readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: roberta_large-chunking_0728_v2
    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. -->
  
  # roberta_large-chunking_0728_v2
  
  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5270
  - Precision: 0.6228
  - Recall: 0.6467
  - F1: 0.6345
  - Accuracy: 0.8153
  
  ## 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: 1e-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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 125  | 0.5667          | 0.4931    | 0.5415 | 0.5162 | 0.7397   |
  | No log        | 2.0   | 250  | 0.4839          | 0.5484    | 0.5894 | 0.5682 | 0.7874   |
  | No log        | 3.0   | 375  | 0.4822          | 0.5997    | 0.6341 | 0.6164 | 0.8085   |
  | 0.4673        | 4.0   | 500  | 0.5117          | 0.6023    | 0.6373 | 0.6193 | 0.8120   |
  | 0.4673        | 5.0   | 625  | 0.5270          | 0.6228    | 0.6467 | 0.6345 | 0.8153   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  