readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - inspec
  metrics:
  - f1
  - precision
  - recall
  model-index:
  - name: bert-finetuned-inspec-3-epochs
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: inspec
        type: inspec
        args: extraction
      metrics:
      - name: F1
        type: f1
        value: 0.28328008519701814
      - name: Precision
        type: precision
        value: 0.26594090202177295
      - name: Recall
        type: recall
        value: 0.3030379746835443
  ---
  
  <!-- 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-finetuned-inspec-3-epochs
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the inspec dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2728
  - F1: 0.2833
  - Precision: 0.2659
  - Recall: 0.3030
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 0
  - 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 | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
  | 0.3338        | 1.0   | 125  | 0.2837          | 0.1401 | 0.1510    | 0.1306 |
  | 0.2575        | 2.0   | 250  | 0.2658          | 0.2183 | 0.2519    | 0.1927 |
  | 0.2259        | 3.0   | 375  | 0.2728          | 0.2833 | 0.2659    | 0.3030 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  