readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-uncased-misogyny-sexism-4tweets-3e-05-0.01
    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-3e-05-0.01
  
  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: 1.1537
  - Accuracy: 0.6647
  - F1: 0.6788
  - Precision: 0.6076
  - Recall: 0.7691
  - Mae: 0.3353
  - Tn: 309
  - Fp: 228
  - Fn: 106
  - Tp: 353
  
  ## 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: 3e-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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.4449        | 1.0   | 1655 | 0.6853          | 0.5944   | 0.6799 | 0.5342    | 0.9346 | 0.4056 | 163 | 374 | 30  | 429 |
  | 0.3732        | 2.0   | 3310 | 0.7372          | 0.6416   | 0.6238 | 0.6041    | 0.6449 | 0.3584 | 343 | 194 | 163 | 296 |
  | 0.2962        | 3.0   | 4965 | 0.7860          | 0.6717   | 0.6714 | 0.6231    | 0.7277 | 0.3283 | 335 | 202 | 125 | 334 |
  | 0.2235        | 4.0   | 6620 | 1.1537          | 0.6647   | 0.6788 | 0.6076    | 0.7691 | 0.3353 | 309 | 228 | 106 | 353 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  