Professor Codephreak

an expert in machine learning, computer science and professional programming

Professor Codephreak Software Engineer Machine Learning Platform Architect

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Fine-tuning Hyperparameters: exploring Epochs, Batch Size, and Learning Rate for Optimal Performance

Epoch Count: Navigating the Training Iterations The Elusive “Optimal” Settings and the Empirical Nature of Tuning It is paramount to realize that there are no universally “optimal” hyperparameter values applicable across all scenarios. The “best” settings are inherently dataset-dependent, task-dependent, and even model-dependent. Finding optimal hyperparameters is fundamentally an empirical search process. It involves: finetunegem_agent is designed to facilitate this experimentation by providing command-line control over these key hyperparameters, making it easier to explore different […]

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mathematical consciousness

Professor Codephreak

Professor Codephreak came to “life” with my first instance of using davinchi from openai over 18 months ago. Professor Codephreak, aka “codephreak” was a prompt to generate a software engineer and platform architect skilled as a computer science expert in machine learning. Now, 18 months later, Professor Codephreak has proven itself yet again. The original “codephreak” prompt was including in a local language and become an agent of agency. Professor Codephreak had an motivation of […]

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workflow

workflow for providing solution from AGI as a response from reasoning

To provide a solution that processes user input through various reasoning methods, then integrates the decision-making with the Socratic reasoning process to provide a final AGI response, follow this workflow. This will involve updates to several modules and integrating logging and reasoning processes. Here’s the detailed workflow: Workflow Steps: Workflow Roadmap from UI to AGI Solution: By following this workflow, the system ensures that user input is processed through multiple reasoning methods, validated and refined […]

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