---
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: 0.0013
- Validation Loss: 0.1945
- Train Precision: 0.8199
- Train Recall: 0.7425
- Train F1: 0.7793
- Train Accuracy: 0.9614
- 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 | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.7385     | 0.3395          | 0.2826          | 0.2232       | 0.2494   | 0.9016         | 0     |
| 0.2565     | 0.2143          | 0.6564          | 0.5494       | 0.5981   | 0.9360         | 1     |
| 0.1188     | 0.2212          | 0.6146          | 0.5064       | 0.5553   | 0.9317         | 2     |
| 0.0631     | 0.1887          | 0.7321          | 0.7039       | 0.7177   | 0.9524         | 3     |
| 0.0358     | 0.1894          | 0.7210          | 0.7210       | 0.7210   | 0.9496         | 4     |
| 0.0161     | 0.1829          | 0.8301          | 0.7339       | 0.7790   | 0.9605         | 5     |
| 0.0092     | 0.1609          | 0.7982          | 0.7811       | 0.7896   | 0.9590         | 6     |
| 0.0060     | 0.1885          | 0.8269          | 0.7382       | 0.7800   | 0.9619         | 7     |
| 0.0035     | 0.1838          | 0.8261          | 0.7339       | 0.7773   | 0.9614         | 8     |
| 0.0022     | 0.1852          | 0.8182          | 0.7339       | 0.7738   | 0.9609         | 9     |
| 0.0026     | 0.1900          | 0.7991          | 0.7339       | 0.7651   | 0.9590         | 10    |
| 0.0012     | 0.1923          | 0.7907          | 0.7296       | 0.7589   | 0.9595         | 11    |
| 0.0010     | 0.1927          | 0.8199          | 0.7425       | 0.7793   | 0.9614         | 12    |
| 0.0014     | 0.1942          | 0.8199          | 0.7425       | 0.7793   | 0.9614         | 13    |
| 0.0013     | 0.1945          | 0.8199          | 0.7425       | 0.7793   | 0.9614         | 14    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2