ChicoPanama/pokedao-mew1a-training-data-layered

PokeDAO Mew-1A Training Dataset (Layered Architecture)

🧬 Project Mew-1A: The world's first AI training dataset specifically for Pokemon TCG pricing analysis, extracted from a production-ready layered database architecture.

Dataset Description

This dataset contains 10,000 high-quality training examples extracted from PokeDAO's layered database containing 116,744 market listings across multiple marketplaces.

Layered Architecture

The data is sourced from a 6-layer database architecture:

• —Layer 0: Official Pokemon TCG metadata (21,626 cards from TCGdex)
• —Layer 1: Canonical card registry (35,421 unique card variants)
• —Layer 2: Market listings (116,744 listings - SOURCE OF THIS DATASET)
• —Layer 3: Sale records (pending)
• —Layer 4: Consensus pricing (pending)
• —Layer 5: Signals & alerts (pending)

Price Tier Classification

Each card is classified into TCG Rarity-Based Price Tiers:

Tier Definitions

• —🌟 SECRET RARE: $100,000+ (Ultra-premium grails)
• —💫 ULTRA RARE: $10,000-100k (High-value collectibles)
• —✨ FULL ART: $1,000-10k (Premium cards)
• —⚡ HOLO RARE: $100-1k (Standard collectibles)
• —📦 UNCOMMON: $10-100 (Common playables)
• —📄 COMMON: $1-10 (Bulk cards)

Dataset Structure

Features

• —id: Unique example identifier
• —card_name: Canonical card name
• —card_set: TCG set name
• —card_number: Card number in set
• —variant: Card variant (holo, reverse holo, etc.)
• —rarity: Official TCG rarity
• —is_first_edition: First edition flag
• —is_holo: Holographic flag
• —is_reverse_holo: Reverse holo flag
• —is_shadowless: Shadowless variant flag
• —avg_price_cents: Average price in cents
• —avg_price_formatted: Human-readable price
• —total_listings: Number of market listings
• —price_tier: TCG-based price tier
• —price_tier_emoji: Tier emoji indicator
• —sample_listings: JSON array of sample listings
• —data_quality: Data quality score (0-1)

Example Row

{
  'id': 'mew1a-1',
  'card_name': 'Charizard',
  'card_set': 'Base Set',
  'card_number': '4/102',
  'variant': 'Holo',
  'rarity': 'Rare Holo',
  'avg_price_cents': 50000,
  'avg_price_formatted': '$500.00',
  'total_listings': 42,
  'price_tier': 'HOLO RARE',
  'price_tier_emoji': '⚡',
  ...
}

Use Cases

1. 1.Price Prediction Models: Train models to predict card prices based on attributes
2. 2.Market Analysis: Analyze pricing trends across tiers and sets
3. 3.Investment Recommendations: Build systems to identify undervalued cards
4. 4.Price Tier Classification: Classify cards into value tiers
5. 5.Anomaly Detection: Identify mispriced listings

Recommended Models

• —Base Model: meta-llama/Llama-3.2-3B-Instruct
• —Task: Text generation / Classification
• —Fine-tuning: LoRA (rank 8, alpha 16)

Training Configuration

model: meta-llama/Llama-3.2-3B-Instruct
task: text-generation
method: LoRA
parameters:
  lora_rank: 8
  lora_alpha: 16
  learning_rate: 2e-4
  epochs: 3
  batch_size: 4
  gradient_accumulation_steps: 4

Metadata

• —Version: v1
• —Created: 2025-10-05
• —Source: Layered Database (canonicalcards + marketlistings)
• —Tier System: TCG Rarity-Based (Option B)
• —Total Examples: 10,000
• —File Size: ~5MB

Data Sources

• —eBay Browse API
• —Courtyard (Ethereum + Polygon tokenized cards)
• —Collector Crypt (Helius/Solana NFTs)
• —Phygitals (Solana NFT marketplace)
• —TCG Player API

License

Proprietary - PokeDAO 2025

For commercial use, please contact: [PokeDAO Team]

Citation

@dataset{pokedao_mew1a_2025,
  title={PokeDAO Mew-1A Training Dataset},
  author={PokeDAO},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/ChicoPanama/pokedao-mew1a-training-data-layered}
}

Links

• —PokeDAO: GitHub
• —Project Mew-1A: Fine-tuned Llama-3.2-3B for TCG pricing
• —Database Architecture: 6-layer canonical system

Generated with Project Mew-1A | 2025-10-05