22best_berita_roberta_model_fold_1 – AI Model by choiruzzia | AlphaNeural AI

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choiruzzia/
22best_berita_roberta_model_fold_1

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text-classification

generated_from_trainer

ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa

autotrain_compatible

endpoints_compatible

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22best_berita_roberta_model_fold_1

This model is a fine-tuned version of ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8575
Accuracy: 0.8868
Precision: 0.8904
Recall: 0.8843
F1: 0.8870

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
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	Precision	Recall	F1
No log	1.0	106	0.9177	0.5472	0.7029	0.6055	0.5274
No log	2.0	212	0.8990	0.7264	0.7612	0.7252	0.7101
No log	3.0	318	0.7968	0.8491	0.8478	0.8622	0.8496
No log	4.0	424	0.8026	0.8396	0.8400	0.8413	0.8353
0.5042	5.0	530	1.0039	0.8443	0.8579	0.8603	0.8488
0.5042	6.0	636	0.8274	0.8774	0.8743	0.8850	0.8780
0.5042	7.0	742	0.8575	0.8868	0.8904	0.8843	0.8870
0.5042	8.0	848	0.9014	0.8821	0.8806	0.8906	0.8830
0.5042	9.0	954	0.9622	0.8726	0.8723	0.8859	0.8741
0.0373	10.0	1060	0.9673	0.8726	0.8723	0.8859	0.8741

Framework versions

Transformers 4.42.3
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1