Update README.md

# Myanmar Sentiment Intensity Dataset v1

This dataset contains Myanmar (Burmese) text samples annotated for sentiment intensity across 5 levels. It is specifically curated for training and evaluating text classification models.

## Dataset Structure
The dataset consists of two primary columns:
- `text`: Raw Myanmar text strings.
- `label`: Sentiment intensity score (Integer 0 to 4).

## Label Definitions
| Label | Emoji | Sentiment | Description |
|---|---|---|---|
| 0 | 🔴 | Very Negative | Strong dissatisfaction, anger, or hate |
| 1 | 🟠 | Negative | Dissatisfaction, boredom, or sadness |
| 2 | 🟡 | Neutral | Normal, factual, or indifferent |
| 3 | 🟢 | Positive | Satisfied, good, or peaceful |
| 4 | 🔵 | Very Positive | Very happy, excellent, or joyful |


## Data Preprocessing
To achieve optimal results with this dataset, it is highly recommended to perform **Syllable Breaking** before tokenization. This ensures the model learns based on Myanmar syllable units rather than characters.

### Python Preprocessing Function:
```python
import re

def myanmar_sylbreak(line):
pat = re.compile(r"((?<!္)[က-အ](?![်္])|[a-zA-Z0-9ဣဤဥဦဧဩဪဿ၌၍၏၀-၉၊။!-/:-@[-`{-~\s])")
line = re.sub(r'\s+', ' ', str(line).strip())
return pat.sub(r" \1", line).strip()

## Acknowledgments & Credits

This dataset is developed by building upon existing Myanmar NLP resources and research:

* **Base Dataset Source:** This work utilizes data and concepts from the [Myanmar Text Segmentation Dataset](https://huggingface.co/datasets/chuuhtetnaing/myanmar-text-segmentation-dataset) by Chuu Htet Naing.
* **Syllable Segmentation:** The syllable breaking logic is based on the [sylbreak](https://github.com/ye-kyaw-thu/sylbreak) repository by Ye Kyaw Thu.

README.md

@@ -1,7 +1,14 @@
 ---
 license: mit
 task_categories:
-- sentence-similarity
+- text-classification
 language:
 - my
+tags:
+- sentiment-analysis
+- myanmar
+- burmese
+pretty_name: Myanmar Sentiment Intensity Dataset v1
+size_categories:
+- 1K<n<10K
 ---