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indobert-hoax-classification – AI Model by Rifky | AlphaNeural AI
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Rifky
/
indobert-hoax-classification
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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indobert-hoax-classification
This model is a fine-tuned version of
indobenchmark/indobert-base-p1
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6230
Accuracy: 0.8059
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: 4.2173070213315e-05
train_batch_size: 32
eval_batch_size: 16
seed: 30
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
85
0.5540
0.7029
No log
2.0
170
0.5432
0.7029
No log
3.0
255
0.4963
0.7441
No log
4.0
340
0.5791
0.7971
No log
5.0
425
0.6230
0.8059
Framework versions
Transformers 4.21.0
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1
