readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: roberta-base-finetuned-removed-0530
    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-base-finetuned-removed-0530
  
  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: 0.7910
  - Accuracy: 0.9082
  - F1: 0.9084
  
  ## 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
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 3180  | 0.6250          | 0.8277   | 0.8250 |
  | No log        | 2.0   | 6360  | 0.4578          | 0.8689   | 0.8684 |
  | No log        | 3.0   | 9540  | 0.4834          | 0.8792   | 0.8797 |
  | No log        | 4.0   | 12720 | 0.6377          | 0.8899   | 0.8902 |
  | No log        | 5.0   | 15900 | 0.6498          | 0.8921   | 0.8921 |
  | No log        | 6.0   | 19080 | 0.6628          | 0.8931   | 0.8928 |
  | No log        | 7.0   | 22260 | 0.7380          | 0.8925   | 0.8918 |
  | 0.2877        | 8.0   | 25440 | 0.7313          | 0.8975   | 0.8974 |
  | 0.2877        | 9.0   | 28620 | 0.7593          | 0.9025   | 0.9026 |
  | 0.2877        | 10.0  | 31800 | 0.7910          | 0.9082   | 0.9084 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.0
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  