---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraEdu-v1.0x
  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/LabiraEdu-v1.0x

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: 0.0512
- Validation Loss: 4.1014
- Epoch: 34

## 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    |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1