damand2061/innermore-x-indobert-base-uncased

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: 0.0053
• Validation Loss: 0.1740
• Validation Precision: 0.7319
• Validation Recall: 0.7644
• Validation F1: 0.7478
• Validation Accuracy: 0.9582
• Epoch: 14

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': 0.0002, 'decay_steps': 420, '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: float32

Training results

Train Loss	Validation Loss	Validation Precision	Validation Recall	Validation F1	Validation Accuracy	Epoch
0.7318	0.4161	0.1453	0.1156	0.1287	0.8751	0
0.3556	0.2296	0.5610	0.5111	0.5349	0.9324	1
0.2050	0.1668	0.6972	0.6756	0.6862	0.9521	2
0.1289	0.1603	0.6807	0.72	0.6998	0.9531	3
0.0875	0.1874	0.7281	0.7022	0.7149	0.9521	4
0.0754	0.1931	0.6653	0.7156	0.6895	0.9479	5
0.0416	0.1637	0.6935	0.7644	0.7273	0.9554	6
0.0238	0.1413	0.7598	0.7733	0.7665	0.9638	7
0.0152	0.1494	0.7479	0.8044	0.7752	0.9634	8
0.0152	0.1946	0.7061	0.7156	0.7108	0.9531	9
0.0128	0.1815	0.7241	0.7467	0.7352	0.9554	10
0.0072	0.1766	0.7210	0.7467	0.7336	0.9568	11
0.0080	0.1860	0.6987	0.7422	0.7198	0.9531	12
0.0089	0.1826	0.7227	0.7644	0.7430	0.9563	13
0.0053	0.1740	0.7319	0.7644	0.7478	0.9582	14

Framework versions

• Transformers 4.38.2
• TensorFlow 2.15.0
• Tokenizers 0.15.2