saiteja001r/job-classification-llama2

🧠 Job Classification Dataset for LLaMA 2 Fine-Tuning

This dataset contains 1,000 synthetic job descriptions and their associated job categories. It is designed for fine-tuning large language models (LLMs), such as LLaMA 2, for job classification tasks.

📂 Dataset Structure

• —Format: JSONL (.jsonl)
• —Fields:
• —instruction: A generic instruction prompt.
• —input: The job description text.
• —output: The job type label.

🔧 Example

{
  "instruction": "Classify the following job description into a job type.",
  "input": "We are looking for someone with experience in PyTorch, machine learning, and LLM fine-tuning.",
  "output": "Machine Learning"
}

📌 Job Categories

The dataset supports the following job types:

• —Machine Learning
• —Full Stack Developer
• —Frontend Developer
• —Backend Developer
• —DevOps Engineer
• —Data Engineer
• —Data Scientist
• —Mobile Developer
• —QA Tester
• —Product Manager

🎯 Intended Use

• —Supervised fine-tuning of instruction-following LLMs (like LLaMA 2)
• —Text classification tasks
• —NLP educational or research purposes

⚖️ License

This dataset is synthetic and does not contain any personal or proprietary data. It is available under the MIT License.

✍️ Citation

If you use this dataset, please cite:

Sai Teja (2025). Synthetic Job Classification Dataset for LLM Fine-Tuning.