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bert-base-uncased-mrpc

This model is a fine-tuned version of bert-base-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6978
  • Accuracy: 0.8603
  • F1: 0.9042
  • Combined Score: 0.8822

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.0+cu102
  • Datasets 1.14.0
  • Tokenizers 0.11.6
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Dataset used to train Intel/bert-base-uncased-mrpc

Evaluation results