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metadata
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
  - generated_from_keras_callback
model-index:
  - name: aadhistii/tsel-finetune-bert-base-indonesian-1.5G-sentiment-analysis-smsa
    results: []

aadhistii/tsel-finetune-bert-base-indonesian-1.5G-sentiment-analysis-smsa

This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0293
  • Validation Loss: 1.3686
  • Train Accuracy: 0.6712
  • Epoch: 7

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': 730, '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
1.3087 0.8960 0.6336 0
0.7406 0.9109 0.6199 1
0.5737 0.8554 0.6473 2
0.3301 0.9670 0.6473 3
0.1785 1.0983 0.6712 4
0.0729 1.2668 0.6678 5
0.0481 1.3972 0.6541 6
0.0293 1.3686 0.6712 7

Framework versions

  • Transformers 4.42.3
  • TensorFlow 2.15.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1