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