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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_1_1000x
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_1_1000x
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: 0.2616
- Validation Loss: 4.8341
- 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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3000, '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 |
|:----------:|:---------------:|:-----:|
| 5.9029 | 5.5338 | 0 |
| 5.5052 | 5.1945 | 1 |
| 5.0405 | 4.9078 | 2 |
| 4.5254 | 4.5685 | 3 |
| 4.1376 | 4.3884 | 4 |
| 3.8263 | 4.1669 | 5 |
| 3.5461 | 3.8994 | 6 |
| 3.1371 | 3.7182 | 7 |
| 2.7303 | 3.6502 | 8 |
| 2.4936 | 3.7608 | 9 |
| 2.2117 | 3.9550 | 10 |
| 1.9386 | 4.0934 | 11 |
| 1.7866 | 4.1102 | 12 |
| 1.4512 | 4.2896 | 13 |
| 1.1873 | 4.5401 | 14 |
| 0.9892 | 4.8950 | 15 |
| 0.8121 | 4.9718 | 16 |
| 0.7331 | 4.6763 | 17 |
| 0.6712 | 4.5185 | 18 |
| 0.5773 | 4.8674 | 19 |
| 0.4841 | 4.9185 | 20 |
| 0.3451 | 4.8513 | 21 |
| 0.2938 | 4.8199 | 22 |
| 0.3125 | 4.9438 | 23 |
| 0.2616 | 4.8341 | 24 |
### Framework versions
- Transformers 4.45.2
- TensorFlow 2.17.0
- Datasets 2.20.0
- Tokenizers 0.20.1
|