readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncasedsexist_with_reddit_and_gab
    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-uncasedsexist_with_reddit_and_gab
  
  This model is a fine-tuned version of [Wiebke/distilbert-base-uncasedsexist_baseline](https://huggingface.co/Wiebke/distilbert-base-uncasedsexist_baseline) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3249
  - Accuracy: 0.8671
  - F1: 0.8641
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.0285        | 0.2   | 500  | 0.3733          | 0.87     | 0.8613 |
  | 0.0276        | 0.4   | 1000 | 0.3660          | 0.8386   | 0.8411 |
  | 0.0245        | 0.6   | 1500 | 0.3575          | 0.865    | 0.8564 |
  | 0.0239        | 0.81  | 2000 | 0.3249          | 0.8671   | 0.8641 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  