---
library_name: peft
license: apache-2.0
tags:
- json-extraction
- modernbert
- lora
- diffuberta
metrics:
- name: train_loss
  value: 4.7773
- name: eval_loss
  value: 4.316555023193359
---

# DiffuBERTa: JSON Extraction Adapter

This model is a Fine-tuned version of **answerdotai/ModernBERT-base** using LoRA. It is designed to extract structured JSON data from unstructured text using a parallel decoding approach.

## Model Performance
- **Final Training Loss**: 4.7773
- **Final Evaluation Loss**: 4.316555023193359
- **Training Epochs**: 5
- **Date Trained**: 2025-11-28

## 🚀 Live Demo Output
*(Generated automatically after training)*

**Input Text:**
> "We are excited to welcome Dr. Sarah to our Paris office as Senior Data Scientist."

**Template:**
> `{'name': '[1]', 'job': '[2]', 'city': '[1]'}`

**Model Output:**
```json
{
  "name": "Sarah",
  "job": "Data scientist",
  "city": "Paris"
}
```

## Usage
```python
from transformers import AutoModelForMaskedLM, AutoTokenizer
from peft import PeftModel

base_model = AutoModelForMaskedLM.from_pretrained("answerdotai/ModernBERT-base")
model = PeftModel.from_pretrained(base_model, "philipp-zettl/DiffuBERTa")
# ... use extract_parallel helper ...
```