readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: roberta-offensive-lm-tapt-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. -->
  
  # roberta-offensive-lm-tapt-finetuned
  
  This model is a fine-tuned version of [k4black/roberta-offensive-lm-tapt](https://huggingface.co/k4black/roberta-offensive-lm-tapt) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4692
  - F1: 0.7744
  
  ## 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: 12
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.6149        | 0.1   | 100  | 0.6323          | 0.3932 |
  | 0.5713        | 0.2   | 200  | 0.6223          | 0.5491 |
  | 0.5529        | 0.29  | 300  | 0.5739          | 0.6120 |
  | 0.5174        | 0.39  | 400  | 0.4812          | 0.7287 |
  | 0.5044        | 0.49  | 500  | 0.4667          | 0.7595 |
  | 0.5022        | 0.59  | 600  | 0.4540          | 0.7648 |
  | 0.4855        | 0.69  | 700  | 0.4523          | 0.7933 |
  | 0.465         | 0.78  | 800  | 0.4479          | 0.7727 |
  | 0.4591        | 0.88  | 900  | 0.4478          | 0.7914 |
  | 0.4702        | 0.98  | 1000 | 0.6035          | 0.7397 |
  | 0.4448        | 1.08  | 1100 | 0.4996          | 0.7535 |
  | 0.4476        | 1.18  | 1200 | 0.4692          | 0.7744 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  