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README.md

@@ -1,58 +1,89 @@
 ---
+license: mit
 base_model: HuggingFaceTB/SmolLM2-135M-Instruct
-library_name: transformers
-model_name: empathLM
 tags:
-- generated_from_trainer
-- trl
-- sft
-licence: license
+  - empathy
+  - mental-health
+  - motivational-interviewing
+  - cognitive-behavioral-therapy
+  - fine-tuned
+  - emotional-support
+  - empathLM
+language:
+  - en
 ---
 
-# Model Card for empathLM
+# 🧠 EmpathLM
 
-This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct).
-It has been trained using [TRL](https://github.com/huggingface/trl).
+**Fine-tuned for Psychologically Safe & Persuasive Emotional Support**
 
-## Quick start
+EmpathLM is a fine-tuned version of [SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) 
+trained to generate responses that combine **Motivational Interviewing (MI)** and **Cognitive Behavioral Therapy (CBT)** principles.
 
-```python
-from transformers import pipeline
+## What Makes EmpathLM Unique
 
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="maliksaad/empathLM", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
+Unlike general-purpose language models, EmpathLM is specifically optimized to:
+- ✅ **Validate emotions** without judgment
+- ✅ **Reflect feelings** back to the person warmly  
+- ✅ **Gently shift perspective** without being manipulative
+- ✅ **Ask powerful open questions** that encourage self-reflection
+- ❌ **Never give unsolicited advice**
 
-## Training procedure
+## Benchmark Results
 
- 
+EmpathLM was benchmarked against GPT-4o-mini and a Groq baseline on 20 unseen test situations,
+scored across: emotional_validation, advice_avoidance, perspective_shift, and overall_empathy.
 
+*See the [GitHub repository](https://github.com/maliksaad/empathLM) for full benchmark results.*
 
+## Usage
 
-This model was trained with SFT.
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("maliksaad/empathLM")
+model = AutoModelForCausalLM.from_pretrained("maliksaad/empathLM")
+
+SYSTEM_PROMPT = """You are EmpathLM — an emotionally intelligent AI trained in Motivational Interviewing 
+and Cognitive Behavioral Therapy. When someone shares emotional pain:
+- Validate their feelings without judgment
+- Reflect their emotions back to them
+- Ask one powerful open-ended question
+- NEVER give unsolicited advice"""
+
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {"role": "user", "content": "I failed my exam again. I feel like I'm just not smart enough."},
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
+outputs = model.generate(inputs, max_new_tokens=200, temperature=0.7)
+print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True))
+```
 
-### Framework versions
+## Training Details
 
-- TRL: 0.29.1
-- Transformers: 5.0.0
-- Pytorch: 2.10.0+cu128
-- Datasets: 4.8.3
-- Tokenizers: 0.22.2
+| Parameter | Value |
+|-----------|-------|
+| Base Model | SmolLM2-135M-Instruct |
+| Training Examples | ~180 (90% of 200) |
+| Epochs | 3 |
+| Batch Size | 8 |
+| Learning Rate | 2e-5 |
+| Max Sequence Length | 512 |
+| Training Platform | Kaggle (Free GPU) |
 
-## Citations
+## Dataset
 
+Trained on [maliksaad/empathLM-dataset](https://huggingface.co/datasets/maliksaad/empathLM-dataset)
 
+## Citation
 
-Cite TRL as:
-    
 ```bibtex
-@software{vonwerra2020trl,
-  title   = {{TRL: Transformers Reinforcement Learning}},
-  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
-  license = {Apache-2.0},
-  url     = {https://github.com/huggingface/trl},
-  year    = {2020}
+@model{saad2025empathLM,
+  title  = {EmpathLM: A Psychologically-Grounded Empathetic Response Model},
+  author = {Muhammad Saad},
+  year   = {2025},
+  url    = {https://huggingface.co/maliksaad/empathLM}
 }
-```
+```