Incremental training for Product Review Parsing
Incremental training lets you add custom labels to the platform's pre-trained models for product review parsing. These models cover the E-commerce, automotive, and local life domains. You can then train a complete parsing model using only the new labels.
If the supported domains and industries do not meet your requirements, you can join the NLP Self-Learning Platform Q&A Group 2 (DingTalk group ID: 44619071) for assistance.
Activate the service and purchase a resource plan
You must activate the service before you can train models on the NLP Self-Learning Platform. After you activate the service, you can purchase discounted resource plans.
NLP Self-Learning Platform: Activation page
NLP Self-Learning Platform resource plan: Purchase page
Procedure
1. Model creation
In the Create Project section, select Product Review Parsing to create a project.
Enter the project information and click OK.
2. Data annotation
In My Projects, go to the Data Center to manage your data. You can create data in two ways:
1. Create an annotation task. 2. Upload a dataset.
2.1 Create an annotation task
Step 1: Upload documents for annotation and add annotators
The project creator and project administrator are annotators by default. You can also assign annotation tasks to your RAM users. These users can then log on to the platform with their RAM user credentials to perform data annotation.
RAM user logon instructions:
1. Go to the RAM user logon page: https://signin.aliyun.com/login.htm
2. After you log on, go to My Projects to perform the annotation task.
Note: Only data files that use UTF-8 encoding are supported.
Step 2: Set the review categories to addStep 3: Annotate data
2.2 Upload a dataset
Alternatively, you can upload training data that has been annotated locally. You must format the data according to the sample file before you upload it.
3. Create a model
In Model Hub, click Create Model.
Enter model information
Set Model Type to Product Review Parsing - Classification - High-Precision - Bert.
Available modes
Disabled: Only annotated data is used for training.
Fuse with platform data: Trains the model using your custom annotated data combined with pre-annotated data from 18 industries on the Alibaba E-commerce platform.
Incremental only: Trains the model using your custom annotated data for the E-commerce, local life, and automotive domains.