Model Training Platform Using Prefabricated Functions
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Solution Overview
Problem
Traditional model training methods and platforms are inadequate for meeting the complex deep learning development requirements, failing to provide an efficient model training solution for natural language processing tasks.
Innovation Solution
A model training method and platform that includes a data interaction module, interaction supporting module, function providing module, model training supporting module, pre-trained model module, and pre-trained model supporting module, enabling efficient model training through user-oriented prefabricated functions, pre-trained models, and customizable network structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional model training methods are used, then basic training functionality is provided, but complex deep learning development requirements cannot be met
Solution Approach 1:
The training platform is divided into multiple functional modules including data interaction module, interaction supporting module, function providing module, model training supporting module, pre-trained model module, and pre-trained model supporting module. Each module handles specific aspects of the training process, allowing the system to meet complex requirements while maintaining manageable complexity through modular design.
Solution Approach 2:
The platform provides user-oriented prefabricated functions that can be applied across different deep learning tasks and scenarios. These universal functions enable the system to handle diverse complex requirements without needing completely separate solutions for each task type.
2Manufacturing precision
If extensive data annotations and underlying code development are performed, then model training accuracy is improved, but development time and resource consumption increase
Solution Approach 1:
The platform provides pre-trained models that have already been trained on extensive datasets beforehand. Users can directly utilize these pre-trained models for their specific tasks, eliminating the need to perform extensive data annotations and training from scratch, thus significantly reducing development time while maintaining model accuracy.
Solution Approach 2:
The platform offers pre-trained models that serve as templates or copies that can be directly applied to new tasks. Instead of creating training data and models from scratch for each application, users can leverage existing pre-trained models, reducing both time and resource investment.
Data Source
AI summary
A model training method, a model training platform, an electronic device and a storage medium are provided, which can be used in the field of artificial intelligence, particularly the fields of natural language processing and deep learning. The model training method includes: receiving an input; determining, based on the input, a user-oriented prefabricated function; determining, based on the input, a model training function; determining, based on the input, a pre-trained model; determining, based on the input, a network structure associated with the pre-trained model so as to support use of the pre-trained model; training, based on the input, the model by using the prefabricated function, the model training function, and the pre-trained model; and providing an output associated with a trained model.