4uiiurz1 / keras-cosine-annealing

Keras implementation of Cosine Annealing Scheduler

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Keras implementation of Cosine Annealing Scheduler

This repository contains code for Cosine Annealing Scheduler based on SGDR: Stochastic Gradient Descent with Warm Restarts implemented in Keras.

Requirements

  • Python 3.6
  • Keras 2.2.4

Usage

Append CosineAnnealingScheduler to list of callbacks and pass to .fit() or .fit_generator():

from cosine_annealing import CosineAnnealingScheduler

callbacks = [
    CosineAnnealingScheduler(T_max=100, eta_max=1e-2, eta_min=1e-4)
]

model.fit(x, y, batch_size=32, callbacks=callbacks)

Training

CIFAR-10

Use CosineAnnealingScheduler:

python train.py --scheduler CosineAnnealingScheduler

Results

CIFAR-10

Model Accuracy (%) Loss
WideResNet28-2 baseline 92.91 0.403
WideResNet28-2 w/ CosineAnnealingScheduler 93.22 0.413

About

Keras implementation of Cosine Annealing Scheduler


Languages

Language:Python 100.0%