---
library_name: transformers
widget:
- text: Aku sayang banget karo koe
  example_title: Positif
- text: Mbok ojo dadi wong sing nganyeli
  example_title: Negatif
language:
- id
metrics:
- accuracy
---

# Model Card for Model ID

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## Model Details

### Model Description

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Model ini merupakan model untuk analisis sentimen yang dirancang khusus untuk teks dalam bahasa Jawa Ngoko Lugu, menggunakan IndoBERT sebagai basisnya. Model ini bertujuan untuk mengidentifikasi sentimen dalam teks Jawa Ngoko Lugu, mengklasifikasikan teks tersebut sebagai positif atau negatif.

- **Developed by:** Aziz Prabowo
- **Model type:** Sentiment Analysis
- **Language(s) (NLP):** Bahasa Jawa Ngoko Lugu
- **Finetuned from model :** IndoBERT

### Model Sources [optional]

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## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**APA:**

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## Glossary [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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