IndoBERT-SAP-mapping

This model is a fine-tuned version of indobenchmark/indobert-base-p2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2940
• Accuracy: 0.9667

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	8	1.1555	0.6667
No log	2.0	16	0.8179	0.8333
No log	3.0	24	0.6175	0.8
No log	4.0	32	0.4520	0.8333
No log	5.0	40	0.4083	0.8
No log	6.0	48	0.3778	0.8333
No log	7.0	56	0.3368	0.9
No log	8.0	64	0.3411	0.9
No log	9.0	72	0.3044	0.9667
No log	10.0	80	0.2940	0.9667

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3