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--- |
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language: |
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- es |
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license: cc-by-nc-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- jpherrerap/competencia2 |
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model-index: |
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- name: ner-roberta-es-clinical-trials-ner |
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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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# ner-roberta-es-clinical-trials-ner |
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This model is a fine-tuned version of [lcampillos/roberta-es-clinical-trials-ner](https://huggingface.co/lcampillos/roberta-es-clinical-trials-ner) on the jpherrerap/competencia2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2661 |
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- Body Part Precision: 0.7124 |
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- Body Part Recall: 0.8173 |
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- Body Part F1: 0.7612 |
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- Body Part Number: 197 |
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- Disease Precision: 0.7712 |
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- Disease Recall: 0.7697 |
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- Disease F1: 0.7704 |
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- Disease Number: 521 |
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- Family Member Precision: 0.8462 |
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- Family Member Recall: 0.8462 |
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- Family Member F1: 0.8462 |
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- Family Member Number: 13 |
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- Medication Precision: 0.8378 |
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- Medication Recall: 0.8378 |
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- Medication F1: 0.8378 |
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- Medication Number: 37 |
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- Procedure Precision: 0.6510 |
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- Procedure Recall: 0.7239 |
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- Procedure F1: 0.6855 |
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- Procedure Number: 134 |
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- Overall Precision: 0.7418 |
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- Overall Recall: 0.7772 |
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- Overall F1: 0.7591 |
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- Overall Accuracy: 0.9238 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 13 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Body Part Precision | Body Part Recall | Body Part F1 | Body Part Number | Disease Precision | Disease Recall | Disease F1 | Disease Number | Family Member Precision | Family Member Recall | Family Member F1 | Family Member Number | Medication Precision | Medication Recall | Medication F1 | Medication Number | Procedure Precision | Procedure Recall | Procedure F1 | Procedure Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.3329 | 1.0 | 502 | 0.2561 | 0.6830 | 0.7766 | 0.7268 | 197 | 0.7718 | 0.7658 | 0.7688 | 521 | 0.9231 | 0.9231 | 0.9231 | 13 | 0.75 | 0.8108 | 0.7792 | 37 | 0.6218 | 0.7239 | 0.6690 | 134 | 0.7274 | 0.7661 | 0.7462 | 0.9219 | |
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| 0.1699 | 2.0 | 1004 | 0.2661 | 0.7124 | 0.8173 | 0.7612 | 197 | 0.7712 | 0.7697 | 0.7704 | 521 | 0.8462 | 0.8462 | 0.8462 | 13 | 0.8378 | 0.8378 | 0.8378 | 37 | 0.6510 | 0.7239 | 0.6855 | 134 | 0.7418 | 0.7772 | 0.7591 | 0.9238 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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