Update README.md

README.md

@@ -33,3 +33,64 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+# Binary Classification Dataset: Profession Detection in Tweets
+
+This dataset is a derived version of the original **PROFNER** task, adapted for binary text classification. The goal is to determine whether a tweet **mentions a profession or not**.
+
+## 🧠 Objective
+
+Each example contains:
+- A `tweet_id` (document identifier)
+- A `text` field (full tweet content)
+- A `label`, which has been normalized into two classes:
+  - `CON_PROFESION`: The tweet contains a reference to a profession.
+  - `SIN_PROFESION`: The tweet does not contain any profession-related term.
+
+## 📦 Dataset Structure
+
+The dataset is formatted as a `DatasetDict` with three splits:
+
+| Split        | Description                                           |
+|--------------|-------------------------------------------------------|
+| `train`      | Balanced dataset containing both classes              |
+| `validation` | Contains equal distribution of profession/no-profession |
+| `test`       | Also balanced for evaluating binary classification    |
+
+Each example follows the structure:
+
+```python
+{
+  "tweet_id": "1242399976644325376",
+  "text": "Nuestros colaboradores y conductores se quedan en casa!",
+  "label": "CON_PROFESION"  # or "SIN_PROFESION"
+}
+```
+
+The `label` column is implemented with Hugging Face `ClassLabel`, which makes it easy to convert between string and integer representation.
+
+## 🔄 Label Mapping
+
+The dataset uses the following class labels:
+
+```python
+label_list = ["SIN_PROFESION", "CON_PROFESION"]
+label2id = { "SIN_PROFESION": 0, "CON_PROFESION": 1 }
+id2label = { 0: "SIN_PROFESION", 1: "CON_PROFESION" }
+```
+
+These are automatically applied via Hugging Face `datasets.Features`.
+
+## 📥 How to Load
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("luisgasco/profner_classification_master")
+print(ds["train"][0])
+```
+
+## ✍️ Author
+
+Processed and [Luis Gasco](https://huggingface.co/luisgasco) for educational purposes, based on the PROFNER corpus.
+