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bert-base-uncased-finetuned-semeval2020-task4b

This model is a fine-tuned version of bert-base-uncased on the ComVE dataset which was part of SemEval 2020 Task 4. It achieves the following results on the test set:

  • Loss: 0.6760
  • Accuracy: 0.8760

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5016 1.0 688 0.3502 0.8600
0.2528 2.0 1376 0.5769 0.8620
0.0598 3.0 2064 0.6720 0.8700
0.0197 4.0 2752 0.6760 0.8760

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Evaluation results

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