results_indobert-large-p1_with_augmentasi – AI Model by Alfanatasya | AlphaNeural AI

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Alfanatasya/
results_indobert-large-p1_with_augmentasi

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text-classification

generated_from_trainer

indobenchmark/indobert-large-p1

autotrain_compatible

endpoints_compatible

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results_indobert-large-p1_with_augmentasi

This model is a fine-tuned version of indobenchmark/indobert-large-p1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9420
Accuracy: 0.6982
Precision: 0.6942
Recall: 0.7060
F1: 0.6946

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: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=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
1.5551	1.0	220	1.1726	0.5114	0.5340	0.5229	0.5165
0.953	2.0	440	0.8799	0.6788	0.6752	0.6843	0.6770
0.7656	3.0	660	0.8589	0.6913	0.6882	0.6981	0.6922
0.9074	4.0	880	0.9420	0.6982	0.6942	0.7060	0.6946
0.5756	5.0	1100	0.8689	0.6948	0.7011	0.6977	0.6992
0.4301	6.0	1320	1.0207	0.6811	0.6816	0.6879	0.6823

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1