bert-base-uncased-finetuned-swag-e1-b16-l5e5

This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:

• Loss: 0.5202
• Accuracy: 0.7997

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: 5e-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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.701	1.0	4597	0.5202	0.7997

Framework versions

• Transformers 4.12.2
• Pytorch 1.9.1
• Datasets 1.12.1
• Tokenizers 0.10.3