Chessmen/TF_fine_tune_bert-base-cased

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: 0.0540
• Validation Loss: 0.0649
• Epoch: 5

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': 1756, '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: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
0.1439	0.0649	0
0.0545	0.0649	1
0.0546	0.0649	2
0.0552	0.0649	3
0.0550	0.0649	4
0.0540	0.0649	5

Framework versions

• Transformers 4.44.2
• TensorFlow 2.17.0
• Datasets 2.21.0
• Tokenizers 0.19.1