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<html lang="en" data-theme="light">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta name="description" content="Parlay β Training Dashboard. GRPO reward curves and model comparison." />
<title>Parlay β Training Dashboard</title>
<link rel="icon" type="image/svg+xml" href="/static/favicon/favicon.svg?v=1" />
<link rel="icon" type="image/x-icon" href="/favicon.ico" />
<!-- Chart.js 4.4.1 (no Three.js needed here) -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/4.4.1/chart.umd.js"
crossorigin="anonymous" referrerpolicy="no-referrer"></script>
<link rel="stylesheet" href="/static/style.css" />
</head>
<body>
<!-- βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
HEADER
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ -->
<header class="app-header" role="banner">
<div class="header-brand">
<span class="brand-dot" aria-hidden="true"></span>
<span>Parlay</span>
<span class="stat-chip blue" style="margin-left: 8px; font-size: 0.6875rem;">Training</span>
</div>
<nav class="header-nav" aria-label="Site navigation">
<a href="/index.html">Game</a>
<a href="/train.html" class="active">Training</a>
</nav>
<div class="header-actions">
<button
id="dark-toggle"
class="dark-toggle"
type="button"
aria-label="Toggle dark mode"
title="Toggle dark mode"
></button>
</div>
</header>
<!-- βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
MAIN
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ -->
<main style="max-width: 1200px; margin: 0 auto; padding: 24px 16px;" role="main">
<!-- Page title row -->
<div class="flex items-center gap-4 mb-4" style="margin-bottom: 24px;">
<div>
<h1 style="font-size: 1.375rem; font-weight: 800; letter-spacing: -0.02em; color: var(--parlay-ink);">
Training Dashboard
</h1>
<p style="font-size: 0.875rem; color: var(--parlay-ink-3); margin-top: 2px;">
GRPO fine-tuning on Qwen2.5-1.5B-Instruct Β· Parlay reward functions
</p>
</div>
<div style="margin-left: auto; display: flex; gap: 8px; align-items: center;">
<span id="training-status-chip" class="stat-chip blue">Ready</span>
<button id="btn-run-training" class="btn btn-primary" type="button" onclick="runTraining()">
βΆ Run Training
</button>
</div>
</div>
<!-- ββ MODEL COMPARISON CARDS ββββββββββββββββββββββββββββ -->
<div class="train-grid" style="margin-bottom: 24px;">
<!-- Base Model -->
<div class="model-card">
<div class="model-tag base">Base</div>
<div style="font-size: 0.8125rem; font-weight: 600; color: var(--parlay-ink); margin-bottom: 12px;">
Qwen2.5-1.5B-Instruct
</div>
<div class="metric-row">
<span class="metric-name">Avg Reward</span>
<span id="base-reward" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Deal Rate</span>
<span id="base-deal-rate" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ZOPA Efficiency</span>
<span id="base-zopa-eff" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ToM Accuracy</span>
<span id="base-tom-acc" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Drift Adapt.</span>
<span id="base-drift-adapt" class="metric-val">β</span>
</div>
</div>
<!-- SFT Model -->
<div class="model-card">
<div class="model-tag sft">SFT</div>
<div style="font-size: 0.8125rem; font-weight: 600; color: var(--parlay-ink); margin-bottom: 12px;">
Qwen2.5-1.5B + SFT Warmup
</div>
<div class="metric-row">
<span class="metric-name">Avg Reward</span>
<span id="sft-reward" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Deal Rate</span>
<span id="sft-deal-rate" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ZOPA Efficiency</span>
<span id="sft-zopa-eff" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ToM Accuracy</span>
<span id="sft-tom-acc" class="metric-val">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Drift Adapt.</span>
<span id="sft-drift-adapt" class="metric-val">β</span>
</div>
</div>
<!-- GRPO Model -->
<div class="model-card highlight">
<div class="model-tag grpo">GRPO</div>
<div style="font-size: 0.8125rem; font-weight: 600; color: var(--parlay-ink); margin-bottom: 12px;">
Qwen2.5-1.5B + SFT + GRPO
</div>
<div class="metric-row">
<span class="metric-name">Avg Reward</span>
<span id="grpo-reward" class="metric-val positive">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Deal Rate</span>
<span id="grpo-deal-rate" class="metric-val positive">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ZOPA Efficiency</span>
<span id="grpo-zopa-eff" class="metric-val positive">β</span>
</div>
<div class="metric-row">
<span class="metric-name">ToM Accuracy</span>
<span id="grpo-tom-acc" class="metric-val positive">β</span>
</div>
<div class="metric-row">
<span class="metric-name">Drift Adapt.</span>
<span id="grpo-drift-adapt" class="metric-val positive">β</span>
</div>
</div>
</div>
<!-- ββ REWARD CURVE CHART βββββββββββββββββββββββββββββββ -->
<div class="chart-panel" style="margin-bottom: 24px;">
<div style="display: flex; align-items: center; justify-content: space-between; margin-bottom: 16px;">
<h2 style="font-size: 1rem; font-weight: 700; color: var(--parlay-ink);">Reward Curve</h2>
<div style="display: flex; gap: 8px;">
<button class="btn btn-ghost btn-sm" type="button" onclick="loadEvalResults()">β» Refresh</button>
<button class="btn btn-ghost btn-sm" type="button" onclick="switchChartView('comparison')" id="tab-comparison">Comparison</button>
<button class="btn btn-ghost btn-sm" type="button" onclick="switchChartView('live')" id="tab-live">Live Curve</button>
<button class="btn btn-ghost btn-sm" type="button" onclick="switchChartView('radar')" id="tab-radar">Radar</button>
</div>
</div>
<div id="chart-comparison-wrap" style="height: 300px; position: relative;">
<canvas id="comparison-chart" aria-label="Model comparison bar chart"></canvas>
</div>
<div id="chart-live-wrap" style="height: 300px; position: relative; display: none;">
<canvas id="live-reward-chart" aria-label="Live GRPO training reward curve"></canvas>
</div>
<div id="chart-radar-wrap" style="height: 300px; position: relative; display: none;">
<canvas id="radar-chart" aria-label="Efficiency radar chart"></canvas>
</div>
</div>
<!-- ββ TRAINING CONFIG βββββββββββββββββββββββββββββββββ -->
<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 24px; margin-bottom: 24px;">
<!-- GRPO Hyperparams -->
<div class="panel">
<div class="panel-header">
<span class="panel-title">GRPO Configuration</span>
</div>
<div class="config-grid">
<div class="config-item">
<span class="config-key">Base Model</span>
<span id="cfg-base-model" class="config-val">Qwen/Qwen2.5-1.5B-Instruct</span>
</div>
<div class="config-item">
<span class="config-key">Generations (G)</span>
<span class="config-val">8</span>
</div>
<div class="config-item">
<span class="config-key">KL Ξ² (beta)</span>
<span class="config-val">0.001</span>
</div>
<div class="config-item">
<span class="config-key">Clip Ξ΅ (epsilon)</span>
<span class="config-val">0.2</span>
</div>
<div class="config-item">
<span class="config-key">Learning Rate</span>
<span class="config-val">5e-7</span>
</div>
<div class="config-item">
<span class="config-key">Reward Scale</span>
<span class="config-val">batch</span>
</div>
<div class="config-item">
<span class="config-key">LoRA r</span>
<span class="config-val">16</span>
</div>
<div class="config-item">
<span class="config-key">LoRA Ξ±</span>
<span class="config-val">32</span>
</div>
<div class="config-item">
<span class="config-key">Target Modules</span>
<span class="config-val">q_proj, v_proj</span>
</div>
<div class="config-item">
<span class="config-key">Top Player ΞΈ</span>
<span id="cfg-top-threshold" class="config-val">0.60</span>
</div>
</div>
</div>
<!-- Data Generation Config -->
<div class="panel">
<div class="panel-header">
<span class="panel-title">Data Generation</span>
</div>
<div class="config-grid">
<div class="config-item">
<span class="config-key">Min Episodes</span>
<span class="config-val">500</span>
</div>
<div class="config-item">
<span class="config-key">Per Pair Min</span>
<span class="config-val">20</span>
</div>
<div class="config-item">
<span class="config-key">Noise Rate</span>
<span class="config-val">30%</span>
</div>
<div class="config-item">
<span class="config-key">Drift Rate</span>
<span class="config-val">40%</span>
</div>
<div class="config-item">
<span class="config-key">Coalition (Act 3)</span>
<span class="config-val">25%</span>
</div>
<div class="config-item">
<span class="config-key">Train / Eval Split</span>
<span class="config-val">90 / 10</span>
</div>
<div class="config-item">
<span class="config-key">LLM Generator</span>
<span class="config-val">Gemini 2.0 Flash</span>
</div>
<div class="config-item">
<span class="config-key">Personas Γ Scenarios</span>
<span class="config-val">5 Γ 5 = 25</span>
</div>
</div>
</div>
</div>
<!-- ββ HOW TO RUN ββββββββββββββββββββββββββββββββββββββββ -->
<div class="panel" style="margin-bottom: 24px;">
<div class="panel-header">
<span class="panel-title">Run Training Pipeline</span>
</div>
<div style="display: flex; gap: 32px; flex-wrap: wrap;">
<div class="steps-list" style="flex: 1; min-width: 280px;">
<div class="step-item">
<div class="step-num">1</div>
<div class="step-text">
Install dependencies and set environment variables:<br />
<code class="step-code">pip install -r requirements.txt</code>
then set <code class="step-code">GOOGLE_API_KEY</code> and <code class="step-code">HF_TOKEN</code>.
</div>
</div>
<div class="step-item">
<div class="step-num">2</div>
<div class="step-text">
Generate self-play training data via Gemini:<br />
<code class="step-code">python -m training.generate_data --episodes 500</code>
</div>
</div>
<div class="step-item">
<div class="step-num">3</div>
<div class="step-text">
SFT warmup on top-player episodes:<br />
<code class="step-code">python -m training.sft_train</code>
</div>
</div>
<div class="step-item">
<div class="step-num">4</div>
<div class="step-text">
GRPO fine-tuning with Parlay reward functions:<br />
<code class="step-code">python -m training.grpo_train</code>
</div>
</div>
<div class="step-item">
<div class="step-num">5</div>
<div class="step-text">
Evaluate and generate the comparison chart:<br />
<code class="step-code">python -m training.evaluate --output results/</code>
</div>
</div>
<div class="step-item">
<div class="step-num">6</div>
<div class="step-text">
Push to Hugging Face Hub:<br />
<code class="step-code">python -m training.push_to_hub</code>
</div>
</div>
</div>
<!-- Reward function breakdown -->
<div style="flex: 1; min-width: 240px;">
<div class="panel-title" style="margin-bottom: 12px;">Reward Function Weights</div>
<div class="metric-row">
<span class="metric-name">Deal Efficiency (ZOPA)</span>
<span class="metric-val">0.35</span>
</div>
<div class="metric-row">
<span class="metric-name">Capitulation Cliff penalty</span>
<span class="metric-val negative">βΞ©</span>
</div>
<div class="metric-row">
<span class="metric-name">ToM Accuracy</span>
<span class="metric-val">0.20</span>
</div>
<div class="metric-row">
<span class="metric-name">Drift Adaptation</span>
<span class="metric-val">0.15</span>
</div>
<div class="metric-row">
<span class="metric-name">Move Diversity</span>
<span class="metric-val">0.10</span>
</div>
<div class="metric-row">
<span class="metric-name">Act Completion Bonus</span>
<span class="metric-val">0.10</span>
</div>
<div class="metric-row">
<span class="metric-name">Format Validity</span>
<span class="metric-val">0.10</span>
</div>
</div>
</div>
</div>
<!-- ββ TRAINING PROGRESS ββββββββββββββββββββββββββββββββ -->
<div class="training-progress-wrap" style="margin-bottom: 24px;">
<div class="panel-header">
<span class="panel-title">Training Progress</span>
<span id="training-step-label" class="text-xs text-muted mono">Step 0 / β</span>
</div>
<div class="training-progress-bar-track">
<div id="training-progress-fill" class="training-progress-bar-fill" style="width: 0%;"></div>
</div>
<div style="display: flex; justify-content: space-between; margin-top: 4px; font-size: 0.6875rem; color: var(--parlay-ink-3);">
<span>SFT Data Gen</span>
<span>SFT Train</span>
<span>GRPO Train</span>
<span>Evaluate</span>
</div>
</div>
<!-- ββ TRAINING LOG βββββββββββββββββββββββββββββββββββββ -->
<div class="panel">
<div class="panel-header">
<span class="panel-title">Training Log</span>
<div style="display: flex; gap: 8px;">
<button class="btn btn-ghost btn-sm" type="button" onclick="clearLog()">Clear</button>
<button class="btn btn-ghost btn-sm" type="button" onclick="refreshLog()">β»</button>
</div>
</div>
<div id="training-log" class="training-log" role="log" aria-live="polite" aria-label="Training log output">
<span class="log-line info">[ Parlay Training Dashboard ]</span>
<span class="log-line">Ready. Click "Run Training" to begin, or use the CLI commands above.</span>
</div>
</div>
</main>
<!-- ββ Training scripts ββββββββββββββββββββββββββββββββββββ -->
<script src="/static/chart.js"></script>
<script>
// ββ Dark mode βββββββββββββββββββββββββββββββββββββββββββββ
(function() {
const saved = localStorage.getItem("parlay-theme");
const prefersDark = window.matchMedia("(prefers-color-scheme: dark)").matches;
const theme = saved || (prefersDark ? "dark" : "light");
document.documentElement.setAttribute("data-theme", theme);
const toggle = document.getElementById("dark-toggle");
if (toggle) {
toggle.addEventListener("click", () => {
const current = document.documentElement.getAttribute("data-theme");
const next = current === "dark" ? "light" : "dark";
document.documentElement.setAttribute("data-theme", next);
localStorage.setItem("parlay-theme", next);
});
}
})();
// ββ Chart instances ββββββββββββββββββββββββββββββββββββββββ
const charts = new ParlayCharts();
let activeView = "comparison";
// ββ Init on load βββββββββββββββββββββββββββββββββββββββββββ
document.addEventListener("DOMContentLoaded", () => {
loadEvalResults();
// Try to fetch config from API
fetch("/api/training/config")
.then(r => r.ok ? r.json() : null)
.then(data => {
if (!data) return;
const baseEl = document.getElementById("cfg-base-model");
const thrEl = document.getElementById("cfg-top-threshold");
if (baseEl && data.base_model) baseEl.textContent = data.base_model;
if (thrEl && data.top_threshold) thrEl.textContent = data.top_threshold;
})
.catch(() => {});
});
// ββ Load evaluation results ββββββββββββββββββββββββββββββββ
async function loadEvalResults() {
try {
const res = await fetch("/api/training/results");
if (!res.ok) {
_useFallbackData();
return;
}
const data = await res.json();
_populateMetrics(data);
_initCharts(data);
} catch {
_useFallbackData();
}
}
function _useFallbackData() {
// Demo data so charts aren't empty
const demo = {
base: { reward: 0.21, deal_rate: 0.34, zopa_eff: 0.48, tom_acc: 0.31, drift_adapt: 0.29 },
sft: { reward: 0.44, deal_rate: 0.56, zopa_eff: 0.63, tom_acc: 0.52, drift_adapt: 0.51 },
grpo: { reward: 0.71, deal_rate: 0.74, zopa_eff: 0.82, tom_acc: 0.69, drift_adapt: 0.73 },
};
_populateMetrics(demo);
_initCharts(demo);
_appendLog("warn", "Could not reach /api/training/results β using demo data.");
}
function _populateMetrics(data) {
const models = ["base", "sft", "grpo"];
const fields = [
["reward", "reward"],
["deal-rate", "deal_rate"],
["zopa-eff", "zopa_eff"],
["tom-acc", "tom_acc"],
["drift-adapt", "drift_adapt"],
];
models.forEach(m => {
const mData = data[m];
if (!mData) return;
fields.forEach(([htmlId, key]) => {
const el = document.getElementById(`${m}-${htmlId}`);
if (!el) return;
const val = mData[key];
if (val == null) return;
el.textContent = (typeof val === "number" && val < 2) ? val.toFixed(3) : val.toFixed(1);
if (m === "grpo") {
const sftVal = data.sft?.[key];
if (sftVal != null && val > sftVal) el.classList.add("positive");
else if (sftVal != null && val < sftVal) el.classList.add("negative");
}
});
});
}
function _initCharts(data) {
const compData = {
labels: ["Reward", "Deal Rate", "ZOPA Eff.", "ToM Acc.", "Drift Adapt."],
base: [data.base?.reward, data.base?.deal_rate, data.base?.zopa_eff, data.base?.tom_acc, data.base?.drift_adapt],
sft: [data.sft?.reward, data.sft?.deal_rate, data.sft?.zopa_eff, data.sft?.tom_acc, data.sft?.drift_adapt],
grpo: [data.grpo?.reward, data.grpo?.deal_rate, data.grpo?.zopa_eff, data.grpo?.tom_acc, data.grpo?.drift_adapt],
};
charts.initComparisonChart("comparison-chart", compData);
charts.initLiveRewardChart("live-reward-chart");
charts.initEfficiencyRadar("radar-chart", {
base: compData.base,
grpo: compData.grpo,
});
// Populate live chart with training history if available
if (data.training_history && Array.isArray(data.training_history)) {
data.training_history.forEach(({ step, reward, sft_baseline }) => {
charts.updateLiveReward(step, reward, sft_baseline);
});
}
}
// ββ Chart view switcher ββββββββββββββββββββββββββββββββββββ
function switchChartView(view) {
activeView = view;
const views = ["comparison", "live", "radar"];
views.forEach(v => {
const wrap = document.getElementById(`chart-${v}-wrap`);
const tab = document.getElementById(`tab-${v}`);
if (wrap) wrap.style.display = v === view ? "block" : "none";
if (tab) tab.style.fontWeight = v === view ? "700" : "400";
});
}
// ββ Run training via API βββββββββββββββββββββββββββββββββββ
async function runTraining() {
const btn = document.getElementById("btn-run-training");
const status = document.getElementById("training-status-chip");
btn.disabled = true;
btn.textContent = "Runningβ¦";
if (status) { status.textContent = "Running"; status.className = "stat-chip amber"; }
_appendLog("info", "βΆ Training run requested via dashboardβ¦");
_appendLog("info", "POST /api/training/run");
try {
const res = await fetch("/api/training/run", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ stages: ["data_gen", "sft", "grpo", "evaluate"] }),
});
if (!res.ok) {
const err = await res.json().catch(() => ({}));
throw new Error(err.detail || `HTTP ${res.status}`);
}
const data = await res.json();
_appendLog("success", "Training pipeline started. Run ID: " + (data.run_id || "β"));
_appendLog("info", "Monitor progress via CLI or refresh this page.");
if (status) { status.textContent = "Running"; status.className = "stat-chip amber"; }
// Poll for progress
_startProgressPoll(data.run_id);
} catch (e) {
_appendLog("error", "Error: " + e.message);
_appendLog("warn", "Start training manually: python -m training.grpo_train");
if (status) { status.textContent = "Error"; status.className = "stat-chip red"; }
} finally {
btn.disabled = false;
btn.textContent = "βΆ Run Training";
}
}
// ββ Progress polling βββββββββββββββββββββββββββββββββββββββ
let _pollInterval = null;
function _startProgressPoll(runId) {
if (_pollInterval) clearInterval(_pollInterval);
_pollInterval = setInterval(async () => {
try {
const url = runId ? `/api/training/status/${runId}` : "/api/training/status";
const res = await fetch(url);
if (!res.ok) return;
const data = await res.json();
_updateProgress(data);
if (data.status === "complete" || data.status === "error") {
clearInterval(_pollInterval);
_pollInterval = null;
const status = document.getElementById("training-status-chip");
if (status) {
status.textContent = data.status === "complete" ? "Done" : "Error";
status.className = data.status === "complete" ? "stat-chip green" : "stat-chip red";
}
if (data.status === "complete") {
_appendLog("success", "β Training complete. Refreshing resultsβ¦");
setTimeout(loadEvalResults, 1000);
} else {
_appendLog("error", "Training failed: " + (data.error || "unknown error"));
}
}
// Stream live reward updates
if (data.step != null && data.reward != null) {
charts.updateLiveReward(data.step, data.reward, data.sft_baseline);
if (activeView !== "live") switchChartView("live");
}
if (data.log_line) {
_appendLog("info", data.log_line);
}
} catch {}
}, 2000);
}
function _updateProgress(data) {
const fill = document.getElementById("training-progress-fill");
const label = document.getElementById("training-step-label");
const pct = data.progress_pct ?? 0;
if (fill) fill.style.width = `${pct}%`;
if (label) label.textContent = `Step ${data.step ?? 0} / ${data.total_steps ?? "β"}`;
}
// ββ Log helpers ββββββββββββββββββββββββββββββββββββββββββββ
function _appendLog(level, text) {
const log = document.getElementById("training-log");
if (!log) return;
const line = document.createElement("span");
line.className = `log-line ${level}`;
const ts = new Date().toLocaleTimeString("en-US", { hour12: false });
line.textContent = `[${ts}] ${text}`;
log.appendChild(document.createTextNode("\n"));
log.appendChild(line);
log.scrollTop = log.scrollHeight;
}
async function refreshLog() {
try {
const res = await fetch("/api/training/log?limit=50");
if (!res.ok) return;
const data = await res.json();
const log = document.getElementById("training-log");
if (!log || !data.lines) return;
log.innerHTML = "";
data.lines.forEach(line => {
const el = document.createElement("span");
el.className = "log-line " + (line.level || "");
el.textContent = line.text || line;
log.appendChild(el);
log.appendChild(document.createTextNode("\n"));
});
log.scrollTop = log.scrollHeight;
} catch {}
}
function clearLog() {
const log = document.getElementById("training-log");
if (log) {
log.innerHTML = "";
const el = document.createElement("span");
el.className = "log-line info";
el.textContent = "[ Log cleared ]";
log.appendChild(el);
}
}
</script>
</body>
</html>
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