PlaygroundOrganizer / Blog /convergence_plot_demo.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Convergence Plot - Model Fitting</title>
<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/3.9.1/chart.min.js"></script>
<style>
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
min-height: 100vh;
padding: 20px;
}
.container {
max-width: 1200px;
margin: 0 auto;
background: white;
border-radius: 20px;
padding: 30px;
box-shadow: 0 20px 60px rgba(0,0,0,0.3);
}
h1 {
text-align: center;
color: #333;
margin-bottom: 30px;
font-size: 2em;
}
.controls {
display: flex;
justify-content: center;
gap: 15px;
margin-bottom: 30px;
flex-wrap: wrap;
}
button {
padding: 12px 30px;
font-size: 16px;
border: none;
border-radius: 8px;
cursor: pointer;
transition: all 0.3s;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.5px;
}
button:hover {
transform: translateY(-2px);
box-shadow: 0 5px 15px rgba(0,0,0,0.2);
}
.btn-underfit {
background: #3498db;
color: white;
}
.btn-bestfit {
background: #2ecc71;
color: white;
}
.btn-overfit {
background: #e74c3c;
color: white;
}
.chart-container {
position: relative;
height: 400px;
margin-bottom: 30px;
}
.info-box {
background: #f8f9fa;
border-left: 5px solid #667eea;
padding: 20px;
border-radius: 8px;
margin-top: 20px;
}
.info-box h3 {
color: #667eea;
margin-bottom: 10px;
}
.info-box p {
color: #555;
line-height: 1.6;
margin-bottom: 10px;
}
.legend {
display: flex;
justify-content: center;
gap: 30px;
margin-top: 20px;
flex-wrap: wrap;
}
.legend-item {
display: flex;
align-items: center;
gap: 8px;
}
.legend-color {
width: 30px;
height: 4px;
border-radius: 2px;
}
.train { background: #3498db; }
.val { background: #e74c3c; }
</style>
</head>
<body>
<div class="container">
<h1>📊 Model Convergence Playground</h1>
<div class="controls">
<button class="btn-underfit" onclick="showUnderfitting()">Underfitting</button>
<button class="btn-bestfit" onclick="showBestFit()">Best Fit</button>
<button class="btn-overfit" onclick="showOverfitting()">Overfitting</button>
</div>
<div class="chart-container">
<canvas id="convergenceChart"></canvas>
</div>
<div class="legend">
<div class="legend-item">
<div class="legend-color train"></div>
<span>Training Loss</span>
</div>
<div class="legend-item">
<div class="legend-color val"></div>
<span>Validation Loss</span>
</div>
</div>
<div class="info-box" id="infoBox">
<h3>Select a scenario to begin</h3>
<p>Click one of the buttons above to see how different model fitting scenarios affect convergence.</p>
</div>
</div>
<script>
let chart;
const ctx = document.getElementById('convergenceChart').getContext('2d');
const scenarios = {
underfit: {
title: '🔵 Underfitting (High Bias)',
description: 'The model is too simple to capture the underlying patterns in the data.',
characteristics: [
'• Both training and validation losses remain high',
'• The model has not learned enough from the data',
'• Poor performance on both training and validation sets',
'• Solution: Increase model complexity, add more features, or train longer'
],
trainLoss: [0.8, 0.72, 0.68, 0.65, 0.63, 0.62, 0.61, 0.605, 0.602, 0.60],
valLoss: [0.82, 0.75, 0.70, 0.68, 0.66, 0.65, 0.64, 0.635, 0.632, 0.63]
},
bestfit: {
title: '🟢 Best Fit (Good Generalization)',
description: 'The model has learned the underlying patterns without memorizing noise.',
characteristics: [
'• Both losses decrease together and converge to low values',
'• Small gap between training and validation loss',
'• Model generalizes well to unseen data',
'• This is the ideal scenario for deployment'
],
trainLoss: [0.9, 0.65, 0.45, 0.32, 0.23, 0.17, 0.13, 0.10, 0.08, 0.07],
valLoss: [0.92, 0.68, 0.48, 0.35, 0.26, 0.20, 0.16, 0.13, 0.11, 0.10]
},
overfit: {
title: '🔴 Overfitting (High Variance)',
description: 'The model has memorized the training data including its noise and outliers.',
characteristics: [
'• Training loss continues to decrease',
'• Validation loss starts increasing after initial decrease',
'• Large gap between training and validation performance',
'• Solution: Add regularization, use dropout, get more data, or early stopping'
],
trainLoss: [0.9, 0.6, 0.4, 0.25, 0.15, 0.08, 0.04, 0.02, 0.01, 0.005],
valLoss: [0.92, 0.65, 0.45, 0.35, 0.32, 0.35, 0.42, 0.50, 0.58, 0.65]
}
};
function createChart(trainData, valData) {
if (chart) {
chart.destroy();
}
const epochs = Array.from({length: trainData.length}, (_, i) => i + 1);
chart = new Chart(ctx, {
type: 'line',
data: {
labels: epochs,
datasets: [{
label: 'Training Loss',
data: trainData,
borderColor: '#3498db',
backgroundColor: 'rgba(52, 152, 219, 0.1)',
borderWidth: 3,
tension: 0.4,
pointRadius: 5,
pointHoverRadius: 7
}, {
label: 'Validation Loss',
data: valData,
borderColor: '#e74c3c',
backgroundColor: 'rgba(231, 76, 60, 0.1)',
borderWidth: 3,
tension: 0.4,
pointRadius: 5,
pointHoverRadius: 7
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
display: false
},
tooltip: {
mode: 'index',
intersect: false
}
},
scales: {
x: {
title: {
display: true,
text: 'Epoch',
font: { size: 14, weight: 'bold' }
},
grid: { color: '#e0e0e0' }
},
y: {
title: {
display: true,
text: 'Loss',
font: { size: 14, weight: 'bold' }
},
beginAtZero: true,
grid: { color: '#e0e0e0' }
}
}
}
});
}
function updateInfo(scenario) {
const info = scenarios[scenario];
const infoBox = document.getElementById('infoBox');
infoBox.innerHTML = `
<h3>${info.title}</h3>
<p><strong>${info.description}</strong></p>
<p><strong>Characteristics:</strong></p>
${info.characteristics.map(c => `<p>${c}</p>`).join('')}
`;
}
function showUnderfitting() {
createChart(scenarios.underfit.trainLoss, scenarios.underfit.valLoss);
updateInfo('underfit');
}
function showBestFit() {
createChart(scenarios.bestfit.trainLoss, scenarios.bestfit.valLoss);
updateInfo('bestfit');
}
function showOverfitting() {
createChart(scenarios.overfit.trainLoss, scenarios.overfit.valLoss);
updateInfo('overfit');
}
// Initialize with best fit
showBestFit();
</script>
</body>
</html>