damand2061/pfsa-id-med-indobert-lem

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

• Train Loss: 0.1033
• Validation Loss: 0.2546
• Validation F1: 0.8649
• Validation Accuracy: 0.9290
• 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'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': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
• training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Validation F1	Validation Accuracy	Epoch
0.3412	0.2362	0.7881	0.9230	0
0.2070	0.2131	0.8448	0.9301	1
0.1615	0.2377	0.8529	0.9254	2
0.1288	0.2406	0.8623	0.9285	3
0.1033	0.2546	0.8649	0.9290	4

Framework versions

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