readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wl-disease
  model-index:
  - name: WL_DISEASE_NER_v1
    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. -->
  
  # WL_DISEASE_NER_v1
  
  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 wl-disease dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1489
  - Diso Precision: 0.7908
  - Diso Recall: 0.8397
  - Diso F1: 0.8145
  - Diso Number: 1765
  - Overall Precision: 0.7908
  - Overall Recall: 0.8397
  - Overall F1: 0.8145
  - Overall Accuracy: 0.9631
  
  ## 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: 2e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
  | 0.1199        | 1.0   | 1714 | 0.1187          | 0.7739         | 0.7972      | 0.7854  | 1765        | 0.7739            | 0.7972         | 0.7854     | 0.9610           |
  | 0.0916        | 2.0   | 3428 | 0.1237          | 0.7748         | 0.8266      | 0.7999  | 1765        | 0.7748            | 0.8266         | 0.7999     | 0.9620           |
  | 0.0625        | 3.0   | 5142 | 0.1343          | 0.7900         | 0.8289      | 0.8090  | 1765        | 0.7900            | 0.8289         | 0.8090     | 0.9630           |
  | 0.0485        | 4.0   | 6856 | 0.1489          | 0.7908         | 0.8397      | 0.8145  | 1765        | 0.7908            | 0.8397         | 0.8145     | 0.9631           |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  