readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-uncased-misogyny-sexism-4tweets-2e-05-0.025
    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-05-0.025
  
  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: 0.9846
  - Accuracy: 0.6673
  - F1: 0.6700
  - Precision: 0.6172
  - Recall: 0.7326
  - Mae: 0.3327
  - Tn: 329
  - Fp: 209
  - Fn: 123
  - Tp: 337
  
  ## 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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.4767        | 1.0   | 1346 | 0.6746          | 0.6493   | 0.6801 | 0.5868    | 0.8087 | 0.3507 | 276 | 262 | 88  | 372 |
  | 0.3977        | 2.0   | 2692 | 0.6923          | 0.6633   | 0.6818 | 0.6040    | 0.7826 | 0.3367 | 302 | 236 | 100 | 360 |
  | 0.3366        | 3.0   | 4038 | 0.8630          | 0.6563   | 0.6779 | 0.5967    | 0.7848 | 0.3437 | 294 | 244 | 99  | 361 |
  | 0.2636        | 4.0   | 5384 | 0.9846          | 0.6673   | 0.6700 | 0.6172    | 0.7326 | 0.3327 | 329 | 209 | 123 | 337 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  