BERT-finetuned-case-hold

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

• Loss: 0.7475
• Accuracy: 0.7367

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: 32
• eval_batch_size: 32
• 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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7716	1.0	1407	0.6712	0.7321
0.6004	2.0	2814	0.6744	0.7364
0.485	3.0	4221	0.7475	0.7367

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu118
• Datasets 3.2.0
• Tokenizers 0.21.0