readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: distilbert-base-cased-finetuned-chunk
    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. -->
  
  # distilbert-base-cased-finetuned-chunk
  
  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5180
  - Precision: 0.8615
  - Recall: 0.9088
  - F1: 0.8845
  - Accuracy: 0.8239
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.8391        | 1.0   | 878  | 0.5871          | 0.8453    | 0.9035 | 0.8734 | 0.8054   |
  | 0.6134        | 2.0   | 1756 | 0.5447          | 0.8555    | 0.8983 | 0.8764 | 0.8142   |
  | 0.5565        | 3.0   | 2634 | 0.5180          | 0.8615    | 0.9088 | 0.8845 | 0.8239   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.9.1
  - Tokenizers 0.10.3
  