File size: 23,903 Bytes
5b6f681 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 | <!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Transformer Sentiment Analysis - Demo</title>
<link rel="stylesheet" href="styles.css">
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/7.8.5/d3.min.js"></script>
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap" rel="stylesheet">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
</head>
<body>
<!-- Header -->
<header class="header">
<div class="container">
<div class="header-content">
<div class="logo">
<i class="fas fa-brain"></i>
<h1>Transformer Sentiment Analysis</h1>
</div>
<nav class="nav">
<a href="#demo" class="nav-link">Demo</a>
<a href="#interpretability" class="nav-link">Interpretability</a>
<a href="#metrics" class="nav-link">Metrics</a>
<a href="#architecture" class="nav-link">Architecture</a>
<a href="#about" class="nav-link">About</a>
</nav>
</div>
</div>
</header>
<!-- Hero Section -->
<section class="hero">
<div class="container">
<div class="hero-content">
<h2>Sentiment Analysis with DistilBERT</h2>
<p>Complete ML project with training, advanced inference, interpretability and production deployment</p>
<div class="hero-stats">
<div class="stat">
<span class="stat-number" id="model-accuracy">74%</span>
<span class="stat-label">Accuracy</span>
</div>
<div class="stat">
<span class="stat-number">66.9M</span>
<span class="stat-label">Parameters</span>
</div>
<div class="stat">
<span class="stat-number">~100ms</span>
<span class="stat-label">Inference Time</span>
</div>
</div>
</div>
</div>
</section>
<!-- Demo Section -->
<section id="demo" class="demo-section">
<div class="container">
<h3>Interactive Demo</h3>
<!-- API Status -->
<div class="api-status" id="api-status">
<i class="fas fa-circle"></i>
<span>Conectando a la API...</span>
</div>
<!-- Single Text Analysis -->
<div class="demo-card">
<h4><i class="fas fa-comment"></i> Individual Text Analysis</h4>
<div class="input-group">
<textarea
id="text-input"
placeholder="Write here the text you want to analyze... E.g.: 'This movie is incredible!'"
rows="3"
></textarea>
<button id="analyze-btn" class="btn-primary">
<i class="fas fa-search"></i>
Analyze
</button>
</div>
<!-- Results -->
<div id="single-result" class="result-card" style="display: none;">
<div class="result-header">
<h5>Resultado del Análisis</h5>
<span class="confidence-badge" id="confidence-badge"></span>
</div>
<div class="sentiment-display">
<div class="sentiment-icon" id="sentiment-icon"></div>
<div class="sentiment-text">
<span class="sentiment-label" id="sentiment-label"></span>
<span class="confidence-text" id="confidence-text"></span>
</div>
</div>
<div class="probability-chart">
<canvas id="probability-chart" width="400" height="200"></canvas>
</div>
</div>
</div>
<!-- Batch Analysis -->
<div class="demo-card">
<h4><i class="fas fa-list"></i> Batch Analysis</h4>
<div class="batch-input">
<textarea
id="batch-input"
placeholder="Enter multiple texts, one per line: This product is excellent I didn't like it at all It's okay, nothing more"
rows="4"
></textarea>
<button id="batch-analyze-btn" class="btn-secondary">
<i class="fas fa-layer-group"></i>
Analyze Batch
</button>
</div>
<div id="batch-results" class="batch-results" style="display: none;">
<h5>Batch Results</h5>
<div id="batch-results-list"></div>
<canvas id="batch-chart" width="400" height="300"></canvas>
</div>
</div>
<!-- Model Selection -->
<div class="demo-card">
<h4><i class="fas fa-cog"></i> Model Configuration</h4>
<div class="model-config">
<div class="config-group">
<label for="model-select">Model:</label>
<select id="model-select">
<option value="pretrained">DistilBERT Pre-trained</option>
<option value="custom">Fine-tuned Model (IMDB)</option>
</select>
</div>
<div class="config-group">
<label for="show-probabilities">
<input type="checkbox" id="show-probabilities" checked>
Show probability distribution
</label>
</div>
</div>
</div>
</div>
</section>
<!-- Interpretability Section -->
<section id="interpretability" class="interpretability-section">
<div class="container">
<h3>Model Interpretability</h3>
<p>Explore how the model makes decisions through attention visualizations and SHAP analysis</p>
<div class="interpretability-grid">
<!-- Input Card -->
<div class="demo-card">
<h4><i class="fas fa-microscope"></i> Interpretability Analysis</h4>
<div class="input-group">
<textarea
id="interpret-input"
placeholder="Write the text you want to analyze to understand how the model makes its decision..."
rows="3"
></textarea>
<button id="interpret-btn" class="btn-primary">
<i class="fas fa-search"></i>
Analyze Interpretability
</button>
</div>
<div id="interpret-prediction" class="prediction-result" style="display: none;">
<h5>Prediction</h5>
<div class="prediction-details">
<span class="prediction-label" id="interpret-pred-label"></span>
<span class="prediction-confidence" id="interpret-pred-confidence"></span>
</div>
</div>
</div>
<!-- Attention Visualization -->
<div class="demo-card interpretation-card">
<h4><i class="fas fa-eye"></i> Attention Visualization</h4>
<div id="attention-placeholder" class="info-placeholder">
<i class="fas fa-eye"></i>
<p>Analyze a text to see how the model's attention mechanism focuses on different words and phrases.</p>
<p class="placeholder-hint">The visualization will show:</p>
<ul class="feature-list">
<li><i class="fas fa-check-circle"></i> Attention patterns across all layers</li>
<li><i class="fas fa-check-circle"></i> Heatmap of token relationships</li>
<li><i class="fas fa-check-circle"></i> Interactive layer and head exploration</li>
</ul>
</div>
<div id="attention-loading" class="loading" style="display: none;">
<i class="fas fa-spinner fa-spin"></i> Generating visualizations...
</div>
<div id="attention-results" style="display: none;">
<div class="attention-tabs">
<button class="tab-btn active" data-tab="summary">Summary</button>
<button class="tab-btn" data-tab="heatmap">Heatmap</button>
<button class="tab-btn" data-tab="interactive">Interactive</button>
</div>
<div class="tab-content">
<div id="tab-summary" class="tab-panel active">
<img id="attention-summary-img" src="" alt="Attention summary" style="width: 100%; max-width: 600px; display: none;">
</div>
<div id="tab-heatmap" class="tab-panel">
<img id="attention-heatmap-img" src="" alt="Attention heatmap" style="width: 100%; max-width: 600px; display: none;">
</div>
<div id="tab-interactive" class="tab-panel">
<div id="interactive-attention" class="interactive-attention">
<div class="attention-controls">
<label>Layer: <select id="layer-select"></select></label>
<label>Head: <select id="head-select"></select></label>
</div>
<div id="attention-matrix" class="attention-matrix"></div>
</div>
</div>
</div>
</div>
</div>
<!-- SHAP Explanation -->
<div class="demo-card interpretation-card">
<h4><i class="fas fa-chart-line"></i> SHAP Explanation</h4>
<div id="shap-placeholder" class="info-placeholder">
<i class="fas fa-chart-line"></i>
<p>SHAP (SHapley Additive exPlanations) provides detailed feature importance analysis.</p>
<p class="placeholder-hint">Understanding SHAP values:</p>
<ul class="feature-list">
<li><i class="fas fa-check-circle"></i> Shows positive and negative contributions</li>
<li><i class="fas fa-check-circle"></i> Highlights impactful words in red/blue</li>
<li><i class="fas fa-check-circle"></i> Based on game theory principles</li>
</ul>
</div>
<div id="shap-results" style="display: none;">
<div class="shap-explanation">
<img id="shap-explanation-img" src="" alt="SHAP explanation" style="width: 100%; max-width: 600px; display: none;">
<div id="shap-not-available" style="display: none;">
<p><i class="fas fa-info-circle"></i> SHAP is not available for this model.</p>
</div>
</div>
</div>
</div>
<!-- Token Importance -->
<div class="demo-card interpretation-card">
<h4><i class="fas fa-weight-hanging"></i> Token Importance</h4>
<div id="token-placeholder" class="info-placeholder">
<i class="fas fa-weight-hanging"></i>
<p>See which words contribute most to the model's decision.</p>
<p class="placeholder-hint">This visualization shows:</p>
<ul class="feature-list">
<li><i class="fas fa-check-circle"></i> Relative importance of each token</li>
<li><i class="fas fa-check-circle"></i> Attention weight distribution</li>
<li><i class="fas fa-check-circle"></i> Key words influencing the prediction</li>
</ul>
</div>
<div id="token-importance" style="display: none;">
<div class="token-importance-viz">
<div id="token-bars"></div>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Metrics Section -->
<section id="metrics" class="metrics-section">
<div class="container">
<h3>Model Metrics</h3>
<div class="metrics-grid">
<!-- Training Metrics -->
<div class="metric-card">
<h4>Métricas de Entrenamiento</h4>
<div style="position: relative; height: 300px; width: 100%;">
<canvas id="training-chart"></canvas>
</div>
<div class="metric-details">
<div class="metric-item">
<span class="metric-label">Epochs:</span>
<span class="metric-value">3</span>
</div>
<div class="metric-item">
<span class="metric-label">Learning Rate:</span>
<span class="metric-value">2e-05</span>
</div>
<div class="metric-item">
<span class="metric-label">Batch Size:</span>
<span class="metric-value">16</span>
</div>
</div>
</div>
<!-- Performance Metrics -->
<div class="metric-card">
<h4>Rendimiento del Modelo</h4>
<div class="performance-metrics">
<div class="performance-item">
<div class="performance-circle" data-percentage="74">
<span>74%</span>
</div>
<label>Accuracy</label>
</div>
<div class="performance-item">
<div class="performance-circle" data-percentage="73">
<span>73%</span>
</div>
<label>F1-Score</label>
</div>
<div class="performance-item">
<div class="performance-circle" data-percentage="59">
<span>0.59</span>
</div>
<label>Loss</label>
</div>
</div>
</div>
<!-- Model Architecture -->
<div class="metric-card">
<h4>Arquitectura del Modelo</h4>
<div class="architecture-info">
<div class="arch-item">
<i class="fas fa-microchip"></i>
<span>DistilBERT-base-uncased</span>
</div>
<div class="arch-item">
<i class="fas fa-layer-group"></i>
<span>6 Transformer Layers</span>
</div>
<div class="arch-item">
<i class="fas fa-brain"></i>
<span>12 Attention Heads</span>
</div>
<div class="arch-item">
<i class="fas fa-database"></i>
<span>768 Hidden Size</span>
</div>
<div class="arch-item">
<i class="fas fa-book"></i>
<span>30,522 Vocabulary</span>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Architecture Section -->
<section id="architecture" class="architecture-section">
<div class="container">
<h3>Arquitectura del Sistema</h3>
<div class="architecture-diagram">
<div class="arch-component" data-component="data">
<i class="fas fa-database"></i>
<h4>Datos</h4>
<p>Dataset IMDB<br>50K reseñas</p>
</div>
<div class="arch-arrow">→</div>
<div class="arch-component" data-component="preprocessing">
<i class="fas fa-cogs"></i>
<h4>Preprocesamiento</h4>
<p>Tokenización<br>DistilBERT</p>
</div>
<div class="arch-arrow">→</div>
<div class="arch-component" data-component="model">
<i class="fas fa-brain"></i>
<h4>Modelo</h4>
<p>DistilBERT<br>Fine-tuning</p>
</div>
<div class="arch-arrow">→</div>
<div class="arch-component" data-component="api">
<i class="fas fa-server"></i>
<h4>API</h4>
<p>FastAPI<br>Inferencia</p>
</div>
<div class="arch-arrow">→</div>
<div class="arch-component" data-component="frontend">
<i class="fas fa-desktop"></i>
<h4>Frontend</h4>
<p>React/JS<br>UI Interactiva</p>
</div>
</div>
<!-- Tech Stack -->
<div class="tech-stack">
<h4>Stack Tecnológico</h4>
<div class="tech-grid">
<div class="tech-item">
<i class="fab fa-python"></i>
<span>Python</span>
</div>
<div class="tech-item">
<i class="fas fa-fire"></i>
<span>PyTorch</span>
</div>
<div class="tech-item">
<i class="fas fa-robot"></i>
<span>Transformers</span>
</div>
<div class="tech-item">
<i class="fas fa-rocket"></i>
<span>FastAPI</span>
</div>
<div class="tech-item">
<i class="fab fa-docker"></i>
<span>Docker</span>
</div>
<div class="tech-item">
<i class="fab fa-js-square"></i>
<span>JavaScript</span>
</div>
</div>
</div>
</div>
</section>
<!-- About Section -->
<section id="about" class="about-section">
<div class="container">
<h3>Acerca del Proyecto</h3>
<div class="about-content">
<div class="about-text">
<p>Este proyecto demuestra una implementación completa de análisis de sentimientos usando Transformers,
desde el entrenamiento hasta el deployment en producción.</p>
<h4>Características Principales:</h4>
<ul>
<li><i class="fas fa-check"></i> Fine-tuning de DistilBERT en dataset IMDB</li>
<li><i class="fas fa-check"></i> API de producción con FastAPI</li>
<li><i class="fas fa-check"></i> Procesamiento por lotes optimizado</li>
<li><i class="fas fa-check"></i> Visualización de métricas en tiempo real</li>
<li><i class="fas fa-check"></i> Interpretabilidad con attention weights</li>
<li><i class="fas fa-check"></i> Deployment con Docker</li>
<li><i class="fas fa-check"></i> Testing comprehensivo</li>
</ul>
</div>
<div class="about-stats">
<div class="stat-box">
<h4>Rendimiento</h4>
<p>Accuracy: 74%<br>
Latencia: ~100ms<br>
Throughput: 1000+ req/s</p>
</div>
<div class="stat-box">
<h4>Escalabilidad</h4>
<p>Horizontal scaling<br>
Load balancing<br>
Auto-restart</p>
</div>
</div>
</div>
</div>
</section>
<!-- Footer -->
<footer class="footer">
<div class="container">
<div class="footer-content">
<div class="footer-section">
<h4>Transformer Sentiment Analysis</h4>
<p>Proyecto demostrativo de ML en producción</p>
</div>
<div class="footer-section">
<h4>Enlaces</h4>
<a href="#demo">Demo</a>
<a href="#metrics">Métricas</a>
<a href="#architecture">Arquitectura</a>
</div>
<div class="footer-section">
<h4>Tecnologías</h4>
<a href="https://huggingface.co/transformers/">Transformers</a>
<a href="https://pytorch.org/">PyTorch</a>
<a href="https://fastapi.tiangolo.com/">FastAPI</a>
</div>
</div>
<div class="footer-bottom">
<p>© 2025 Transformer Sentiment Analysis Project</p>
</div>
</div>
</footer>
<!-- Loading Overlay -->
<div id="loading-overlay" class="loading-overlay" style="display: none;">
<div class="spinner"></div>
<p>Analizando texto...</p>
</div>
<script src="app.js"></script>
</body>
</html> |