fintuned-bert-disfluency

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

• Train Loss: 0.0814
• Train Sparse Categorical Accuracy: 0.9795
• Validation Loss: 0.0816
• Validation Sparse Categorical Accuracy: 0.9795
• Epoch: 2

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:

• optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Validation Loss	Validation Sparse Categorical Accuracy	Epoch
0.1105	0.9694	0.0821	0.9800	0
0.0942	0.9759	0.0987	0.9765	1
0.0814	0.9795	0.0816	0.9795	2

Framework versions

• Transformers 4.21.3
• TensorFlow 2.8.2
• Datasets 2.4.0
• Tokenizers 0.12.1