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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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model-index:
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- name: DisTEMIST_bsc_test1
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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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# DisTEMIST_bsc_test1
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This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1876
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- Diso Precision: 0.7529
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- Diso Recall: 0.7818
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- Diso F1: 0.7671
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- Diso Number: 1407
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- Overall Precision: 0.7529
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- Overall Recall: 0.7818
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- Overall F1: 0.7671
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- Overall Accuracy: 0.9744
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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: 4e-05
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- train_batch_size: 8
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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=2.6e-09
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 73
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
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| 0.1734 | 1.0 | 997 | 0.1084 | 0.7166 | 0.6397 | 0.6759 | 1407 | 0.7166 | 0.6397 | 0.6759 | 0.9656 |
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| 0.0589 | 2.0 | 1994 | 0.0896 | 0.7249 | 0.7662 | 0.7450 | 1407 | 0.7249 | 0.7662 | 0.7450 | 0.9725 |
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| 0.0288 | 3.0 | 2991 | 0.1162 | 0.7199 | 0.7910 | 0.7538 | 1407 | 0.7199 | 0.7910 | 0.7538 | 0.9725 |
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| 0.0163 | 4.0 | 3988 | 0.1267 | 0.7434 | 0.7783 | 0.7604 | 1407 | 0.7434 | 0.7783 | 0.7604 | 0.9731 |
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| 0.0096 | 5.0 | 4985 | 0.1362 | 0.7406 | 0.7832 | 0.7613 | 1407 | 0.7406 | 0.7832 | 0.7613 | 0.9748 |
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| 0.0047 | 6.0 | 5982 | 0.1573 | 0.7619 | 0.7711 | 0.7665 | 1407 | 0.7619 | 0.7711 | 0.7665 | 0.9745 |
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| 0.0041 | 7.0 | 6979 | 0.1773 | 0.7083 | 0.7939 | 0.7487 | 1407 | 0.7083 | 0.7939 | 0.7487 | 0.9691 |
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| 0.0019 | 8.0 | 7976 | 0.1682 | 0.7441 | 0.7811 | 0.7621 | 1407 | 0.7441 | 0.7811 | 0.7621 | 0.9741 |
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| 0.0012 | 9.0 | 8973 | 0.1823 | 0.7507 | 0.7811 | 0.7656 | 1407 | 0.7507 | 0.7811 | 0.7656 | 0.9743 |
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| 0.0004 | 10.0 | 9970 | 0.1876 | 0.7529 | 0.7818 | 0.7671 | 1407 | 0.7529 | 0.7818 | 0.7671 | 0.9744 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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