readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: biobertpt-all-finetuned-ner
    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. -->
  
  # biobertpt-all-finetuned-ner
  
  This model is a fine-tuned version of [pucpr/biobertpt-all](https://huggingface.co/pucpr/biobertpt-all) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3721
  - Precision: 0.0179
  - Recall: 0.0149
  - F1: 0.0163
  - Accuracy: 0.6790
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 1    | 2.7864          | 0.0091    | 0.0448 | 0.0152 | 0.3339   |
  | No log        | 2.0   | 2    | 2.5096          | 0.0097    | 0.0149 | 0.0118 | 0.6292   |
  | No log        | 3.0   | 3    | 2.3721          | 0.0179    | 0.0149 | 0.0163 | 0.6790   |
  
  
  ### Framework versions
  
  - Transformers 4.12.0.dev0
  - Pytorch 1.9.1+cu102
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  