Model Training

Our platform features diverse cutting-edge deep learning architectures tailored to address various computer vision tasks, including object detection, image classification, LLM-instruction tuning, instance segmentation, and semantic segmentation. Users can leverage our base models. The platform guides you through end-to-end model lifecycle management - model selection, training, optimization, and deployment to achieve exceptional results in your computer vision initiatives.

Use the following combinations based on your requirement (Base, Split, or Fine-Tune models) and For all three combinations — Base Model, Hyperparameter Tuning, and Augmentation — you can use either Split or Skip.

• If you choose Skip, the default configuration will automatically be applied from the backend, so there’s no need for manual setup.

• If you want to test with ratio-based configurations, use the Split option to balance according to your desired split ratio.

• Base Model → Skip → Hyperparameter + Augmentation

  • Standard base configuration for initial training.

• Base Model + Augmentation → Skip Hyperparameter

  • Use when applying augmentation directly without tuning hyperparameters.

• Base Model + Split → Skip Augmentation + Skip Hyperparameter

  • Use for split-based training without augmentation or hyperparameter tuning.

• Fine-Tune Model → Skip → Hyperparameter + Augmentation

  • Use when fine-tuning with both augmentation and hyperparameter adjustments.

• Fine-Tune Model + ABase Model → Skip → Hyperparameter + Augmentation

  • Standard base configuration for initial training.

• Base Model + Augmentation → Skip Hyperparameter

  • Use when applying augmentation directly without tuning hyperparameters.

• Base Model + Split → Skip Augmentation + Skip Hyperparameter

  • Use for split-based training without augmentation or hyperparameter tuning.

• Fine-Tune Model → Skip → Hyperparameter + Augmentation

  • Use when fine-tuning with both augmentation and hyperparameter adjustments.

• Fine-Tune Model + Augmentation → Skip Hyperparameter

  • Use when applying augmentation only during fine-tuning.

• Fine-Tune Model + Split → Skip Augmentation + Skip Hyperparameter

  • Use for fine-tuned split models without augmentation or hyperparameter tuning.

• Hyperparameter Model + Augmentation → Toggle Button: ON

  • Enables augmentation along with hyperparameter optimization.

• Hyperparameter Model – Without Augmentation → Toggle Button: OFF

  • Disables augmentation while retaining existing hyperparameter configuration.

• Augmentation → Skip Hyperparameter

  • Use when applying augmentation only during fine-tuning.

• Fine-Tune Model + Split → Skip Augmentation + Skip Hyperparameter

  • Use for fine-tuned split models without augmentation or hyperparameter tuning.

• Hyperparameter Model + Augmentation → Toggle Button: ON

  • Enables augmentation along with hyperparameter optimization.

• Hyperparameter Model – Without Augmentation → Toggle Button: OFF

  • Disables augmentation while retaining existing hyperparameter configuration.