Naveengo/bert-finetuned-on-ncbi__disease

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

• Train Loss: 0.0209
• Validation Loss: 0.0649
• Train Accuracy: 0.9828
• 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1017, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.1255	0.0659	0.9788	0
0.0391	0.0594	0.9821	1
0.0209	0.0649	0.9828	2

Framework versions

• Transformers 4.34.1
• TensorFlow 2.13.0
• Datasets 2.14.5
• Tokenizers 0.14.1