results_indobert-base-p2_aug_tuning – AI Model by Alfanatasya | AlphaNeural AI

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Alfanatasya/
results_indobert-base-p2_aug_tuning

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text-classification

generated_from_trainer

indobenchmark/indobert-base-p2

autotrain_compatible

endpoints_compatible

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results_indobert-base-p2_aug_tuning

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

Loss: 0.7988
Accuracy: 0.7016
Precision: 0.7164
Recall: 0.7055
F1: 0.7020

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: 5.676783347142969e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.9839	1.0	220	0.7988	0.7016	0.7164	0.7055	0.7020
0.5162	2.0	440	0.9342	0.6970	0.7175	0.6937	0.7028
0.2465	3.0	660	1.1822	0.6811	0.6957	0.6843	0.6867
0.1443	4.0	880	1.2859	0.7016	0.7129	0.7049	0.7074
0.1108	5.0	1100	1.6919	0.6834	0.6852	0.6893	0.6839
0.0921	6.0	1320	1.8590	0.6879	0.6915	0.6969	0.6934

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 4.0.0
Tokenizers 0.21.0