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pfsa-id-indobert-lem – AI Model by damand2061 | AlphaNeural AI
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damand2061
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pfsa-id-indobert-lem
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0
transformers
tf
bert
token-classification
generated_from_keras_callback
indolem/indobert-base-uncased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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damand2061/pfsa-id-indobert-lem
This model is a fine-tuned version of
indolem/indobert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Train Loss: 0.1353
Validation Loss: 0.2440
Validation F1: 0.8119
Validation Accuracy: 0.9295
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': 10440, '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
0.4338
0.2589
0.6515
0.9170
0
0.2529
0.2283
0.7705
0.9276
1
0.2046
0.2272
0.7979
0.9293
2
0.1622
0.2312
0.8089
0.9303
3
0.1353
0.2440
0.8119
0.9295
4
Framework versions
Transformers 4.44.2
TensorFlow 2.17.0
Datasets 2.21.0
Tokenizers 0.19.1
