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pfsa-id-med-NusaBERT – AI Model by damand2061 | AlphaNeural AI
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damand2061
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pfsa-id-med-NusaBERT
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transformers
tf
bert
token-classification
generated_from_keras_callback
LazarusNLP/NusaBERT-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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damand2061/pfsa-id-med-NusaBERT
This model is a fine-tuned version of
LazarusNLP/NusaBERT-base
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.1463
Validation Loss: 0.2312
Validation F1: 0.8260
Validation Accuracy: 0.9308
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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'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': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16
Training results
Train Loss
Validation Loss
Validation F1
Validation Accuracy
Epoch
0.3937
0.2724
0.6512
0.9110
0
0.2361
0.2354
0.7562
0.9255
1
0.1954
0.2295
0.8054
0.9296
2
0.1651
0.2309
0.8228
0.9303
3
0.1463
0.2312
0.8260
0.9308
4
Framework versions
Transformers 4.44.2
TensorFlow 2.17.0
Datasets 2.21.0
Tokenizers 0.19.1
