Update README.md

README.md

@@ -29,3 +29,126 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+
+
+# Multilingual Text Classification Dataset
+
+This dataset is designed for **multilingual text classification** tasks.
+It includes labeled text samples across **8 languages**, making it ideal for training and evaluating models on **cross-lingual transfer**, **language identification**, and **multilingual understanding**.
+
+
+## Dataset Overview
+
+| Split      | # Examples | Size (bytes)  |
+| ---------- | ---------- | ------------- |
+| Train      | 18,657     | 2,651,248     |
+| Validation | 2,665      | 378,709       |
+| Test       | 5,331      | 757,560       |
+| **Total**  | **26,653** | **3,787,517** |
+
+**Total Download Size:** 2.6 MB
+**Total Dataset Size:** 3.8 MB
+**Task Type:** Text Classification
+
+
+## Data Fields
+
+| Field   | Type     | Description                                        |
+| ------- | -------- | -------------------------------------------------- |
+| `text`  | `string` | The input text sample.                             |
+| `lang`  | `string` | The ISO 639-3 language code of the text.           |
+| `label` | `int64`  | The integer label representing the language class. |
+
+
+## Language Labels
+
+| Language | Code  | Label ID |
+| -------- | ----- | -------- |
+| German   | `deu` | 0        |
+| Chinese  | `zho` | 1        |
+| Amharic  | `amh` | 2        |
+| Arabic   | `arb` | 3        |
+| Hausa    | `hau` | 4        |
+| Urdu     | `urd` | 5        |
+| Spanish  | `spa` | 6        |
+| English  | `eng` | 7        |
+
+This mapping is stored internally in the dataset and can be used to decode model predictions or remap outputs.
+
+
+## Intended Uses
+
+* Multilingual language classification
+* Cross-lingual and zero-shot evaluation
+* Benchmarking multilingual embeddings (e.g., mBERT, XLM-R, LaBSE)
+* Studying language similarity and confusion patterns
+
+
+## Usage Example
+
+You can easily load the dataset using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("8Opt/multilingual-classification-0001")
+
+example = dataset["train"][0]
+print(example)
+```
+
+Output:
+
+```python
+{
+  "text": "Das ist ein Beispielsatz.",
+  "lang": "deu",
+  "label": 0
+}
+```
+
+Label mapping:
+
+```python
+id2label = {
+    0: "deu",
+    1: "zho",
+    2: "amh",
+    3: "arb",
+    4: "hau",
+    5: "urd",
+    6: "spa",
+    7: "eng"
+}
+```
+
+
+## Configurations
+
+**Configuration name:** `default`
+
+Each split is stored under `data/`:
+
+```
+data/
+ ├── train-*
+ ├── validation-*
+ └── test-*
+```
+
+---
+
+## Citation
+
+If you use this dataset in your work, please cite it as:
+
+```
+@dataset{8Opt,
+  title={Multilingual Text Classification Dataset},
+  author={Your Name},
+  year={2025},
+  url={https://huggingface.co/datasets/8Opt/multilingual-classification-0001}
+}
+```
+