ner_fine_tuned_gdsc_tutoring_fariz

This model is a fine-tuned version of cahya/bert-base-indonesian-NER on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8927
• Precision: 0.5946
• Recall: 0.5116
• F1: 0.55
• Accuracy: 0.8763

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	8	0.9070	0.6471	0.5116	0.5714	0.8866
No log	2.0	16	0.8893	0.5946	0.5116	0.55	0.8763
No log	3.0	24	0.8927	0.5946	0.5116	0.55	0.8763

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1