PerceptiLabs
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  • Welcome
  • ⚡Getting Started
    • Quickstart Guide
      • Requirements
      • Installation
      • Video Tutorials
    • Load and Pre-process Data
    • Build Models
    • Train Models
    • Evaluate Models
    • Export and Deploy Models
    • Manage, Version, and Track Models
  • 🙏How to Contribute
    • Datasets
    • Models
    • Components
  • 👨‍🍳Tutorials
    • Basic Image Recognition
    • Basic Image Segmentation
  • 🛠️Advanced
    • Common Testing Issues
    • Common Training Issues
    • Components
      • Input and Target
      • Processing
      • Deep Learning
      • Operations
      • Custom
    • CSV File Format
    • Debugging and Diagnostic Features
    • How PerceptiLabs Works With TensorFlow
    • Included Packages
    • Types of Tests
    • UI Overview
      • Data Wizard
      • Overview Screen
      • Model Training Settings
      • Modeling Tool
      • Training View
      • Evaluate View
      • Deploy View
    • Using the Exported/Deployed Model
  • 💡Use Cases
    • General
      • A Guide to Using U-Nets for Image Segmentation
      • A Voice Recognition model using Image Recognition
    • Environmental
      • Automated Weather Analysis Using Image Recognition
      • Wildfire Detection
    • Healthcare & Medical
      • Brain Tumor Detection
      • Breast Cancer Detection
      • Classifying Chest X-Rays to Detect Pneumonia
      • Classifying Ways to Wear a Face Mask
      • Detecting Defective Pills
      • Highlighting Blood Cells in Dark-field Microscopy Using Image Segmentation
      • Ocular Disease Recognition
      • Retinal OCT
      • Skin Cancer Classification
    • Industrial IoT & Manufacturing
      • Air Conditioner Piston Check
      • Classifying Fruit
      • Classifying Wood Veneers Into Dry and Wet
      • Defect Detection in Metal Surfaces
      • Fabric Stain Classification
  • 📖Support
    • FAQs
    • Changelog
  • Code of Conduct
  • Marketing Site
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  1. Advanced
  2. UI Overview

Training View

PreviousModeling ToolNextEvaluate View

Last updated 3 years ago

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The Training View is displayed when training begins (by clicking Run in the Modeling Tool), and provides a number of stats about how the model is performing during training:

The following are the key controls in the Training View's tool bar:

  1. Back to Model: Returns to the Modeling Tool.

  2. Pause: pauses training.

  3. Stop: stops training.

Downloading Stats

Most of the panes contain a download button that generates a screenshot of that tab's/pane's data:

This can be useful for grabbing snapshots of different statistics (e.g., when you pause training at a certain point).

Input Tab

The Input tab displays a visualization of the current data sample:

Target Tab

The Target tab shows a number of panes with vital statistics including loss and accuracy over all epochs, prediction versus ground truth (for the current data sample), and the predictions made so far for each classification (you want to strive for a single color per category):

Tip: You can toggle the display of specific data within a graph (e.g., validation data) by clicking on the respective item in the graph's legend.

Map and View Box

At the bottom of the Statistics View are the Map and View Box areas:

The Map displays the model and the View Box displays real-time statistics about the training. When you click on individual components in the Map, the View Box displays statistics for the selected component, allowing you to analyze your model on a more granular level during training.

The View Box contains the three tabs described in the following sub sections.

Weights & Output Tab

The Weights & Output tab displays the Component's output on the right, and the weights used to create that output on the left. When training models, watch out for weights which are 0 or those which not changing.

Bias Tab

The Bias tab displays the bias for the current data sample:

Gradients Tab

The Gradients tab displays the gradient descent for the model:

🛠️
  • Downloading Stats
  • Input Tab
  • Target Tab
  • Map and View Box
  • Weights & Output Tab
  • Bias Tab
  • Gradients Tab
A pane's download button can be used to download a screenshot of that specific pane.
Map and View Box
Weights & Output Tab
Bias Tab
Gradients Tab