readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: levit-192_finetuned_on_unlabelled_IA_with_snorkel_labels
    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. -->
  
  # levit-192_finetuned_on_unlabelled_IA_with_snorkel_labels
  
  This model is a fine-tuned version of [facebook/levit-192](https://huggingface.co/facebook/levit-192) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: nan
  - Precision: 0.9836
  - Recall: 0.9822
  - F1: 0.9829
  - Accuracy: 0.9873
  
  ## 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: 128
  - eval_batch_size: 256
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 253  | nan             | 0.9743    | 0.9791 | 0.9766 | 0.9826   |
  | 0.0557        | 2.0   | 506  | nan             | 0.9829    | 0.9801 | 0.9815 | 0.9863   |
  | 0.0557        | 3.0   | 759  | nan             | 0.9836    | 0.9822 | 0.9829 | 0.9873   |
  | 0.0543        | 4.0   | 1012 | nan             | 0.9839    | 0.9775 | 0.9807 | 0.9858   |
  | 0.0543        | 5.0   | 1265 | nan             | 0.9616    | 0.9727 | 0.9670 | 0.9752   |
  | 0.0457        | 6.0   | 1518 | nan             | 0.9563    | 0.9699 | 0.9629 | 0.9720   |
  | 0.0457        | 7.0   | 1771 | nan             | 0.9822    | 0.9808 | 0.9815 | 0.9863   |
  | 0.0418        | 8.0   | 2024 | nan             | 0.9735    | 0.9769 | 0.9752 | 0.9815   |
  | 0.0418        | 9.0   | 2277 | nan             | 0.9832    | 0.9811 | 0.9822 | 0.9868   |
  | 0.0396        | 10.0  | 2530 | nan             | 0.9843    | 0.9815 | 0.9829 | 0.9873   |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  