readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-uncased-misogyny-sexism-4tweets-2e-05-0.05
    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. -->
  
  # distilbert-base-uncased-misogyny-sexism-4tweets-2e-05-0.05
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0008
  - Accuracy: 0.6683
  - F1: 0.6720
  - Precision: 0.6175
  - Recall: 0.7370
  - Mae: 0.3317
  - Tn: 328
  - Fp: 210
  - Fn: 121
  - Tp: 339
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    | Tn  | Fp  | Fn  | Tp  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.4786        | 1.0   | 1346 | 0.6820          | 0.6403   | 0.6597 | 0.5849    | 0.7565 | 0.3597 | 291 | 247 | 112 | 348 |
  | 0.3952        | 2.0   | 2692 | 0.6787          | 0.6713   | 0.6906 | 0.61      | 0.7957 | 0.3287 | 304 | 234 | 94  | 366 |
  | 0.3326        | 3.0   | 4038 | 0.8870          | 0.6563   | 0.6821 | 0.5945    | 0.8    | 0.3437 | 287 | 251 | 92  | 368 |
  | 0.2617        | 4.0   | 5384 | 1.0008          | 0.6683   | 0.6720 | 0.6175    | 0.7370 | 0.3317 | 328 | 210 | 121 | 339 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  