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: 0.4588
• Accuracy: 0.8382
• F1: 0.8878

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
0.579	1.0	230	0.4858	0.7745	0.8521
0.4163	2.0	460	0.4477	0.8088	0.8721
0.2533	3.0	690	0.4588	0.8382	0.8878

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3