results_indobert-large-p2_preprocessing_without_stopword_tuning – AI Model by Alfanatasya | AlphaNeural AI

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Alfanatasya/
results_indobert-large-p2_preprocessing_without_stopword_tuning

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text-classification

generated_from_trainer

indobenchmark/indobert-large-p2

autotrain_compatible

endpoints_compatible

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results_indobert-large-p2_preprocessing_without_stopword_tuning

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

Loss: 0.6643
Accuracy: 0.7568
Precision: 0.7774
Recall: 0.7524
F1: 0.7581

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: 2.085396971587942e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.5977	1.0	111	1.3853	0.4477	0.5530	0.3966	0.3767
1.0253	2.0	222	0.7431	0.725	0.7550	0.7211	0.7179
0.5893	3.0	333	0.6643	0.7568	0.7774	0.7524	0.7581
0.363	4.0	444	0.8267	0.7523	0.7625	0.7562	0.7463
0.1944	5.0	555	0.8982	0.7364	0.7345	0.7514	0.7339

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2