DistilBERT-Hoax-Detection – AI Model by dafqi | AlphaNeural AI

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dafqi/
DistilBERT-Hoax-Detection

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text-classification

generated_from_trainer

cahya/distilbert-base-indonesian

autotrain_compatible

endpoints_compatible

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DistilBERT-Hoax-Detection

This model is a fine-tuned version of cahya/distilbert-base-indonesian on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5261
Accuracy: 0.8441

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-06
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
lr_scheduler_warmup_ratio: 0.15
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6644	1.0	93	0.6368	0.6237
0.4151	2.0	186	0.5300	0.7258
0.3645	3.0	279	0.5003	0.7688
0.3283	4.0	372	0.4585	0.7957
0.2557	5.0	465	0.4599	0.8065
0.3993	6.0	558	0.5004	0.8065
0.0536	7.0	651	0.4658	0.8387
0.1944	8.0	744	0.5264	0.8280
0.0612	9.0	837	0.5195	0.8387
0.0602	10.0	930	0.5261	0.8441

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3