best_bert_model_fold_3

This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2908
• Accuracy: 0.8386
• Precision: 0.8281
• Recall: 0.7986
• F1: 0.8101

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	252	0.6290	0.8008	0.7903	0.7322	0.7457
0.5166	2.0	504	0.6945	0.8068	0.8131	0.7396	0.7568
0.5166	3.0	756	0.9795	0.8108	0.7953	0.7652	0.7721
0.1546	4.0	1008	1.1504	0.8187	0.8024	0.7829	0.7902
0.1546	5.0	1260	1.2908	0.8386	0.8281	0.7986	0.8101
0.0243	6.0	1512	1.2868	0.8247	0.8043	0.7947	0.7988
0.0243	7.0	1764	1.4339	0.8307	0.8214	0.7823	0.7949
0.0077	8.0	2016	1.4287	0.8327	0.8222	0.7845	0.7978
0.0077	9.0	2268	1.4630	0.8287	0.8098	0.7842	0.7941
0.0001	10.0	2520	1.4618	0.8307	0.8129	0.7863	0.7966

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.2
• Datasets 2.19.2
• Tokenizers 0.19.1