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pfsa-id-med-indobert-nlu – AI Model by damand2061 | AlphaNeural AI
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damand2061
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pfsa-id-med-indobert-nlu
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transformers
tf
bert
token-classification
generated_from_keras_callback
id
indobenchmark/indobert-base-p1
finetune
mit
autotrain_compatible
endpoints_compatible
us
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damand2061/pfsa-id-med-indobert-nlu
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:
Train Loss: 0.0536
Validation Loss: 0.3159
Validation F1: 0.8593
Validation Accuracy: 0.9287
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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 19220, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Validation F1
Validation Accuracy
Epoch
0.2859
0.2166
0.8202
0.9290
0
0.1802
0.2188
0.8487
0.9301
1
0.1260
0.2377
0.8558
0.9281
2
0.0807
0.2802
0.8588
0.9274
3
0.0536
0.3159
0.8593
0.9287
4
Framework versions
Transformers 4.44.0
TensorFlow 2.16.1
Datasets 2.21.0
Tokenizers 0.19.1
