readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - inspec
  metrics:
  - f1
  model-index:
  - name: bert-finetuned-inspec
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: inspec
        type: inspec
        args: extraction
      metrics:
      - name: F1
        type: f1
        value: 0.30353331752430635
  ---
  
  <!-- 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
  
  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: 0.3055
  - F1: 0.3035
  
  ## 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: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.3323        | 1.0   | 125  | 0.2799          | 0.1521 |
  | 0.2563        | 2.0   | 250  | 0.2638          | 0.2230 |
  | 0.2179        | 3.0   | 375  | 0.2689          | 0.2607 |
  | 0.1809        | 4.0   | 500  | 0.2807          | 0.3122 |
  | 0.1545        | 5.0   | 625  | 0.3055          | 0.3035 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  