---
license: mit
datasets:
- mstafam/Kilter-Board-Dataset
pipeline_tag: text2text-generation
---

# GenClimb: AI-Generated Climbing Routes for Interactive Training Boards

GenClimb is a generative AI model designed to create climbing routes for Standardized Interactive Climbing Training Boards (SICTBs). It a seq2seq transformer architecture, GenClimb generates climbs based on board layouts and climb difficulties.

## Model Details

### Architecture

- **Dimension**: 512
- **Attention Heads**: 4
- **Layers**: 5
- **Feed-Forward Dimension**: 1024
- **Dropout Rate**: 0.15
- **Activation Function**: GELU
- **Layer Normalization Epsilon**: 1e-5

### Training Configuration

- **Device**: CUDA (1x NVIDIA GeForce RTX 3070)
- **Learning Rate**: 1e-4
- **Epochs**: 8
- **Weight Decay**: 0.0125
- **Batch Size**: 32
- **Train/Test Split**: 90/10

### Performance Metrics

- **Training Time**: 12 hours and 6 minutes
- **Final Loss**: 2.114803

## Dataset

The model is trained on the [Kilter-Board-Dataset](https://huggingface.co/datasets/mstafam/Kilter-Board-Dataset), a comprehensive collection of climbing routes curated with the help of the [BoardLib utility](https://github.com/lemeryfertitta/BoardLib) by lemeryfertitta.