indobert-base-uncased-finetuned-indonlu-smsa

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

• Loss: 0.2277
• Accuracy: 0.9302
• F1: 0.9066
• Precision: 0.8992
• Recall: 0.9147

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1500
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	344	0.3831	0.8476	0.7715	0.7817	0.7627
0.4167	2.0	688	0.2809	0.8905	0.8406	0.8699	0.8185
0.2624	3.0	1032	0.2254	0.9230	0.8842	0.9004	0.8714
0.2624	4.0	1376	0.2378	0.9238	0.8797	0.9180	0.8594
0.1865	5.0	1720	0.2277	0.9302	0.9066	0.8992	0.9147
0.1217	6.0	2064	0.2444	0.9262	0.8981	0.9013	0.8957
0.1217	7.0	2408	0.2985	0.9286	0.8999	0.9035	0.8971
0.0847	8.0	2752	0.3397	0.9278	0.8969	0.9090	0.8871
0.0551	9.0	3096	0.3542	0.9270	0.8961	0.9010	0.8924
0.0551	10.0	3440	0.3862	0.9222	0.8895	0.8970	0.8846

Framework versions

• Transformers 4.14.1
• Pytorch 1.10.0+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3