readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_3_binary_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. -->
  
  # Bio_ClinicalBERT_fold_3_binary_v1
  
  This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8860
  - F1: 0.8051
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 289  | 0.4493          | 0.7916 |
  | 0.3975        | 2.0   | 578  | 0.4608          | 0.7909 |
  | 0.3975        | 3.0   | 867  | 0.8364          | 0.7726 |
  | 0.1885        | 4.0   | 1156 | 1.0380          | 0.7902 |
  | 0.1885        | 5.0   | 1445 | 1.1612          | 0.7921 |
  | 0.0692        | 6.0   | 1734 | 1.3894          | 0.7761 |
  | 0.0295        | 7.0   | 2023 | 1.3730          | 0.7864 |
  | 0.0295        | 8.0   | 2312 | 1.4131          | 0.7939 |
  | 0.0161        | 9.0   | 2601 | 1.5538          | 0.7929 |
  | 0.0161        | 10.0  | 2890 | 1.6417          | 0.7931 |
  | 0.006         | 11.0  | 3179 | 1.5745          | 0.7974 |
  | 0.006         | 12.0  | 3468 | 1.7212          | 0.7908 |
  | 0.0132        | 13.0  | 3757 | 1.7349          | 0.7945 |
  | 0.0062        | 14.0  | 4046 | 1.7593          | 0.7908 |
  | 0.0062        | 15.0  | 4335 | 1.7420          | 0.8035 |
  | 0.0073        | 16.0  | 4624 | 1.7620          | 0.8007 |
  | 0.0073        | 17.0  | 4913 | 1.8286          | 0.7908 |
  | 0.0033        | 18.0  | 5202 | 1.7863          | 0.7977 |
  | 0.0033        | 19.0  | 5491 | 1.9275          | 0.7919 |
  | 0.0035        | 20.0  | 5780 | 1.8481          | 0.8042 |
  | 0.0035        | 21.0  | 6069 | 1.9465          | 0.8012 |
  | 0.0035        | 22.0  | 6358 | 1.8177          | 0.8044 |
  | 0.005         | 23.0  | 6647 | 1.8615          | 0.8030 |
  | 0.005         | 24.0  | 6936 | 1.8427          | 0.8054 |
  | 0.0011        | 25.0  | 7225 | 1.8860          | 0.8051 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  