Model Information 🧬

🔬 Base Model:

🧩 Task Type:

📊 Dataset:

• protein: Contains mutation data including the RhlA enzyme sequence and corresponding performance metrics.
• Label: The experimentally tested fitness score, representing the scaled mutation effect for each mutant.
• Source: Label derived from CAPE

🔡 Model Input Type:

📈 Performance (the best on test set):

LoRA Configuration ⚙️

• r: 8
• LoRA dropout: 0.1
• LoRA alpha: 8
• Modules to save: ["regression"]

Training Configuration 🎛️

• Optimizer:
  • Class: AdamW
  • Betas: (0.9, 0.98)
  • Weight decay: 0.01
• Learning rate: 5e-5
• Epochs: 5
• Batch size: Adaptive