---
license: mit
tags: [chess, pytorch, resnet, se-resnet, position-evaluation, policy-head, arabic]
language: [ar, en]
---
# Chess Position Evaluator - V7 HULK

Ahmed Darwish | [@engdarwish](https://huggingface.co/engdarwish)

## Architecture
SE-ResNet-20 with Dual Head (Value + Policy)

| Metric | Value |
|--------|-------|
| Parameters | 47,450,753 |
| Best Val Loss | 0.030174 |
| Architecture | SE-ResNet-20 |
| Input | 18x8x8 board tensor |
| Value Output | [-1, 1] (tanh) |
| Policy Output | 20,480 move logits (from-square x to-square x underpromotion) |

## Training Data

| Source | Size |
|--------|------|
| Kaggle Chess Evaluations | 12.9M positions (Stockfish evals) |
| Lichess 2023-10 | 2M moves from ELO 2000+ games |

## Quick Start

```bash
pip install torch python-chess huggingface_hub numpy
```

```python
from inference import load_model, get_best_move
import chess

model = load_model()
value, moves = get_best_move(model, chess.STARTING_FEN, top_k=3)
print(value, moves)
```

See inference.py in this repo for the full, runnable example: board encoding, model definition, and legal-move-masked move ranking.

## Files

| File | Purpose |
|------|---------|
| model_weights.pt (190MB) | Inference weights: use this to load the model |
| checkpoint.pt (569MB) | Full training checkpoint (model + optimizer + scheduler state): only needed to resume training |
| config.json | Architecture config |
| inference.py | Minimal working inference example |
| training_curves.png | Training/validation loss curves |

## Contact
eahmeddarwish@gmail.com
[GitHub](https://github.com/eahmeddarwish)