Metadata.yaml

---
model-index:
- name: Agentic Unified Mind UANN
  results:
    - task:
        type: text-classification
      dataset:
        name: imdb
        type: huggingface
        split: train[:10%]
    - task:
        type: image-classification
      dataset:
        name: cifar10
        type: huggingface
        split: train[:10%]
    - task:
        type: structured-data
      dataset:
        name: titanic
        type: huggingface
        split: train
model_description: |
  The Agentic Unified Mind UANN integrates text, image, and structured data processing using advanced neural network architectures and reinforcement learning. This multi-modal AI model combines BERT for text, ResNet50 for images, and dense neural networks for structured data.
model_type: multi-modal
languages:
  - en
library_name: tensorflow
tags:
  - multi-modal
  - reinforcement-learning
  - text-classification
  - image-classification
  - structured-data
license: apache-2.0
datasets:
  - imdb
  - cifar10
  - titanic
metrics:
  - accuracy
  - loss
---

# Agentic Unified Mind UANN

## Model Description

The Agentic Unified Mind UANN integrates:
- Text processing using BERT.
- Image processing using ResNet50.
- Structured data processing with dense neural networks.
- Reinforcement learning for autonomous decision-making.

## Features

- **Multi-modal Inputs:** Handles text, images, and structured data.
- **Advanced Neural Network Architectures:** Uses BERT for text, ResNet50 for images, and dense layers for structured data.
- **Unified Cognitive Framework:** Combines information from multiple modalities for better decision-making.
- **Reinforcement Learning:** Enhances the model's ability to learn and adapt from interactions.

## Setup

### Installation

Install the required dependencies:

```bash
pip install -r requirements.txt