readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - mnli
  metrics:
  - accuracy
  model-index:
  - name: '42'
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: MNLI
        type: glue
        args: mnli
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8633723892002038
  ---
  
  <!-- 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. -->
  
  # 42
  
  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the MNLI dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8447
  - Accuracy: 0.8634
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - distributed_type: not_parallel
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.4274        | 1.0   | 12272 | 0.3892          | 0.8524   |
  | 0.2844        | 2.0   | 24544 | 0.4079          | 0.8565   |
  | 0.1589        | 3.0   | 36816 | 0.5033          | 0.8527   |
  | 0.0877        | 4.0   | 49088 | 0.6624          | 0.8576   |
  | 0.0426        | 5.0   | 61360 | 0.8447          | 0.8634   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu113
  - Datasets 2.7.1
  - Tokenizers 0.11.6
  