---
license: mit
base_model: ayameRushia/indobert-base-uncased-finetuned-indonlu-smsa
tags:
- generated_from_keras_callback
model-index:
- name: stevanussmbrng/speeches_sentiment
  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. -->

# stevanussmbrng/speeches_sentiment

This model is a fine-tuned version of [ayameRushia/indobert-base-uncased-finetuned-indonlu-smsa](https://huggingface.co./ayameRushia/indobert-base-uncased-finetuned-indonlu-smsa) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0253
- Validation Loss: 0.3025
- Train Accuracy: 0.9
- 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': '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': 420, '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 | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.5261     | 0.2992          | 0.9059         | 0     |
| 0.2843     | 0.2773          | 0.8941         | 1     |
| 0.1874     | 0.3459          | 0.8706         | 2     |
| 0.1765     | 0.3533          | 0.8706         | 3     |
| 0.0829     | 0.2778          | 0.9059         | 4     |
| 0.0566     | 0.2593          | 0.8941         | 5     |
| 0.0394     | 0.2550          | 0.9176         | 6     |
| 0.0252     | 0.2876          | 0.9            | 7     |
| 0.0268     | 0.3052          | 0.8941         | 8     |
| 0.0253     | 0.3025          | 0.9            | 9     |


### Framework versions

- Transformers 4.41.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1