readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: paper_feedback_intent
    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. -->
  
  # paper_feedback_intent
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3621
  - Accuracy: 0.9302
  - Precision: 0.9307
  - Recall: 0.9302
  - F1: 0.9297
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.9174        | 1.0   | 11   | 0.7054          | 0.7907   | 0.7903    | 0.7907 | 0.7861 |
  | 0.6917        | 2.0   | 22   | 0.4665          | 0.8140   | 0.8134    | 0.8140 | 0.8118 |
  | 0.4276        | 3.0   | 33   | 0.3326          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
  | 0.2656        | 4.0   | 44   | 0.3286          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
  | 0.1611        | 5.0   | 55   | 0.3044          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  | 0.1025        | 6.0   | 66   | 0.3227          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  | 0.0799        | 7.0   | 77   | 0.3216          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  | 0.0761        | 8.0   | 88   | 0.3529          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  | 0.0479        | 9.0   | 99   | 0.3605          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  | 0.0358        | 10.0  | 110  | 0.3621          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  