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