gacoanReviewer / README.md
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Training in progress epoch 24
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metadata
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
  - generated_from_keras_callback
model-index:
  - name: aditnnda/gacoanReviewer
    results: []

aditnnda/gacoanReviewer

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: 0.0001
  • Validation Loss: 0.5471
  • Train Accuracy: 0.9163
  • Epoch: 24

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3550, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
0.2751 0.2043 0.9107 0
0.1202 0.2077 0.9177 1
0.0583 0.2770 0.9079 2
0.0435 0.3412 0.9066 3
0.0251 0.3762 0.9079 4
0.0208 0.2241 0.9303 5
0.0070 0.2794 0.9317 6
0.0151 0.3823 0.9219 7
0.0088 0.3740 0.9261 8
0.0019 0.4286 0.9261 9
0.0030 0.6086 0.8912 10
0.0052 0.4023 0.9344 11
0.0005 0.5193 0.9121 12
0.0002 0.5171 0.9135 13
0.0002 0.5276 0.9163 14
0.0002 0.5344 0.9135 15
0.0002 0.5362 0.9163 16
0.0001 0.5407 0.9163 17
0.0001 0.5406 0.9163 18
0.0001 0.5484 0.9149 19
0.0001 0.5406 0.9177 20
0.0001 0.5431 0.9177 21
0.0001 0.5453 0.9163 22
0.0001 0.5466 0.9163 23
0.0001 0.5471 0.9163 24

Framework versions

  • Transformers 4.35.2
  • TensorFlow 2.15.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0