bert-base-cased-finetuned-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: 0.5719
• Accuracy: 0.8382
• F1: 0.8874

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: 32
• eval_batch_size: 32
• seed: 91
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	115	0.5228	0.7549	0.8471
No log	2.0	230	0.4315	0.8088	0.8673
No log	3.0	345	0.4212	0.8284	0.8785
No log	4.0	460	0.5462	0.8382	0.8889
0.3551	5.0	575	0.5719	0.8382	0.8874

Framework versions

• Transformers 4.28.0
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.13.3