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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: damand2061/pfsa-id-med-indobert-lem
    results: []
language:
  - id
pipeline_tag: token-classification
library_name: transformers

damand2061/pfsa-id-med-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: 0.1033
  • Validation Loss: 0.2546
  • Validation F1: 0.8649
  • Validation Accuracy: 0.9290
  • 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
0.3412 0.2362 0.7881 0.9230 0
0.2070 0.2131 0.8448 0.9301 1
0.1615 0.2377 0.8529 0.9254 2
0.1288 0.2406 0.8623 0.9285 3
0.1033 0.2546 0.8649 0.9290 4

Framework versions

  • Transformers 4.44.0
  • TensorFlow 2.16.1
  • Datasets 2.21.0
  • Tokenizers 0.19.1