5202 | 0.9634 | |
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| 0.1282 | 9.0 | 513 | 0.1539 | 0.5226 | 0.4402 | 0.4779 | 0.9651 | |
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| 0.1282 | 10.0 | 570 | 0.1631 | 0.4597 | 0.6196 | 0.5278 | 0.9607 | |
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| 0.1282 | 11.0 | 627 | 0.1511 | 0.5333 | 0.4783 | 0.5043 | 0.9666 | |
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| 0.1282 | 12.0 | 684 | 0.1705 | 0.4690 | 0.5761 | 0.5171 | 0.9626 | |
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| 0.1282 | 13.0 | 741 | 0.1760 | 0.5138 | 0.5054 | 0.5096 | 0.9651 | |
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| 0.1282 | 14.0 | 798 | 0.1917 | 0.4296 | 0.6630 | 0.5214 | 0.9580 | |
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| 0.1282 | 15.0 | 855 | 0.1833 | 0.4563 | 0.625 | 0.5275 | 0.9619 | |
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| 0.1282 | 16.0 | 912 | 0.1887 | 0.4933 | 0.6033 | 0.5428 | 0.9638 | |
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| 0.1282 | 17.0 | 969 | 0.1723 | 0.5138 | 0.6087 | 0.5572 | 0.9659 | |
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| 0.0102 | 18.0 | 1026 | 0.1849 | 0.5022 | 0.6196 | 0.5547 | 0.9649 | |
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| 0.0102 | 19.0 | 1083 | 0.1773 | 0.5352 | 0.6196 | 0.5743 | 0.9676 | |
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| 0.0102 | 20.0 | 1140 | 0.1945 | 0.4957 | 0.6304 | 0.5550 | 0.9646 | |
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| 0.0102 | 21.0 | 1197 | 0.1967 | 0.4756 | 0.6359 | 0.5442 | 0.9634 | |
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| 0.0102 | 22.0 | 1254 | 0.1876 | 0.4978 | 0.6087 | 0.5477 | 0.9658 | |
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| 0.0102 | 23.0 | 1311 | 0.1935 | 0.4978 | 0.6087 | 0.5477 | 0.9656 | |
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| 0.0102 | 24.0 | 1368 | 0.1930 | 0.5256 | 0.6141 | 0.5664 | 0.9671 | |
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| 0.0102 | 25.0 | 1425 | 0.1945 | 0.5110 | 0.6304 | 0.5645 | 0.9661 | |
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| 0.0102 | 26.0 | 1482 | 0.1955 | 0.5283 | 0.6087 | 0.5657 | 0.9673 | |
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| 0.0023 | 27.0 | 1539 | 0.2017 | 0.5043 | 0.6359 | 0.5625 | 0.9654 | |
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| 0.0023 | 28.0 | 1596 | 0.2010 | 0.5088 | 0.6304 | 0.5631 | 0.9659 | |
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| 0.0023 | 29.0 | 1653 | 0.2019 | 0.5088 | 0.6304 | 0.5631 | 0.9659 | |
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| 0.0023 | 30.0 | 1710 | 0.2031 | 0.5065 | 0.6359 | 0.5639 | 0.9658 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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