finetuned-bert-mrpc

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

  • Loss: 0.4382
  • Accuracy: 0.8676
  • F1: 0.9085

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: 2e-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: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5454 1.0 230 0.4396 0.8309 0.8871
0.3387 2.0 460 0.3783 0.8529 0.8976
0.1956 3.0 690 0.4382 0.8676 0.9085

Framework versions

  • Transformers 4.10.0
  • Pytorch 1.9.0+cu102
  • Datasets 1.11.0
  • Tokenizers 0.10.3
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Evaluation results