swag-multiple-choice

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: 1.0120
• Accuracy: 0.7052

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	157	0.8148	0.6848
No log	2.0	314	0.8738	0.702
No log	3.0	471	1.0120	0.7052

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3