metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraEdu-v1.0x
results: []
Labira/LabiraEdu-v1.0x
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: 0.0652
- Validation Loss: 4.2064
- Epoch: 37
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': 1100, '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 | Epoch |
|---|---|---|
| 5.0565 | 3.9761 | 0 |
| 3.6621 | 3.2932 | 1 |
| 3.0961 | 3.2587 | 2 |
| 2.7357 | 3.2031 | 3 |
| 2.3059 | 3.2519 | 4 |
| 1.8933 | 3.4772 | 5 |
| 1.9076 | 3.1664 | 6 |
| 1.5492 | 3.4201 | 7 |
| 1.2578 | 3.5190 | 8 |
| 1.0478 | 3.4076 | 9 |
| 1.0130 | 3.5961 | 10 |
| 0.9073 | 3.4919 | 11 |
| 0.7071 | 3.5013 | 12 |
| 0.5616 | 4.0259 | 13 |
| 0.4798 | 3.9766 | 14 |
| 0.5938 | 3.8146 | 15 |
| 0.6476 | 3.7065 | 16 |
| 0.4264 | 4.1631 | 17 |
| 0.5290 | 3.7455 | 18 |
| 0.4637 | 3.6362 | 19 |
| 0.3826 | 3.8389 | 20 |
| 0.2876 | 3.7611 | 21 |
| 0.2221 | 4.0540 | 22 |
| 0.1752 | 4.0683 | 23 |
| 0.1544 | 4.0452 | 24 |
| 0.1600 | 4.0417 | 25 |
| 0.1390 | 4.0668 | 26 |
| 0.1134 | 4.0659 | 27 |
| 0.0965 | 4.0700 | 28 |
| 0.0820 | 4.2026 | 29 |
| 0.0810 | 4.3008 | 30 |
| 0.1166 | 4.0835 | 31 |
| 0.0776 | 4.0886 | 32 |
| 0.1033 | 4.1303 | 33 |
| 0.0512 | 4.1014 | 34 |
| 0.0484 | 4.1462 | 35 |
| 0.0565 | 4.2404 | 36 |
| 0.0652 | 4.2064 | 37 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1