Create README.md

README.md

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+---
+datasets:
+- kornwtp/indonlu-smsa
+language:
+- id
+metrics:
+- accuracy
+base_model:
+- indobenchmark/indobert-base-p1
+pipeline_tag: text-classification
+---
+
+# Indonesian Text Sentiment Analysis 🚀
+**Model Is Under Development**
+## 📌 Overview  
+This project fine-tunes a **transformer-based model** to analyze sentiment for Indonesian text.  
+
+## 📥 Data Collection  
+The dataset used for fine-tuning was sourced from **IndoNLU Datasets**, specifically:  
+[SmSA (IndoNLU) Dataset](https://metatext.io/datasets/smsa-(indonlu))
+
+## 🔄 Data Preparation  
+- **Tokenization**:
+  - Used **Indobert** for efficient text processing.
+- **Train-Test Split**:
+  - The Dataset is already splitted into train, validation, and test.
+
+## 🏋️ Fine-Tuning & Results  
+The model was fine-tuned using **TensorFlow Hugging Face Transformers**.
+
+### **📊 Evaluation Metrics**
+| **Epoch** | **Train Loss** | **Train Accuracy** | **Eval Loss** | **Eval Accuracy** | **Training Time** | **Validation Time** |
+|-----------|----------------|---------------------|---------------|-------------------|-------------------|---------------------|
+| **1**     | `0.2471`       | `88.15%`           | `0.2107`      | `91.31%`          | `7:55 min`        | `10 sec`            |
+| **2**     | `0.1844`       | `90.41%`           | `0.2107`      | `92.39%`          | `7:50 min`        | `10 sec`            |
+| **3**     | `0.1502`       | `91.66%`           | `0.2135`      | `93.14%`          | `7:51 min`        | `9 sec`             |
+| **4**     | `0.1285`       | `92.50%`           | `0.2192`      | `93.69%`          | `7:50 min`        | `10 sec`            |
+| **5**     | `0.1101`       | `93.13%`           | `0.2367`      | `94.14%`          | `7:48 min`        | `9 sec`             |
+
+## ⚙️ Training Parameters  
+epochs = 5
+learning_rate = 5e-5
+seed_val = 42
+max_length = 128
+batch_size = 32
+eval_batch_size = 32