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, a comprehensive collection of climbing routes curated with the help of the BoardLib utility by lemeryfertitta.
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