bert-model-english

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

• Train Loss: 0.1408
• Train Sparse Categorical Accuracy: 0.9512
• Validation Loss: nan
• Validation Sparse Categorical Accuracy: 0.0
• Epoch: 4

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
0.2775	0.8887	nan	0.0	0
0.1702	0.9390	nan	0.0	1
0.1300	0.9555	nan	0.0	2
0.1346	0.9544	nan	0.0	3
0.1408	0.9512	nan	0.0	4

Framework versions

• Transformers 4.16.2
• TensorFlow 2.7.0
• Datasets 1.18.3
• Tokenizers 0.11.0