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README.md

@@ -1,24 +1,43 @@
 ---
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: label
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3931749
-    num_examples: 24000
-  - name: test
-    num_bytes: 983502
-    num_examples: 6000
-  download_size: 3306674
-  dataset_size: 4915251
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+license: mit
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- gender-classification
+- synthetic
+- distillation
+- c4
+size_categories:
+- 10K<n<100K
 ---
+
+# Gender Classification Dataset (English)
+
+## Dataset Description
+This dataset contains 30000 text samples labeled for the gender of the grammatical subject. 
+It was generated using a **Teacher-Student distillation** process.
+
+- **Repository:** [IsGarrido/gender-classifier-dataset-en](https://huggingface.co/IsGarrido/gender-classifier-dataset-en)
+- **Language:** English
+- **Labels:** `male`, `female`, `neutral`
+
+## Creation Process
+1.  **Source:** Sentences were streamed from the `allenai/c4` (Colossal Clean Crawled Corpus) dataset.
+2.  **Filtering:** Sentences between 50-200 characters were selected.
+3.  **Labeling (Teacher):** A local LLM (`mistralai/magistral-small-2509`) running via LM Studio analyzed each sentence.
+4.  **Prompt:** "Analyze the following sentence and identify the gender of the SUBJECT... Return ONLY one word: 'Male', 'Female', or 'Neutral'."
+5.  **Balancing:** The dataset generation was strictly controlled to ensure an even 33/33/33 split between classes.
+
+## Data Structure
+- `text`: The sentence (string).
+- `label`: The gender class (string: "male", "female", "neutral").
+
+## Usage
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("IsGarrido/gender-classifier-dataset-en")
+print(dataset["train"][0])
+```