readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: bert-base-spanish-wwm-uncased-finetuned-clinical
    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. -->
  
  # bert-base-spanish-wwm-uncased-finetuned-clinical
  
  This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7962
  - F1: 0.1081
  
  ## 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: 5e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 80
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | F1     |
  |:-------------:|:-----:|:------:|:---------------:|:------:|
  | 1.1202        | 1.0   | 2007   | 1.0018          | 0.0062 |
  | 1.0153        | 2.0   | 4014   | 0.9376          | 0.0166 |
  | 0.9779        | 3.0   | 6021   | 0.9026          | 0.0342 |
  | 0.9598        | 4.0   | 8028   | 0.8879          | 0.0337 |
  | 0.9454        | 5.0   | 10035  | 0.8699          | 0.0598 |
  | 0.9334        | 6.0   | 12042  | 0.8546          | 0.0682 |
  | 0.9263        | 7.0   | 14049  | 0.8533          | 0.0551 |
  | 0.9279        | 8.0   | 16056  | 0.8538          | 0.0715 |
  | 0.9184        | 9.0   | 18063  | 0.8512          | 0.0652 |
  | 0.9151        | 10.0  | 20070  | 0.8313          | 0.0789 |
  | 0.9092        | 11.0  | 22077  | 0.8299          | 0.0838 |
  | 0.9083        | 12.0  | 24084  | 0.8331          | 0.0718 |
  | 0.9057        | 13.0  | 26091  | 0.8319          | 0.0719 |
  | 0.9018        | 14.0  | 28098  | 0.8133          | 0.0969 |
  | 0.9068        | 15.0  | 30105  | 0.8234          | 0.0816 |
  | 0.9034        | 16.0  | 32112  | 0.8151          | 0.0899 |
  | 0.9008        | 17.0  | 34119  | 0.8145          | 0.0967 |
  | 0.8977        | 18.0  | 36126  | 0.8168          | 0.0891 |
  | 0.898         | 19.0  | 38133  | 0.8167          | 0.0818 |
  | 0.8956        | 20.0  | 40140  | 0.8076          | 0.1030 |
  | 0.8983        | 21.0  | 42147  | 0.8129          | 0.0867 |
  | 0.896         | 22.0  | 44154  | 0.8118          | 0.0892 |
  | 0.8962        | 23.0  | 46161  | 0.8066          | 0.1017 |
  | 0.8917        | 24.0  | 48168  | 0.8154          | 0.0908 |
  | 0.8923        | 25.0  | 50175  | 0.8154          | 0.0897 |
  | 0.8976        | 26.0  | 52182  | 0.8089          | 0.0910 |
  | 0.8926        | 27.0  | 54189  | 0.8069          | 0.0947 |
  | 0.8911        | 28.0  | 56196  | 0.8170          | 0.0882 |
  | 0.8901        | 29.0  | 58203  | 0.7991          | 0.1112 |
  | 0.8934        | 30.0  | 60210  | 0.7996          | 0.1112 |
  | 0.8903        | 31.0  | 62217  | 0.8049          | 0.0950 |
  | 0.8924        | 32.0  | 64224  | 0.8116          | 0.0951 |
  | 0.8887        | 33.0  | 66231  | 0.7982          | 0.1075 |
  | 0.8922        | 34.0  | 68238  | 0.8013          | 0.1025 |
  | 0.8871        | 35.0  | 70245  | 0.8064          | 0.0979 |
  | 0.8913        | 36.0  | 72252  | 0.8108          | 0.0909 |
  | 0.8924        | 37.0  | 74259  | 0.8081          | 0.0889 |
  | 0.8848        | 38.0  | 76266  | 0.7923          | 0.1228 |
  | 0.8892        | 39.0  | 78273  | 0.8025          | 0.0959 |
  | 0.8886        | 40.0  | 80280  | 0.7954          | 0.1148 |
  | 0.8938        | 41.0  | 82287  | 0.8017          | 0.1058 |
  | 0.8897        | 42.0  | 84294  | 0.7946          | 0.1146 |
  | 0.8906        | 43.0  | 86301  | 0.7983          | 0.1102 |
  | 0.889         | 44.0  | 88308  | 0.8068          | 0.0950 |
  | 0.8872        | 45.0  | 90315  | 0.7999          | 0.1089 |
  | 0.8902        | 46.0  | 92322  | 0.7992          | 0.0999 |
  | 0.8912        | 47.0  | 94329  | 0.7981          | 0.1048 |
  | 0.886         | 48.0  | 96336  | 0.8024          | 0.0991 |
  | 0.8848        | 49.0  | 98343  | 0.8026          | 0.0984 |
  | 0.8866        | 50.0  | 100350 | 0.7965          | 0.1135 |
  | 0.8848        | 51.0  | 102357 | 0.8054          | 0.0926 |
  | 0.8863        | 52.0  | 104364 | 0.8068          | 0.0917 |
  | 0.8866        | 53.0  | 106371 | 0.7993          | 0.0964 |
  | 0.8823        | 54.0  | 108378 | 0.7929          | 0.1126 |
  | 0.8911        | 55.0  | 110385 | 0.7938          | 0.1132 |
  | 0.8911        | 56.0  | 112392 | 0.7932          | 0.1144 |
  | 0.8866        | 57.0  | 114399 | 0.8018          | 0.0957 |
  | 0.8841        | 58.0  | 116406 | 0.7976          | 0.1015 |
  | 0.8874        | 59.0  | 118413 | 0.8035          | 0.0966 |
  | 0.887         | 60.0  | 120420 | 0.7954          | 0.1112 |
  | 0.888         | 61.0  | 122427 | 0.7927          