damand2061/pfsa-id-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: 0.1353
• Validation Loss: 0.2440
• Validation F1: 0.8119
• Validation Accuracy: 0.9295
• 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': 10440, '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
0.4338	0.2589	0.6515	0.9170	0
0.2529	0.2283	0.7705	0.9276	1
0.2046	0.2272	0.7979	0.9293	2
0.1622	0.2312	0.8089	0.9303	3
0.1353	0.2440	0.8119	0.9295	4

Framework versions

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