---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: digo-prayudha/Indonesian_sentiment
  results: []
language:
- id
pipeline_tag: text-classification
datasets:
- sepidmnorozy/Indonesian_sentiment
---

<!-- 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. -->

# digo-prayudha/Indonesian_sentiment

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on [sepidmnorozy/Indonesian_sentiment](https://huggingface.co/datasets/sepidmnorozy/Indonesian_sentiment).
It achieves the following results on the evaluation set:
- Train Loss: 0.1678
- Validation Loss: 0.2402
- Train Accuracy: 0.9016
- Epoch: 2

### 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': 2475, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.4013     | 0.3141          | 0.8667         | 0     |
| 0.2526     | 0.2923          | 0.8839         | 1     |
| 0.1678     | 0.2402          | 0.9016         | 2     |

### How to use this model in Transformers Library

```python
from transformers import pipeline

model = pipeline("text-classification",model="digo-prayudha/Indonesian_sentiment")

model("Makanannya Enak sekali!")
```

### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0