bert-base-banking77-pt2

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: 0.2989
• F1: 0.9295
• Accuracy: 0.9295

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: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_HF 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	F1	Accuracy
1.0279	1.0	626	0.7673	0.8552	0.8614
0.3534	2.0	1252	0.3743	0.9094	0.9104
0.1735	3.0	1878	0.2989	0.9295	0.9295

Framework versions

• Transformers 4.46.1
• Pytorch 2.5.1
• Datasets 3.0.2
• Tokenizers 0.20.1