22best_berita_roberta_model_fold_4 – AI Model by choiruzzia | AlphaNeural AI

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choiruzzia/
22best_berita_roberta_model_fold_4

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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_4

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: 0.9316
Accuracy: 0.8578
Precision: 0.8563
Recall: 0.8589
F1: 0.8565

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	0.6362	0.7630	0.7721	0.7544	0.7523
No log	2.0	212	0.6104	0.7915	0.8111	0.7792	0.7784
No log	3.0	318	0.9225	0.8389	0.8441	0.8394	0.8349
No log	4.0	424	0.7776	0.8531	0.8505	0.8526	0.8513
0.4372	5.0	530	0.9357	0.8531	0.8545	0.8499	0.8482
0.4372	6.0	636	1.2975	0.8341	0.8573	0.8336	0.8289
0.4372	7.0	742	0.9316	0.8578	0.8563	0.8589	0.8565
0.4372	8.0	848	1.2425	0.8199	0.8267	0.8221	0.8159
0.4372	9.0	954	1.2742	0.8389	0.8549	0.8352	0.8324
0.0124	10.0	1060	1.2426	0.8341	0.8476	0.8311	0.8278

Framework versions

Transformers 4.42.3
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1