damand2061/pfsa-id-med-indobert-nlu

This model is a fine-tuned version of indobenchmark/indobert-base-p1 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0536
• Validation Loss: 0.3159
• Validation F1: 0.8593
• Validation Accuracy: 0.9287
• 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': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 19220, '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	Validation F1	Validation Accuracy	Epoch
0.2859	0.2166	0.8202	0.9290	0
0.1802	0.2188	0.8487	0.9301	1
0.1260	0.2377	0.8558	0.9281	2
0.0807	0.2802	0.8588	0.9274	3
0.0536	0.3159	0.8593	0.9287	4

Framework versions

• Transformers 4.44.0
• TensorFlow 2.16.1
• Datasets 2.21.0
• Tokenizers 0.19.1