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