kategori_aspek_model – AI Model by Dhanang | AlphaNeural AI

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Dhanang/
kategori_aspek_model

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text-classification

generated_from_trainer

indobenchmark/indobert-base-p2

autotrain_compatible

endpoints_compatible

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kategori_aspek_model

This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5731
Accuracy: 0.7532
F1: 0.7342
Precision: 0.6791
Recall: 0.8234

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.6662	1.0	1816	0.6854	0.7449	0.7139	0.6657	0.7857
0.4846	2.0	3632	0.5731	0.7532	0.7342	0.6791	0.8234
0.3135	3.0	5448	0.6906	0.7667	0.7431	0.7017	0.7994
0.2189	4.0	7264	0.8181	0.7755	0.7387	0.7065	0.7994
0.152	5.0	9080	0.9838	0.7893	0.7486	0.7290	0.7799
0.0938	6.0	10896	1.0601	0.7826	0.7598	0.7314	0.7957
0.0629	7.0	12712	1.3297	0.7868	0.7665	0.7673	0.7684
0.0423	8.0	14528	1.3356	0.7906	0.7639	0.7477	0.7875
0.0178	9.0	16344	1.5868	0.7887	0.7625	0.7656	0.7638
0.008	10.0	18160	1.5453	0.7928	0.7650	0.7621	0.7709

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0