readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - boolq
  metrics:
  - accuracy
  model_index:
  - name: distilbert-base-uncased-boolq
    results:
    - task:
        name: Question Answering
        type: question-answering
      dataset:
        name: boolq
        type: boolq
        args: default
      metric:
        name: Accuracy
        type: accuracy
        value: 0.7314984709480122
  ---
  
  <!-- 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-boolq
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the boolq dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2071
  - Accuracy: 0.7315
  
  ## 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: 16
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6506        | 1.0   | 531  | 0.6075          | 0.6681   |
  | 0.575         | 2.0   | 1062 | 0.5816          | 0.6978   |
  | 0.4397        | 3.0   | 1593 | 0.6137          | 0.7253   |
  | 0.2524        | 4.0   | 2124 | 0.8124          | 0.7466   |
  | 0.126         | 5.0   | 2655 | 1.1437          | 0.7370   |
  
  
  ### Framework versions
  
  - Transformers 4.8.2
  - Pytorch 1.8.1+cu111
  - Datasets 1.8.0
  - Tokenizers 0.10.3
  