bert-base-uncased-banking77

This model is a fine-tuned version of bert-base-uncased on an unknown dataset.

Model description

crafted a specialized model by fine-tuning BERT base uncased with the Banking77 dataset, enhancing its ability to understand and process banking-related information. This fine-tuned model is optimized for tasks within the financial domain, showcasing improved performance in tasks like sentiment analysis, intent detection, or document classification related to banking data.

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.35.2
• Pytorch 2.2.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1