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levit-192_finetuned_on_unlabelled_IA_with_snorkel_labels

This model is a fine-tuned version of 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
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