finetuned-bert

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: 0.3916
• Accuracy: 0.875
• F1: 0.9125

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
0.581	1.0	230	0.4086	0.8260	0.8711
0.366	2.0	460	0.3758	0.8480	0.8963
0.2328	3.0	690	0.3916	0.875	0.9125

Framework versions

• Transformers 4.9.0.dev0
• Pytorch 1.8.1+cu111
• Datasets 1.8.1.dev0
• Tokenizers 0.10.1