bert-base-uncased-finetuned-swag

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

• Loss: 0.8480
• Accuracy: 0.8005

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	147	0.5757	0.8485
No log	2.0	294	1.1518	0.7637
No log	3.0	441	0.8480	0.8005

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.1+cpu
• Datasets 2.20.0
• Tokenizers 0.19.1