---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: damand2061/innermore-x-indobert-base-uncased
  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. -->

# damand2061/innermore-x-indobert-base-uncased

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: 0.0053
- Validation Loss: 0.1740
- Validation Precision: 0.7319
- Validation Recall: 0.7644
- Validation F1: 0.7478
- Validation Accuracy: 0.9582
- Epoch: 14

## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0002, 'decay_steps': 420, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy | Epoch |
|:----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|:-----:|
| 0.7318     | 0.4161          | 0.1453               | 0.1156            | 0.1287        | 0.8751              | 0     |
| 0.3556     | 0.2296          | 0.5610               | 0.5111            | 0.5349        | 0.9324              | 1     |
| 0.2050     | 0.1668          | 0.6972               | 0.6756            | 0.6862        | 0.9521              | 2     |
| 0.1289     | 0.1603          | 0.6807               | 0.72              | 0.6998        | 0.9531              | 3     |
| 0.0875     | 0.1874          | 0.7281               | 0.7022            | 0.7149        | 0.9521              | 4     |
| 0.0754     | 0.1931          | 0.6653               | 0.7156            | 0.6895        | 0.9479              | 5     |
| 0.0416     | 0.1637          | 0.6935               | 0.7644            | 0.7273        | 0.9554              | 6     |
| 0.0238     | 0.1413          | 0.7598               | 0.7733            | 0.7665        | 0.9638              | 7     |
| 0.0152     | 0.1494          | 0.7479               | 0.8044            | 0.7752        | 0.9634              | 8     |
| 0.0152     | 0.1946          | 0.7061               | 0.7156            | 0.7108        | 0.9531              | 9     |
| 0.0128     | 0.1815          | 0.7241               | 0.7467            | 0.7352        | 0.9554              | 10    |
| 0.0072     | 0.1766          | 0.7210               | 0.7467            | 0.7336        | 0.9568              | 11    |
| 0.0080     | 0.1860          | 0.6987               | 0.7422            | 0.7198        | 0.9531              | 12    |
| 0.0089     | 0.1826          | 0.7227               | 0.7644            | 0.7430        | 0.9563              | 13    |
| 0.0053     | 0.1740          | 0.7319               | 0.7644            | 0.7478        | 0.9582              | 14    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2