---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_keras_callback
model-index:
- name: damand2061/innermore-x-indobert-base-p1
  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-p1

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0007
- Validation Loss: 0.2387
- Validation Precision: 0.7583
- Validation Recall: 0.6987
- Validation F1: 0.7273
- Validation Accuracy: 0.9535
- 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 |
|:----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|:-----:|
| 0.5438     | 0.2878          | 0.5065               | 0.5109            | 0.5087        | 0.9161              | 0     |
| 0.1798     | 0.1890          | 0.6416               | 0.6332            | 0.6374        | 0.9425              | 1     |
| 0.0764     | 0.2122          | 0.5833               | 0.5502            | 0.5663        | 0.9338              | 2     |
| 0.0491     | 0.1986          | 0.7729               | 0.6987            | 0.7339        | 0.9545              | 3     |
| 0.0333     | 0.2071          | 0.75                 | 0.6812            | 0.7140        | 0.9545              | 4     |
| 0.0252     | 0.1806          | 0.7456               | 0.7424            | 0.7440        | 0.9530              | 5     |
| 0.0138     | 0.2283          | 0.7018               | 0.6987            | 0.7002        | 0.9497              | 6     |
| 0.0073     | 0.2202          | 0.7318               | 0.7031            | 0.7171        | 0.9530              | 7     |
| 0.0065     | 0.2174          | 0.7762               | 0.7118            | 0.7426        | 0.9540              | 8     |
| 0.0037     | 0.2373          | 0.7619               | 0.6987            | 0.7289        | 0.9516              | 9     |
| 0.0021     | 0.2343          | 0.7594               | 0.7031            | 0.7302        | 0.9535              | 10    |
| 0.0015     | 0.2478          | 0.7546               | 0.7118            | 0.7326        | 0.9530              | 11    |
| 0.0011     | 0.2405          | 0.7630               | 0.7031            | 0.7318        | 0.9540              | 12    |
| 0.0006     | 0.2388          | 0.7583               | 0.6987            | 0.7273        | 0.9535              | 13    |
| 0.0007     | 0.2387          | 0.7583               | 0.6987            | 0.7273        | 0.9535              | 14    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Tokenizers 0.15.2