bert-finetuned-health-fact

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

• Loss: 0.8504
• Accuracy: 0.6680

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8064	1.0	1226	0.7489	0.6779
0.6966	2.0	2452	0.7398	0.6771
0.5055	3.0	3678	0.8504	0.6680

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.0
• Tokenizers 0.21.0