indobert-base-uncased-multilabel-indonesian-hate-speech-new

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3543
• F1: 0.7722
• Roc Auc: 0.8657
• Accuracy: 0.7010

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:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3501	1.0	659	0.2838	0.6629	0.8057	0.5313
0.2605	2.0	1318	0.2387	0.7122	0.8282	0.5687
0.2164	3.0	1977	0.2381	0.7231	0.8249	0.6355
0.1468	4.0	2636	0.2437	0.7455	0.8429	0.6524
0.1172	5.0	3295	0.2534	0.7517	0.8422	0.6553
0.1019	6.0	3954	0.2661	0.7545	0.8481	0.6557
0.0695	7.0	4613	0.2833	0.7597	0.8512	0.6735
0.0568	8.0	5272	0.2976	0.7615	0.8553	0.6824
0.0508	9.0	5931	0.3146	0.7649	0.8602	0.6809
0.0366	10.0	6590	0.3294	0.7583	0.8454	0.6929
0.0299	11.0	7249	0.3407	0.7667	0.8626	0.6875
0.0262	12.0	7908	0.3437	0.7706	0.8622	0.6940
0.0195	13.0	8567	0.3481	0.7707	0.8603	0.7010
0.0176	14.0	9226	0.3543	0.7722	0.8657	0.7010
0.0151	15.0	9885	0.3566	0.7711	0.8642	0.6978

Framework versions

• Transformers 4.51.3
• Pytorch 2.7.0+cu128
• Datasets 3.6.0
• Tokenizers 0.21.1