readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: biobert-base-cased-v1.2-finetuned-ner-BioNLP13
    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. -->
  
  # biobert-base-cased-v1.2-finetuned-ner-BioNLP13
  
  This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2042
  - Precision: 0.9550
  - Recall: 0.9559
  - F1: 0.9555
  - Accuracy: 0.9552
  
  ## 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: 3e-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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.3114        | 1.0   | 692  | 0.1693          | 0.9453    | 0.9452 | 0.9453 | 0.9461   |
  | 0.1292        | 2.0   | 1384 | 0.1754          | 0.9492    | 0.9525 | 0.9509 | 0.9508   |
  | 0.0522        | 3.0   | 2076 | 0.1895          | 0.9529    | 0.9540 | 0.9534 | 0.9530   |
  | 0.032         | 4.0   | 2768 | 0.2042          | 0.9550    | 0.9559 | 0.9555 | 0.9552   |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  