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---
library_name: transformers
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_2_50
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Labira/LabiraPJOK_2_50
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0612
- Validation Loss: 5.0368
- Epoch: 49
## 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 250, '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 |
|:----------:|:---------------:|:-----:|
| 5.8505 | 5.6669 | 0 |
| 5.2925 | 5.1030 | 1 |
| 4.5442 | 4.7484 | 2 |
| 4.0958 | 4.7040 | 3 |
| 3.7810 | 4.5713 | 4 |
| 3.5676 | 4.4824 | 5 |
| 3.1885 | 4.3205 | 6 |
| 2.7673 | 4.2241 | 7 |
| 2.5267 | 4.2636 | 8 |
| 2.1790 | 4.3948 | 9 |
| 1.8900 | 4.4249 | 10 |
| 1.6497 | 4.3953 | 11 |
| 1.4075 | 4.6399 | 12 |
| 1.1854 | 4.7024 | 13 |
| 0.9754 | 4.9350 | 14 |
| 0.9994 | 5.3112 | 15 |
| 0.7262 | 5.0277 | 16 |
| 0.5385 | 5.6396 | 17 |
| 0.5031 | 5.0280 | 18 |
| 0.4707 | 5.4408 | 19 |
| 0.3623 | 5.2230 | 20 |
| 0.3844 | 5.0132 | 21 |
| 0.3438 | 5.1672 | 22 |
| 0.2012 | 5.2035 | 23 |
| 0.2089 | 5.1718 | 24 |
| 0.1978 | 5.0590 | 25 |
| 0.2140 | 5.1029 | 26 |
| 0.1903 | 4.9778 | 27 |
| 0.1750 | 4.9790 | 28 |
| 0.1228 | 5.0673 | 29 |
| 0.0892 | 5.0525 | 30 |
| 0.1576 | 4.9680 | 31 |
| 0.1337 | 4.9172 | 32 |
| 0.0976 | 4.8575 | 33 |
| 0.0649 | 4.7732 | 34 |
| 0.1050 | 4.8566 | 35 |
| 0.0885 | 5.0122 | 36 |
| 0.0725 | 5.0716 | 37 |
| 0.1004 | 5.0808 | 38 |
| 0.0443 | 5.0632 | 39 |
| 0.0514 | 5.0632 | 40 |
| 0.0632 | 5.0526 | 41 |
| 0.1997 | 5.0193 | 42 |
| 0.0600 | 5.0489 | 43 |
| 0.0482 | 5.0666 | 44 |
| 0.0862 | 5.0719 | 45 |
| 0.1512 | 5.0631 | 46 |
| 0.0815 | 5.0498 | 47 |
| 0.0462 | 5.0410 | 48 |
| 0.0612 | 5.0368 | 49 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.1
- Tokenizers 0.19.1
|