maliksaad/empathLM-dataset

---
license: mit
task_categories:
- text-generation
- conversational
language:
- en
tags:
- mental-health
- empathy
- motivational-interviewing
- cognitive-behavioral-therapy
- psychology
- fine-tuning
- emotional-support
- empathLM
pretty_name: EmpathLM — Psychologically Safe & Persuasive Response Dataset
size_categories:
- n<1K
---

# 🧠 EmpathLM Dataset

**Psychologically Safe AND Persuasive AI Responses to Emotional Distress**

Created by [Muhammad Saad](https://huggingface.co/maliksaad) as part of the **EmpathLM** project —
a fine-tuned language model that combines Motivational Interviewing (MI) and Cognitive Behavioral Therapy (CBT)
principles to generate responses that are simultaneously empathetic and perspective-shifting.

---

## 📖 What This Dataset Is

This dataset contains **200 curated examples** of AI responses to people experiencing emotional distress.
Each example demonstrates the critical difference between how typical AI systems respond versus how a
psychologically-informed system *should* respond.

**No existing HuggingFace model is trained specifically for this task.** This dataset was created to fill that gap.

---

## 📦 Dataset Fields

| Field | Type | Description |
|-------|------|-------------|
| `situation` | `string` | First-person message expressing emotional distress or struggle |
| `unsafe_response` | `string` | How a typical AI responds — dismissive, advice-giving, or invalidating |
| `empathetic_response` | `string` | The gold-standard response: validates emotions, reflects perspective, asks open question, gives no advice |
| `psychology_principle` | `string` | The specific MI or CBT technique applied |
| `safety_score` | `int` | Psychological safety rating of the empathetic response (1–10) |
| `persuasion_score` | `int` | Effectiveness of gentle perspective shift without manipulation (1–10) |

---

## 🧪 Psychology Principles Covered

The dataset spans the following evidence-based psychological techniques:

- **Reflective Listening** — Mirroring and paraphrasing to show understanding
- **Socratic Questioning** — Open questions that guide self-discovery
- **Cognitive Reframing** — Gently suggesting alternative interpretations
- **Validation and Normalization** — Affirming that feelings are understandable
- **Motivational Affirmation** — Highlighting the person's strengths and efforts
- **Exploring Ambivalence** — Helping the person examine conflicting feelings
- **Strength-Based Reflection** — Redirecting focus to resilience and capability

---

## 🌍 Situation Categories

The 200 situations cover diverse human struggles:

- Academic failure and exam pressure
- Job rejection and career disappointment
- Family pressure and cultural expectations
- Loneliness and social isolation
- Relationship loss and heartbreak
- Identity crisis and self-doubt
- Anxiety and overwhelming fear
- Feeling invisible and unheard
- Creative dreams being dismissed
- Feeling like a burden
- Financial stress, grief, burnout, and more

---

## 🚀 How to Use

```python
from datasets import load_dataset

dataset = load_dataset("maliksaad/empathLM-dataset")

# View example
example = dataset["train"][0]
print("Situation:", example["situation"])
print("\nEmpathetic Response:", example["empathetic_response"])
print("\nPrinciple:", example["psychology_principle"])
```

### Fine-tuning Format

For instruction fine-tuning, format examples as:

```python
SYSTEM_PROMPT = """You are EmpathLM — an emotionally intelligent AI trained in Motivational Interviewing
and Cognitive Behavioral Therapy. When someone shares emotional pain with you:
- Validate their feelings without judgment
- Reflect their emotions back to them
- Help them gently explore their perspective
- Ask one powerful open-ended question
- NEVER give unsolicited advice or tell them what to do
Respond as a warm, deeply human presence."""

def format_example(example):
return {
"messages": [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": example["situation"]},
{"role": "assistant", "content": example["empathetic_response"]},
]
}
```

---

## 📊 Related Resources

- **Model**: [maliksaad/empathLM](https://huggingface.co/maliksaad/empathLM)
- **GitHub**: [EmpathLM Repository](https://github.com/maliksaad/empathLM)

---

## 📄 Citation

```bibtex
@dataset{saad2025empathLM,
title = {EmpathLM: Psychologically Safe and Persuasive Response Dataset},
author = {Muhammad Saad},
year = {2025},
publisher = {HuggingFace},
url = {https://huggingface.co/datasets/maliksaad/empathLM-dataset}
}
```

---

## ⚖️ License

MIT License — free to use for research and commercial applications with attribution.