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README.md

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+---
+language: en
+tags:
+- phi-2
+- customer-service
+- transcript-analysis
+- multi-issue
+license: mit
+---
+
+# Phi-2 Multi-Issue Transcript Analysis Model
+
+This model is fine-tuned from Microsoft's Phi-2 for analyzing customer service transcripts with multiple issues. It can:
+
+1. Identify primary and secondary issues
+2. Analyze customer sentiment
+3. Rate agent performance
+4. Track resolution status
+5. Predict CSAT scores
+6. Extract key actions and outcomes
+
+## Model Details
+
+- **Base Model**: microsoft/phi-2
+- **Task**: Multi-issue customer service transcript analysis
+- **Training Data**: Customer service transcripts with multiple issues
+- **Output Format**: Structured JSON with detailed analysis
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("chendren/phi2-multi-issue-analysis")
+tokenizer = AutoTokenizer.from_pretrained("chendren/phi2-multi-issue-analysis")
+
+# Prepare input
+transcript = """[Your customer service transcript here]"""
+
+# Generate analysis
+inputs = tokenizer(transcript, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=512)
+analysis = tokenizer.decode(outputs[0])
+```
+
+## Example Output
+
+```json
+{
+  "primary_issue": "Internet connection drops",
+  "secondary_issues": [
+    "Signal interference",
+    "Router firmware outdated"
+  ],
+  "customer_sentiment": "negative",
+  "agent_performance": {
+    "rating": 4,
+    "justification": "Agent was helpful and provided clear instructions"
+  },
+  "resolution_status": "resolved",
+  "follow_up_needed": false,
+  "key_points": [
+    "Customer experienced internet drops",
+    "Agent guided through troubleshooting",
+    "Issue resolved with firmware update"
+  ],
+  "issues": [
+    "Intermittent connection drops",
+    "WiFi interference",
+    "Outdated firmware"
+  ],
+  "actions": [
+    "Diagnosed signal fluctuations",
+    "Updated router firmware",
+    "Provided monitoring instructions"
+  ],
+  "outcomes": [
+    "Connection stability improved",
+    "Firmware updated successfully"
+  ],
+  "predicted_csat": 4
+}
+```
+
+## Limitations
+
+- Designed specifically for customer service transcripts
+- Best performance with clear dialogue format
+- May require adjustment for different transcript formats
+
+## Citation
+
+If you use this model, please cite:
+
+```bibtex
+@misc{phi2-multi-issue-analysis,
+  author = {args.username},
+  title = {Phi-2 Multi-Issue Transcript Analysis Model},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {Hugging Face Model Hub},
+  howpublished = {https://huggingface.co/chendren/phi2-multi-issue-analysis}
+}
+```