Training Parameters
This function block allows users to specify parameters for training an artificial intelligence (AI) model, particularly in the context of a convolutional neural network (CNN). Users can define the batch size and the number of epochs for the training process.
📥 Inputs
This block does not require any inputs.
📤 Outputs
Training Parameters
Returns a dictionary containing the specified batch size and epochs for training the AI model.
🕹️ Controls
Batch Size
A text field where users can specify the number of training samples to be processed before the model's internal parameters are updated. The default value is set to 32.
Epochs
A text field where users can specify the number of complete passes through the training dataset. The default value is set to 150.
🎨 Features
Dynamic Parameter Setting
Users can adjust the batch size and epochs directly from the interface, allowing for flexible model training configurations.
Validation Check
Each input field validates its number type, ensuring correct data types are provided for training parameters.
📝 Usage Instructions
Open the Block: Drag and drop the block into your flow.
Set Parameters: Enter the desired values for
Batch Size
andEpochs
. Adjust these values to fit your training needs.Run the Training: Use the output from this block in conjunction with your AI training setup.
📊 Evaluation
When executed, this function block will output the selected training parameters in a structured format ready to be utilized for AI model training.
💡 Tips and Tricks
🛠️ Troubleshooting
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