| <title>Pickplace Run v1</title> | |
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| </style> | |
| <div class="wrap"> | |
| <header> | |
| <div class="runline"> | |
| <h1>pickplace_full_v1</h1> | |
| <span class="pill"><span class="dot"></span><span class="mono" id="pillTxt">running</span></span> | |
| </div> | |
| <div class="chips mono"> | |
| <span class="chip">pi0.5 <b>full fine-tune</b></span> | |
| <span class="chip">batch <b>32</b></span> | |
| <span class="chip">lr <b>5e-5</b></span> | |
| <span class="chip">ema <b>0.999</b></span> | |
| <span class="chip">horizon <b>50</b></span> | |
| <span class="chip">A100 80GB <b id="chipRate"></b></span> | |
| </div> | |
| </header> | |
| <section class="card pad"> | |
| <div class="rail-head"> | |
| <div> | |
| <div class="lbl" style="margin-bottom:7px">Progress</div> | |
| <div class="rail-now mono"><span id="railPct"></span></div> | |
| </div> | |
| <div style="text-align:right"> | |
| <div class="lbl" style="margin-bottom:7px">Step</div> | |
| <div class="rail-now mono" id="railStep"></div> | |
| </div> | |
| </div> | |
| <div class="rail" id="rail"> | |
| <div class="rail-fill" id="railFill"></div> | |
| </div> | |
| <div class="rail-axis" id="railAxis"></div> | |
| <div class="rail-key mono" id="railKey"></div> | |
| </section> | |
| <div class="kpis" id="kpis"></div> | |
| <section class="card pad"> | |
| <div class="chart-head"> | |
| <div> | |
| <h2><span class="keyline" style="background:var(--s1)"></span>Flow-matching loss</h2> | |
| <p>Log scale — the value spans 101×. One loss is all pi0.5 reports; the vision-language | |
| backbone is trained by gradient flow from this same MSE.</p> | |
| </div> | |
| <div style="text-align:right" class="mono"> | |
| <div class="lbl">latest</div> | |
| <div style="font-size:17px;font-weight:650" id="lossNow"></div> | |
| </div> | |
| </div> | |
| <figure><svg class="plot" id="cLoss" height="290" tabindex="0" role="img" | |
| aria-label="Flow-matching loss against training step, log scale, falling from 1.03 to 0.011 and flattening"></svg></figure> | |
| </section> | |
| <div class="pair"> | |
| <section class="card pad"> | |
| <div class="chart-head"><div> | |
| <h2><span class="keyline" style="background:var(--s2)"></span>Gradient norm</h2> | |
| <p>Log scale. Bounded and settling is healthy; a sustained climb is not.</p> | |
| </div></div> | |
| <figure><svg class="plot" id="cGrad" height="200" tabindex="0" role="img" | |
| aria-label="Gradient norm against training step, log scale, falling from 4.38 to 0.066"></svg></figure> | |
| </section> | |
| <section class="card pad"> | |
| <div class="chart-head"><div> | |
| <h2><span class="keyline" style="background:var(--s3)"></span>Parameter norm</h2> | |
| <p>Linear, narrow band. Rising means the weights are actually moving.</p> | |
| </div></div> | |
| <figure><svg class="plot" id="cParam" height="200" tabindex="0" role="img" | |
| aria-label="Parameter norm against training step, rising from 1802.4 to 1835.7"></svg></figure> | |
| </section> | |
| </div> | |
| <section class="card pad"> | |
| <details> | |
| <summary>Table view — every logged point</summary> | |
| <div class="scroll"><table class="mono"> | |
| <thead><tr><th>Step</th><th>Epochs</th><th>Loss</th><th>Grad norm</th><th>Param norm</th><th>Checkpoint</th></tr></thead> | |
| <tbody id="tbody"></tbody> | |
| </table></div> | |
| </details> | |
| </section> | |
| <section class="card pad notes"> | |
| <div class="lbl">Reading this</div> | |
| <div class="note"><span class="n">1</span><div><b>The loss log lags the run.</b> | |
| Telemetry stops at step <span class="mono" id="nLogged"></span> while the run is at | |
| <span class="mono" id="nCur"></span> — Python block-buffers stdout when it is piped, so | |
| <code>tee</code> receives the lines late. Add <code>PYTHONUNBUFFERED=1</code> to see it live.</div></div> | |
| <div class="note"><span class="n">2</span><div><b>The absolute value reads low by construction.</b> | |
| 11 of the 32 action dimensions are constants — 7 left-hand joints commanded to exactly 0, | |
| plus 4 padding dims — so roughly a third of the mean squared error is over channels with | |
| nothing to predict. Compare the curve to itself, never to another dataset.</div></div> | |
| <div class="note"><span class="n">3</span><div><b>The curve has stopped discriminating.</b> | |
| Over the last 2,000 logged steps the mean loss moved | |
| <span class="mono" id="nFlat"></span> — smaller than the step-to-step noise. Every | |
| checkpoint from here on is indistinguishable <em>by loss</em>, which is not the same as | |
| equivalent on the robot.</div></div> | |
| <div class="note"><span class="n">4</span><div><b>So pick by rollout, not by this page.</b> | |
| Two checkpoints with equal loss can differ by tens of points of success rate, and nothing | |
| plotted here measures grasp success. Choosing among the | |
| <span class="mono" id="nKeptNote"></span> surviving checkpoints needs real-robot trials from a | |
| fixed object-placement grid.</div></div> | |
| </section> | |
| <footer class="mono">Parsed from train_v1.log · <span id="nPts"></span> logged points | |
| · the pruner keeps step 7,500 and later; 10 survive to the end</footer> | |
| </div> | |
| <div class="tip" id="tip" role="status" aria-live="polite"></div> | |
| <script> | |
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1833.8629, 1833.9265, 1833.9916, 1834.0543, 1834.1162, 1834.1797, 1834.2424, 1834.3041, 1834.3674, 1834.4326, 1834.4952, 1834.5533, 1834.6208, 1834.6847, 1834.748, 1834.8097, 1834.8694, 1834.9327, 1834.998, 1835.0615, 1835.1244, 1835.1849, 1835.2474, 1835.3112, 1835.3796, 1835.4443, 1835.504, 1835.5675, 1835.6284, 1835.688401], "saves": [2500, 5000, 7500, 10000, 12500, 15000, 17500, 20000, 22500, 25000, 27500], "cur": 28700, "total": 30000, "rate": 4.1, "elapsed": "33:37:50", "remaining": "1:31:22", "loggedTo": 25800, "frames": 161440, "bs": 32, "pruneFloor": 7500, "finalStep": 29999}; | |
| const fmt = (n,d=4)=>n.toFixed(d); | |
| const gp = k=>getComputedStyle(document.documentElement).getPropertyValue(k).trim(); | |
| const nf = new Intl.NumberFormat('en-US'); | |
| const ep = s=>(s*D.bs/D.frames); | |
| /* ---------- header + rail ---------- */ | |
| const pct = D.cur/D.total; | |
| document.getElementById('chipRate').textContent = D.rate+'s/step'; | |
| document.getElementById('pillTxt').textContent = 'running · '+D.elapsed+' elapsed'; | |
| document.getElementById('railPct').textContent = (pct*100).toFixed(1)+'%'; | |
| document.getElementById('railStep').innerHTML = | |
| nf.format(D.cur)+' <span>/ '+nf.format(D.total)+'</span>'; | |
| document.getElementById('railFill').style.width = (pct*100)+'%'; | |
| document.getElementById('lossNow').textContent = fmt(D.loss.at(-1)); | |
| document.getElementById('nLogged').textContent = nf.format(D.loggedTo); | |
| document.getElementById('nCur').textContent = nf.format(D.cur); | |
| document.getElementById('nPts').textContent = nf.format(D.steps.length); | |
| document.getElementById('nKeptNote').textContent= D.saves.filter(s=>s>=D.pruneFloor).length+' + 1'; | |
| { /* 2,000 steps at the 50-step log interval = 40 points each side. */ | |
| const w=40, mu=a=>a.reduce((x,y)=>x+y,0)/a.length, | |
| a=mu(D.loss.slice(-2*w,-w)), b=mu(D.loss.slice(-w)); | |
| document.getElementById('nFlat').textContent = | |
| fmt(a)+' \u2192 '+fmt(b)+' ('+(100*(b-a)/a).toFixed(1)+'%)'; } | |
| const rail = document.getElementById('rail'), axis = document.getElementById('railAxis'); | |
| /* A checkpoint below the prune floor is deleted by the janitor, so the rail says which | |
| ones actually survive rather than treating all three as equivalent. */ | |
| D.saves.forEach(st=>{ | |
| const kept = st >= D.pruneFloor, x = 100*st/D.total; | |
| const t = document.createElement('div'); | |
| t.className = 'tick'+(kept?'':' floor'); t.style.left = 'calc('+x+'% - 1px)'; | |
| rail.appendChild(t); | |
| /* Every save gets a tick, but only a 5k grid gets a label -- 11 labels at 2.5k | |
| spacing overlap into unreadable mush. Tick STYLE carries pruned-vs-kept; the | |
| key line below carries the counts. */ | |
| if(st % 5000) return; | |
| const i = document.createElement('i'); | |
| if(kept) i.className='k'; | |
| i.style.left = x+'%'; | |
| i.textContent = (st/1000)+'k'; | |
| axis.appendChild(i); | |
| }); | |
| { const nPruned = D.saves.filter(s=>s < D.pruneFloor).length, | |
| nKept = D.saves.filter(s=>s >= D.pruneFloor).length, | |
| left = Math.floor((D.total - D.saves.at(-1))/2500); | |
| document.getElementById('railKey').innerHTML = | |
| '<span><b class="sw kept"></b>'+nKept+' kept</span>' + | |
| '<span><b class="sw"></b>'+nPruned+' pruned — below step '+nf.format(D.pruneFloor)+'</span>' + | |
| '<span>'+left+' more to come, last at step '+nf.format(D.finalStep)+'</span>'; } | |
| { const i=document.createElement('i'); i.style.left='0%'; i.style.transform='none'; i.textContent='0'; axis.appendChild(i); | |
| const j=document.createElement('i'); j.style.left='100%'; j.style.transform='translateX(-100%)'; j.textContent='30k'; axis.appendChild(j); } | |
| /* ---------- KPIs ---------- */ | |
| const best = Math.min(...D.loss), bestAt = D.steps[D.loss.indexOf(best)]; | |
| const mean = a=>a.reduce((x,y)=>x+y,0)/a.length; | |
| const sd = a=>{const m=mean(a);return Math.sqrt(mean(a.map(v=>(v-m)*(v-m))));}; | |
| /* 40 points = 2,000 steps at the 50-step log interval, matching note 3. The shift | |
| between windows only counts as a trend once it clears the in-window spread -- | |
| a fixed epsilon like 1e-4 sits far below the noise here and always says | |
| 'falling'. */ | |
| const cut = Math.min(40, Math.max(1, Math.floor(D.loss.length/4))); | |
| const rec = mean(D.loss.slice(-cut)), prev = mean(D.loss.slice(-2*cut,-cut)); | |
| const dev = sd(D.loss.slice(-cut)); | |
| const trend = Math.abs(rec-prev) < dev ? 'flat' : (rec < prev ? 'falling' : 'rising'); | |
| [['Loss now', fmt(D.loss.at(-1)), 'at step '+nf.format(D.loggedTo)], | |
| ['Best loss', fmt(best), 'at step '+nf.format(bestAt)], | |
| ['Trend', trend, '\u00b1'+fmt(dev)+' noise over '+nf.format(cut*50)+' steps'], | |
| ['Epochs done', ep(D.cur).toFixed(2), 'of '+ep(D.total).toFixed(2)+' planned'], | |
| ['Elapsed', D.elapsed.split(':').slice(0,2).join('h ')+'m', D.rate+'s per step'], | |
| ['Remaining', D.remaining.split(':').slice(0,2).join('h ')+'m', 'to step '+nf.format(D.total)] | |
| ].forEach(([l,v,s])=>{ | |
| const d=document.createElement('div'); d.className='kpi'; | |
| const a=document.createElement('div'); a.className='lbl'; a.textContent=l; | |
| const b=document.createElement('div'); b.className='v mono'; b.textContent=v; | |
| const c=document.createElement('div'); c.className='s mono'; c.textContent=s; | |
| d.append(a,b,c); document.getElementById('kpis').appendChild(d); | |
| }); | |
| /* ---------- table ---------- */ | |
| const tb=document.getElementById('tbody'); | |
| D.steps.forEach((s,i)=>{ | |
| const tr=document.createElement('tr'); | |
| const ck=D.saves.includes(s)?'saved':''; | |
| [nf.format(s), ep(s).toFixed(2), fmt(D.loss[i]), fmt(D.grad[i]), D.param[i].toFixed(2), ck] | |
| .forEach((v,j)=>{ const td=document.createElement('td'); if(j===5) td.className='ck'; | |
| td.textContent=v; tr.appendChild(td); }); | |
| tb.appendChild(tr); | |
| }); | |
| /* ---------- charts ---------- */ | |
| const SVG='http://www.w3.org/2000/svg'; | |
| const el=(n,a={})=>{const e=document.createElementNS(SVG,n);for(const k in a)e.setAttribute(k,a[k]);return e;}; | |
| const tip=document.getElementById('tip'); | |
| function chart(id, vals, colorVar, opts){ | |
| const svg=document.getElementById(id); | |
| const W=svg.clientWidth||720, H=+svg.getAttribute('height'); | |
| const M={t:14,r:opts.rightPad||52,b:26,l:opts.leftPad||46}; | |
| svg.setAttribute('viewBox','0 0 '+W+' '+H); | |
| svg.replaceChildren(); | |
| const iw=W-M.l-M.r, ih=H-M.t-M.b; | |
| const col=gp(colorVar), surf=gp('--card'); | |
| const lo=Math.min(...vals), hi=Math.max(...vals); | |
| let ys, ticks; | |
| if(opts.log){ | |
| const l0=Math.log10(lo), l1=Math.log10(hi), padv=(l1-l0)*0.08; | |
| const a=l0-padv, b=l1+padv; | |
| ys=v=>M.t+ih-(Math.log10(v)-a)/(b-a)*ih; | |
| ticks=opts.ticks.filter(t=>t>=Math.pow(10,a)&&t<=Math.pow(10,b)); | |
| }else{ | |
| const padv=(hi-lo)*0.12||1, a=lo-padv, b=hi+padv; | |
| ys=v=>M.t+ih-(v-a)/(b-a)*ih; | |
| const span=hi-lo, raw=span/4, mag=Math.pow(10,Math.floor(Math.log10(raw))); | |
| const stepv=[1,2,5,10].map(m=>m*mag).find(m=>m>=raw)||10*mag; | |
| ticks=[]; for(let t=Math.ceil(a/stepv)*stepv; t<=b; t+=stepv) ticks.push(+t.toFixed(6)); | |
| } | |
| const xs=s=>M.l+(s-D.steps[0])/(D.steps.at(-1)-D.steps[0]||1)*iw; | |
| ticks.forEach(t=>{ | |
| const y=ys(t); | |
| svg.appendChild(el('line',{x1:M.l,x2:M.l+iw,y1:y,y2:y,stroke:gp('--grid'),'stroke-width':1})); | |
| const tx=el('text',{x:M.l-9,y:y+3.5,'text-anchor':'end',fill:gp('--ink-3'),'font-size':10, | |
| 'font-family':'ui-monospace,Menlo,monospace'}); | |
| tx.textContent=opts.fmtTick(t); svg.appendChild(tx); | |
| }); | |
| /* Checkpoint rules on EVERY save, but text on a 10k grid only. 11 saves x | |
| 'ckpt 12.5k' overruns the axis and collides with the endpoint label. */ | |
| if(opts.marks) D.saves.filter(s=>s<=D.steps.at(-1)).forEach(s=>{ | |
| svg.appendChild(el('line',{x1:xs(s),x2:xs(s),y1:M.t,y2:M.t+ih,stroke:gp('--rule'),'stroke-width':1})); | |
| if(s % 10000 || xs(s) > M.l+iw-46) return; | |
| const t=el('text',{x:xs(s),y:M.t+ih+16,'text-anchor':'middle',fill:gp('--ink-3'),'font-size':9, | |
| 'font-family':'ui-monospace,Menlo,monospace'}); | |
| t.textContent='ckpt '+(s/1000)+'k'; svg.appendChild(t); | |
| }); | |
| /* x ends */ | |
| [[D.steps[0],'start'],[D.steps.at(-1),'end']].forEach(([s,anch])=>{ | |
| const t=el('text',{x:xs(s),y:H-6,'text-anchor':anch==='start'?'start':'end',fill:gp('--ink-3'), | |
| 'font-size':10,'font-family':'ui-monospace,Menlo,monospace'}); | |
| t.textContent=nf.format(s); svg.appendChild(t); | |
| }); | |
| const pts=vals.map((v,i)=>[xs(D.steps[i]),ys(v)]); | |
| const dpath=pts.map((p,i)=>(i?'L':'M')+p[0].toFixed(2)+' '+p[1].toFixed(2)).join(' '); | |
| svg.appendChild(el('path',{d:dpath+' L'+pts.at(-1)[0]+' '+(M.t+ih)+' L'+pts[0][0]+' '+(M.t+ih)+' Z', | |
| fill:col,opacity:.10,stroke:'none'})); | |
| svg.appendChild(el('path',{d:dpath,fill:'none',stroke:col,'stroke-width':2, | |
| 'stroke-linejoin':'round','stroke-linecap':'round'})); | |
| /* endpoint: 8px marker with a 2px surface ring, plus a direct label (relief for the aqua WARN) */ | |
| const last=pts.at(-1); | |
| svg.appendChild(el('circle',{cx:last[0],cy:last[1],r:4,fill:col,stroke:surf,'stroke-width':2})); | |
| const lab=el('text',{x:last[0]+9,y:last[1]+3.5,fill:gp('--ink'),'font-size':11,'font-weight':650, | |
| 'font-family':'ui-monospace,Menlo,monospace'}); | |
| lab.textContent=opts.fmtLabel(vals.at(-1)); svg.appendChild(lab); | |
| /* hover: crosshair snapping to nearest step */ | |
| const cross=el('line',{y1:M.t,y2:M.t+ih,stroke:gp('--ink-3'),'stroke-width':1,opacity:0}); | |
| const hv=el('circle',{r:4.5,fill:col,stroke:surf,'stroke-width':2,opacity:0}); | |
| svg.append(cross,hv); | |
| const hit=el('rect',{x:M.l,y:M.t,width:iw,height:ih,fill:'transparent'}); | |
| svg.appendChild(hit); | |
| function show(cx){ | |
| const r=svg.getBoundingClientRect(), sx=(cx-r.left)*(W/r.width); | |
| let bi=0,bd=1e9; | |
| D.steps.forEach((s,i)=>{const dd=Math.abs(xs(s)-sx); if(dd<bd){bd=dd;bi=i;}}); | |
| cross.setAttribute('x1',xs(D.steps[bi])); cross.setAttribute('x2',xs(D.steps[bi])); | |
| cross.setAttribute('opacity',.45); | |
| hv.setAttribute('cx',pts[bi][0]); hv.setAttribute('cy',pts[bi][1]); hv.setAttribute('opacity',1); | |
| tip.replaceChildren(); | |
| const h=document.createElement('div'); h.className='tstep'; | |
| h.textContent='step '+nf.format(D.steps[bi])+' · '+ep(D.steps[bi]).toFixed(2)+' ep'; | |
| tip.appendChild(h); | |
| [['--s1','loss',fmt(D.loss[bi])],['--s2','grad norm',fmt(D.grad[bi])], | |
| ['--s3','param norm',D.param[bi].toFixed(2)]].forEach(([cv,nm,v])=>{ | |
| const row=document.createElement('div'); row.className='trow'; | |
| const l=document.createElement('span'); | |
| const k=document.createElement('span'); k.className='keyline'; k.style.background=gp(cv); | |
| l.append(k,document.createTextNode(nm)); | |
| const b=document.createElement('b'); b.className='mono'; b.textContent=v; | |
| row.append(l,b); tip.appendChild(row); | |
| }); | |
| const tr=svg.getBoundingClientRect(); | |
| const px=tr.left+pts[bi][0]*(tr.width/W), py=tr.top+pts[bi][1]*(tr.height/H); | |
| tip.style.opacity=1; | |
| const tw=tip.offsetWidth, th=tip.offsetHeight; | |
| tip.style.left=Math.min(window.innerWidth-tw-10,Math.max(10,px-tw/2))+'px'; | |
| tip.style.top=Math.max(10,py-th-14)+'px'; | |
| } | |
| function hide(){cross.setAttribute('opacity',0);hv.setAttribute('opacity',0);tip.style.opacity=0;} | |
| svg.addEventListener('pointermove',e=>show(e.clientX)); | |
| svg.addEventListener('pointerleave',hide); | |
| svg.addEventListener('focus',()=>show(svg.getBoundingClientRect().right-20)); | |
| svg.addEventListener('blur',hide); | |
| } | |
| const charts=()=>{ | |
| chart('cLoss', D.loss, '--s1', {log:true, marks:true, | |
| ticks:[0.02,0.05,0.1,0.2,0.5,1], fmtTick:t=>t<0.1?t.toFixed(2):(t<1?t.toFixed(1):t.toFixed(0)), | |
| fmtLabel:v=>v.toFixed(4)}); | |
| chart('cGrad', D.grad, '--s2', {log:true, leftPad:40, rightPad:56, | |
| ticks:[0.1,0.2,0.5,1,2,5], fmtTick:t=>t<1?t.toFixed(1):t.toFixed(0), fmtLabel:v=>v.toFixed(3)}); | |
| chart('cParam', D.param, '--s3', {log:false, leftPad:52, rightPad:60, | |
| fmtTick:t=>t.toFixed(0), fmtLabel:v=>v.toFixed(1)}); | |
| }; | |
| charts(); | |
| addEventListener('resize',()=>{clearTimeout(window._t);window._t=setTimeout(charts,120);}); | |
| matchMedia('(prefers-color-scheme: dark)').addEventListener('change',charts); | |
| new MutationObserver(charts).observe(document.documentElement,{attributes:true,attributeFilter:['data-theme']}); | |
| </script> | |