Habiba9/bert_best_model

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: 0.0020
• Train Accuracy: 1.0
• Validation Loss: 0.1250
• Validation Accuracy: 0.9718
• Epoch: 9

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2300, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.4447	0.8693	0.1970	0.9448	0
0.1220	0.9654	0.1743	0.9448	1
0.0438	0.9898	0.1265	0.9624	2
0.0200	0.9963	0.1615	0.9546	3
0.0133	0.9967	0.1236	0.9681	4
0.0071	0.9989	0.1304	0.9710	5
0.0044	0.9997	0.1248	0.9714	6
0.0026	0.9999	0.1296	0.9702	7
0.0033	0.9996	0.1249	0.9722	8
0.0020	1.0	0.1250	0.9718	9

Framework versions

• Transformers 4.53.0
• TensorFlow 2.19.0
• Datasets 3.6.0
• Tokenizers 0.21.1