Optimizer Adadelta
This function block implements the Adadelta optimization algorithm, which is used for training artificial intelligence (AI) models. It provides parameters to customize the behavior of the optimizer for various training scenarios.
π₯ Inputs
This function block does not have any inputs.
π€ Outputs
The output is the Adadelta optimizer configured with the specified parameters. This optimizer can be utilized in an AI training process.
πΉοΈ Controls
Learning Rate
A text input field to specify the learning rate for the optimizer. The default value is 0.001
.
Rho
A text input field to set the decay rate for the Adadelta optimizer. The default value is 0.95
.
Epsilon
A text input field to specify a small constant added to the denominator to improve numerical stability. The default value is 1e-07
.
π¨ Features
Customizable Parameters
Users can adjust the learning rate, rho, and epsilon values to fine-tune the optimizer for different training conditions.
User-Friendly Interface
The interface provides labeled input fields for easy configuration of each parameter.
π Usage Instructions
Configure Parameters: Enter your desired values for
Learning Rate
,Rho
, andEpsilon
in the respective fields.Run the Block: Evaluate the block to create an instance of the Adadelta optimizer configured with your specified values.
π Evaluation
Upon evaluation, this function block outputs an instance of the Adadelta optimizer that is prepared to be used in the training of machine learning models.
π‘ Tips and Tricks
π οΈ Troubleshooting
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