readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: roberta-large-mnli-misogyny-sexism-4tweets-3e-05-0.05-singledt
    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-large-mnli-misogyny-sexism-4tweets-3e-05-0.05-singledt
  
  This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4013
  - Accuracy: 0.703
  - F1: 0.7003
  - Precision: 0.6535
  - Recall: 0.7543
  - Mae: 0.297
  - Tn: 356
  - Fp: 184
  - Fn: 113
  - Tp: 347
  
  ## 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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:---:|:---:|:---:|
  | 0.4806        | 1.0   | 250  | 0.6819          | 0.63     | 0.6838 | 0.5634    | 0.8696 | 0.37  | 230 | 310 | 60  | 400 |
  | 0.3544        | 2.0   | 500  | 0.6215          | 0.692    | 0.6864 | 0.6456    | 0.7326 | 0.308 | 355 | 185 | 123 | 337 |
  | 0.2422        | 3.0   | 750  | 0.8286          | 0.716    | 0.7221 | 0.6566    | 0.8022 | 0.284 | 347 | 193 | 91  | 369 |
  | 0.1615        | 4.0   | 1000 | 1.4013          | 0.703    | 0.7003 | 0.6535    | 0.7543 | 0.297 | 356 | 184 | 113 | 347 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  