BestHub
Sign in
Tagged articles
10 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 LearningNeural Networkshyperparameters
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 trainingLarge ModelLoRA
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.

LLaMAFactoryLoRAQLoRA
0 likes · 27 min read
A Beginner's Deep Dive into Large‑Model Training Parameters with LLaMAFactory
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 traininghyperparameterslarge language models
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 LearningNeural Networks
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