results_indobert-large-p2_with_preprocess_augmentasi – AI Model by Alfanatasya | AlphaNeural AI

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Alfanatasya/
results_indobert-large-p2_with_preprocess_augmentasi

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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_with_preprocess_augmentasi

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: 0.6566
Accuracy: 0.7699
Precision: 0.7801
Recall: 0.7810
F1: 0.7787

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
1.5419	1.0	219	1.1051	0.6196	0.6402	0.6091	0.5945
0.946	2.0	438	0.7191	0.7380	0.7533	0.7460	0.7386
0.7298	3.0	657	0.6566	0.7699	0.7801	0.7810	0.7787
0.5705	4.0	876	0.7686	0.7403	0.7421	0.7523	0.7444
0.4361	5.0	1095	0.8300	0.7449	0.7435	0.7583	0.7425

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2