readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: twitter-roberta-base-offensive-finetuned
    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. -->
  
  # twitter-roberta-base-offensive-finetuned
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-offensive](https://huggingface.co/cardiffnlp/twitter-roberta-base-offensive) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6574
  - Accuracy: 0.8467
  - F1: 0.8798
  
  ## 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: 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.4202        | 1.0   | 1548 | 0.4947          | 0.8130   | 0.8543 |
  | 0.3487        | 2.0   | 3096 | 0.4970          | 0.8351   | 0.8739 |
  | 0.2596        | 3.0   | 4644 | 0.6574          | 0.8467   | 0.8798 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  