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