bert-base-uncased-finetuned-swag

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5166
• Accuracy: 0.8379

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	374	0.4023	0.8294
0.4482	2.0	748	0.4094	0.8389
0.2431	3.0	1122	0.5166	0.8379

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cpu
• Datasets 2.19.1
• Tokenizers 0.19.1