---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: apwic/indobert-base-uncased-lora-nergrit
  results: []
library_name: peft
---

<!-- 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. -->

# apwic/indobert-base-uncased-lora-nergrit

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: 0.1277
- Validation Loss: 0.1806
- Train Accuracy: 0.9468
- Epoch: 9

## 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2352, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4709     | 0.2069          | 0.9399         | 0     |
| 0.1823     | 0.1855          | 0.9441         | 1     |
| 0.1402     | 0.1806          | 0.9468         | 2     |
| 0.1287     | 0.1806          | 0.9468         | 3     |
| 0.1280     | 0.1806          | 0.9468         | 4     |
| 0.1278     | 0.1806          | 0.9468         | 5     |
| 0.1285     | 0.1806          | 0.9468         | 6     |
| 0.1279     | 0.1806          | 0.9468         | 7     |
| 0.1289     | 0.1806          | 0.9468         | 8     |
| 0.1277     | 0.1806          | 0.9468         | 9     |


### Framework versions

- PEFT 0.5.0
- PEFT 0.5.0
- Transformers 4.33.0
- TensorFlow 2.12.0
- Datasets 2.14.6
- Tokenizers 0.13.3