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: 0.4917
  • Accuracy: 0.8235
  • F1: 0.8792

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
0.5382 1.0 230 0.4008 0.8456 0.8893
0.3208 2.0 460 0.4182 0.8309 0.8844
0.1587 3.0 690 0.4917 0.8235 0.8792

Framework versions

  • Transformers 4.9.0.dev0
  • Pytorch 1.8.1+cu111
  • Datasets 1.8.1.dev0
  • Tokenizers 0.10.1
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