bert-base-nsmc

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

• Train Loss: 0.0257
• Train Accuracy: 0.9921
• Validation Loss: 0.5707
• Validation Accuracy: 0.8712
• 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': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1058, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 117, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.1}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.4122	0.7999	0.3081	0.8694	0
0.2172	0.9141	0.3063	0.8706	1
0.1092	0.9611	0.4054	0.8698	2
0.0479	0.9845	0.5164	0.8704	3
0.0257	0.9921	0.5707	0.8712	4

Framework versions

• Transformers 4.57.6
• TensorFlow 2.19.0
• Datasets 4.0.0
• Tokenizers 0.22.2