readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - stereoset
  metrics:
  - accuracy
  model-index:
  - name: stereoset_trainer_roberta-base_finetuned
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: stereoset
        type: stereoset
        config: intersentence
        split: validation
        args: intersentence
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7535321821036107
  ---
  
  <!-- 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. -->
  
  # stereoset_trainer_roberta-base_finetuned
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the stereoset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5749
  - Accuracy: 0.7535
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.54  | 50   | 0.6919          | 0.5157   |
  | No log        | 1.08  | 100  | 0.6944          | 0.4843   |
  | No log        | 1.61  | 150  | 0.6275          | 0.6664   |
  | No log        | 2.15  | 200  | 0.5548          | 0.7355   |
  | No log        | 2.69  | 250  | 0.5613          | 0.7331   |
  | No log        | 3.23  | 300  | 0.6062          | 0.7331   |
  | No log        | 3.76  | 350  | 0.5455          | 0.7488   |
  | No log        | 4.3   | 400  | 0.6223          | 0.7488   |
  | No log        | 4.84  | 450  | 0.5749          | 0.7535   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  