Jueju.Wang
Training & Tuning

Model Training · Algorithm Tuning

From model fine-tuning to hyperparameter optimization, from inference acceleration to performance evaluation — end-to-end AI model training and tuning services.

Training Pipeline

End-to-End Training Pipeline

Data Preparation
Cleaning, augmentation, feature engineering
Config Tuning
Hyperparameter search, architecture selection
Training Execution
Distributed training, monitoring
Evaluation & Validation
Metric validation, A/B testing
Deployment & Launch
Model compression, serving
Core Capabilities

Model Training and Tuning Services

Model Fine-Tuning

Domain fine-tuning based on pre-trained models, adapting to bio-computing scenarios

  • ESMFold protein structure fine-tuning
  • Protenix conformation refinement
  • Domain Lora adaptation
  • Few-shot learning

Hyperparameter Tuning

Automated hyperparameter search and optimization, raising the model performance ceiling

  • Bayesian optimization
  • Grid search and random search
  • Learning rate scheduling strategies
  • Batch size and optimizer selection

Model Ensemble

Multi-model fusion and ensemble strategies, improving prediction robustness

  • Model distillation
  • Ensemble learning (Bagging/Boosting)
  • Multi-modal fusion
  • Uncertainty quantification

Inference Optimization

Model compression and inference acceleration, reducing deployment cost

  • Quantization (INT8/FP16)
  • Pruning and sparsification
  • ONNX/TensorRT deployment
  • KV-Cache optimization

Performance Evaluation

Comprehensive model evaluation system, ensuring prediction reliability

  • Cross-validation
  • Ablation Study
  • ROC-AUC / MCC / F1
  • Confidence calibration

Algorithm Development

Customized algorithm R&D, solving specific computational problems

  • Molecular dynamics simulation optimization
  • Custom loss functions
  • Graph neural network design
  • Sequence-to-structure mapping
Training Infrastructure

High-Performance Computing Environment

GPU Cluster

A100/H100 multi-card parallel

Distributed Training

DeepSpeed/FSDP

MLOps Platform

Experiment tracking, version management

Monitoring & Alerting

Real-time training curve visualization