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

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: 1.0161
- Validation Loss: 3.1318
- Epoch: 11

## 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': 132, '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 |
|:----------:|:---------------:|:-----:|
| 5.3332     | 4.2681          | 0     |
| 3.7948     | 3.4128          | 1     |
| 2.8637     | 3.0312          | 2     |
| 2.5416     | 3.0434          | 3     |
| 2.3160     | 3.0057          | 4     |
| 2.1121     | 2.9734          | 5     |
| 1.7971     | 2.9516          | 6     |
| 1.5246     | 2.9939          | 7     |
| 1.5344     | 3.0014          | 8     |
| 1.2878     | 3.0860          | 9     |
| 1.1462     | 3.1003          | 10    |
| 1.0161     | 3.1318          | 11    |


### Framework versions

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