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IndoBERT-IndoNLU-QA – AI Model by Rifky | AlphaNeural AI
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Rifky
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IndoBERT-IndoNLU-QA
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transformers
tf
bert
question-answering
generated_from_keras_callback
mit
endpoints_compatible
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Rifky/IndoBERT-IndoNLU-QA
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:
Train Loss: 0.8296
Validation Loss: 2.3649
Epoch: 4
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:
optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 20360, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32
Training results
Train Loss
Validation Loss
Epoch
2.1819
2.0387
0
1.5849
1.9827
1
1.2610
2.0652
2
1.0048
2.2270
3
0.8296
2.3649
4
Framework versions
Transformers 4.26.1
TensorFlow 2.11.0
Datasets 2.9.0
Tokenizers 0.13.2
