readme: ---
  license: apache-2.0
  
  widget:
  - text: "Ayer dormí la siesta durante 3 horas"
  - text: "Recuerda tu cita con el médico el lunes a las 8 de la tarde"
  - text: "Recuerda tomar la medicación cada noche"
  
  tags:
  - LABEL-0 = NONE  
  - LABEL-1 = B-DATE  
  - LABEL-2 = I-DATE
  - LABEL-3 = B-TIME
  - LABEL-4 = I-TIME
  - LABEL-5 = B-DURATION
  - LABEL-6 = I-DURATION
  - LABEL-7 = B-SET  
  - LABEL-8 = I-SET
  
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: Bio-RoBERTime
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # Bio-RoBERTime
  
  This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0177
  - Precision: 0.8121
  - Recall: 0.8854
  - F1: 0.8472
  - Accuracy: 0.9919
  
  ## 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: 8e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 72
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 24
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0433        | 1.0   | 12   | 0.0443          | 0.4948    | 0.5    | 0.4974 | 0.9800   |
  | 0.0234        | 2.0   | 24   | 0.0221          | 0.4082    | 0.7257 | 0.5225 | 0.9732   |
  | 0.0055        | 3.0   | 36   | 0.0159          | 0.4768    | 0.7847 | 0.5932 | 0.9797   |
  | 0.0089        | 4.0   | 48   | 0.0153          | 0.5317    | 0.8160 | 0.6438 | 0.9813   |
  | 0.0033        | 5.0   | 60   | 0.0131          | 0.7229    | 0.8333 | 0.7742 | 0.9896   |
  | 0.008         | 6.0   | 72   | 0.0129          | 0.6649    | 0.8681 | 0.7530 | 0.9885   |
  | 0.0063        | 7.0   | 84   | 0.0146          | 0.7523    | 0.8542 | 0.8    | 0.9904   |
  | 0.0086        | 8.0   | 96   | 0.0150          | 0.7470    | 0.8715 | 0.8045 | 0.9906   |
  | 0.0009        | 9.0   | 108  | 0.0139          | 0.7658    | 0.8854 | 0.8213 | 0.9910   |
  | 0.0031        | 10.0  | 120  | 0.0159          | 0.8031    | 0.8924 | 0.8454 | 0.9919   |
  | 0.0011        | 11.0  | 132  | 0.0158          | 0.7649    | 0.8924 | 0.8237 | 0.9909   |
  | 0.0006        | 12.0  | 144  | 0.0153          | 0.7398    | 0.8785 | 0.8032 | 0.9902   |
  | 0.0013        | 13.0  | 156  | 0.0157          | 0.7815    | 0.8819 | 0.8287 | 0.9910   |
  | 0.0008        | 14.0  | 168  | 0.0154          | 0.7822    | 0.8854 | 0.8306 | 0.9908   |
  | 0.0008        | 15.0  | 180  | 0.0164          | 0.7778    | 0.875  | 0.8235 | 0.9910   |
  | 0.0007        | 16.0  | 192  | 0.0168          | 0.7864    | 0.8819 | 0.8314 | 0.9912   |
  | 0.0018        | 17.0  | 204  | 0.0173          | 0.7870    | 0.8854 | 0.8333 | 0.9912   |
  | 0.0006        | 18.0  | 216  | 0.0178          | 0.7730    | 0.875  | 0.8208 | 0.9914   |
  | 0.0012        | 19.0  | 228  | 0.0171          | 0.8013    | 0.8819 | 0.8397 | 0.9916   |
  | 0.0006        | 20.0  | 240  | 0.0181          | 0.8137    | 0.8646 | 0.8384 | 0.9916   |
  | 0.0007        | 21.0  | 252  | 0.0186          | 0.8137    | 0.8646 | 0.8384 | 0.9918   |
  | 0.0012        | 22.0  | 264  | 0.0188          | 0.8137    | 0.8646 | 0.8384 | 0.9919   |
  | 0.0006        | 23.0  | 276  | 0.0178          | 0.8121    | 0.8854 | 0.8472 | 0.9919   |
  | 0.0009        | 24.0  | 288  | 0.0177          | 0.8121    | 0.8854 | 0.8472 | 0.9919   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  