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hyperparameters

11 articles · Page 1 of 1
Machine Heart
Machine Heart
Apr 26, 2026 · Artificial Intelligence

Has Deep Learning Discovered Its Own “Newton’s Law”?

A new collaborative paper titled “There Will Be a Scientific Theory of Deep Learning” proposes a unified “Learning Mechanics” framework that connects solvable idealized models, tractable limits, empirical scaling laws, hyperparameter theory, and universal representation behavior, aiming to give deep learning a first‑principles scientific foundation.

Deep Learninghyperparameterslearning mechanics
0 likes · 14 min read
Has Deep Learning Discovered Its Own “Newton’s Law”?
Fun with Large Models
Fun with Large Models
Apr 17, 2026 · Artificial Intelligence

Mastering Large Model Training: Practical Parameter Tuning from Beginner to Pro

This guide walks you through interpreting training logs and loss curves, diagnosing common issues such as oscillation, under‑fitting, and over‑fitting, and applying concrete adjustments to learning rate, LoRA settings, batch size, and epochs, with scenario‑specific strategies to turn a novice into a tuning expert.

AI trainingLoRAhyperparameters
0 likes · 23 min read
Mastering Large Model Training: Practical Parameter Tuning from Beginner to Pro
Fun with Large Models
Fun with Large Models
Apr 1, 2026 · Artificial Intelligence

A Beginner's Deep Dive into Large‑Model Training Parameters with LLaMAFactory

This article walks readers through the three major training methods—full‑parameter, LoRA, and QLoRA—explaining their memory costs, data requirements, and trade‑offs, then provides a line‑by‑line breakdown of LLaMAFactory configuration files, hyper‑parameter tuning guidelines, and the process for merging LoRA adapters into a deployable model.

LLaMAFactoryLoRAModel Merge
0 likes · 27 min read
A Beginner's Deep Dive into Large‑Model Training Parameters with LLaMAFactory
Amazon Cloud Developers
Amazon Cloud Developers
Sep 12, 2025 · Artificial Intelligence

Fine‑Tune Amazon Nova Canvas in 12 Hours for Consistent, Cohesive AI Storyboards (Part 2)

This guide shows how to fine‑tune the Amazon Nova Canvas foundation model on Amazon Bedrock using a 12‑hour workflow that extracts character frames from video with Amazon Rekognition, prepares labeled data, configures hyper‑parameters, creates a custom model, deploys it with provisioned throughput, and tests the model to generate coherent storyboard images, while also covering cleanup steps to avoid ongoing costs.

AI storyboardAmazon BedrockAmazon Nova Canvas
0 likes · 17 min read
Fine‑Tune Amazon Nova Canvas in 12 Hours for Consistent, Cohesive AI Storyboards (Part 2)
NewBeeNLP
NewBeeNLP
Jul 31, 2024 · Artificial Intelligence

Training 7B–13B LLMs: Practical Tips, Hyperparameters, and Scaling Challenges

The article shares hands‑on experience training 7‑ and 13‑billion‑parameter language models, covering essential hyper‑parameters, hardware requirements, data quality considerations, open dataset resources, and the systemic difficulties that arise when scaling to trillion‑parameter models.

LLM trainingLarge Language Modelshyperparameters
0 likes · 8 min read
Training 7B–13B LLMs: Practical Tips, Hyperparameters, and Scaling Challenges
NewBeeNLP
NewBeeNLP
Feb 22, 2024 · Artificial Intelligence

Practical Tips for CPT, SFT, and LoRA in Large Language Model Fine‑Tuning

This article shares hands‑on guidance on using continual pre‑training (CPT), supervised fine‑tuning (SFT), and LoRA adapters for large language models, covering dataset size requirements, learning‑rate scheduling, warm‑up ratios, epoch strategies, and practical routing choices based on real‑world experiments.

CPTLLM fine-tuningLoRA
0 likes · 12 min read
Practical Tips for CPT, SFT, and LoRA in Large Language Model Fine‑Tuning
Architects' Tech Alliance
Architects' Tech Alliance
Sep 3, 2020 · Artificial Intelligence

Deep Learning Specialization Infographic Overview

This article presents a comprehensive English summary of the deep learning specialization infographics originally shared by Andrew Ng, covering fundamentals, logistic regression, shallow and deep neural networks, regularization, optimization, hyperparameters, convolutional and recurrent networks, and practical advice for model building and evaluation.

CNNDeep LearningOptimization
0 likes · 21 min read
Deep Learning Specialization Infographic Overview
Sohu Tech Products
Sohu Tech Products
Mar 6, 2019 · Artificial Intelligence

Applying Word2Vec Embeddings to Rental and News Recommendation: Model, Hyper‑parameters, and Optimization

This article explains the fundamentals of the Word2Vec SGNS model, details its hyper‑parameters and training tricks, and demonstrates how customized embeddings are built for rental‑listing and news‑article recommendation, covering data preparation, objective‑function redesign, evaluation, and deployment in both recall and ranking stages.

EmbeddingSGNSWord2Vec
0 likes · 14 min read
Applying Word2Vec Embeddings to Rental and News Recommendation: Model, Hyper‑parameters, and Optimization