A
Alpha
super_chat_20260225140824_ee4kactivechat17.44M params2m 23s elapsed · ~11h 51m remaining
8L / 384D / 8H · helios · bpe-4k · adamw· Created Feb 25, 2026 2:09 PM
Step 159 / 50,0000.3%
7.4462
Loss?
7.4366
Best Loss?
-11.1% from start
-
Val Loss?
1.22e-5
Learning Rate?
7,215
Throughput?
tok/s (avg)
856
Speed?
ms/iter (avg)
1.047
Grad Norm?
avg: 1.081
976.9K
Tokens
processed
181ms
Forward
21% of step
609ms
Backward
71% of step
8ms
GPU Sync
1% of step
828
GPU Ops
per step
2.5%
MFU
model FLOPS util
3.4x
Bwd/Fwd
ratio
Loss Curve ?
Symbio semantics: this chart stitches many fresh candidate evaluations onto one global step axis. Loss resets near switches are expected because candidates are re-initialized. Compare local candidate shapes and the global frontier, not a single continuous model trajectory.
Search semantics
Validation / selection
Run diagnostics
Search Trajectory + Frontier
Candidate-local train/val loss segments on a shared step axis, with switch events and global frontier overlays.
Search-aware view
Architecture
Layers?8
Embedding?384
Heads?8
Vocab?4,000
Context?512
Dropout?0.1
Parameters?17.44M
Training Config
Total iters?50,000
Batch size?12
Max LR?0.00005
Optimizer?adamw
Backend?helios
Tokenizer?bpe-4k
Seed?42
Weight decay?0.1
Grad clip?1
Eval interval?1000
GPU & VRAM
Learning Rate
Grad Norm
Step Time Breakdown
Step Time Breakdown
Clip Telemetry
SymbiogenesisSWIGLU
1.80
Wt Entropy
bits
20.0
Eff. Rank
7.5425
Free Energy
3.910
Pop Entropy
nats
0.0756
Complexity
0.0418
Fitness
151
CUSUM Alerts
of 159 steps
8
Batch Size
adaptive
CUSUM Change-Point Monitor
Weight Entropy
Effective Rank
Free Energy
Fitness Score
Population Entropy
Adaptive Batch Size
Phase Change / Gelation
Current
Transitioning
Stability
0%
Phase Changes
4
Regime Shifts
0
Training dynamics are shifting. The model may be entering a new loss basin or the learning rate is hitting a critical threshold. This often happens before a breakthrough or a plateau.
Phase Timeline
Step 1Step 151
Loss Oscillation (Harmonic Analysis)
Evolutionary Search
Generations
1
Candidates
1
Activations
1
Best Loss
7.4366
Total Steps
159
#CandidateActivationGenLossFitnessStepsMutation
1gen0_gelu_1gelu07.43660.0418159origin
Generation Summary
G01c7.4366
Architecture Diversity
Convergence vs Diversity (Tug-of-War)
Current Mode
Converging
Diversity Pressure
0%
Convergence Momentum
100%
Convergence Progress
100%
Phase Portrait: Diversity Pressure vs Convergence Momentum
Low diversity / high momentum = lock-in convergence
High diversity / high momentum = productive exploration
Low diversity / low momentum = stalled collapse
High diversity / low momentum = diversity stalling convergence
Tug-of-War Trace (Time Domain)
Positive tension means recent frontier improvement is outpacing diversity pressure (search is converging). Negative tension means exploration pressure is dominating recent convergence momentum (search is broadening or getting “stumped”).
Strongest Convergence
step 14
tension 1.000
Strongest Diversity Push
step 1
tension -0.000
Best Frontier
7.4366
progress 100%
Evolutionary Lineage Tree
Lineage Tree
100%
Activation Flow (Sankey)
Activation Switch Log
StepFromToGenPrev StepsBest LossFinal LossFitnessTree
1-→gelu0----
Search Candidates
#NameActivationGenParentStepsBest LossBest ValAvg LossFitnessAvg tok/sAlerts
1gen0_gelu_1gelu0-1597.4366-7.83810.04187,158151
Activation Distribution
gelu
159 (100%)
Oscillation & Heat Capacity
Activation Evolution Radial
Symbio Config
{
  "cusumSensitivity": 4,
  "cusumBaselineWindow": 5,
  "metricsInterval": 10,
  "trackWeightEntropy": true,
  "trackEffectiveRank": true,
  "trackFreeEnergy": true,
  "trackMIProfiles": true,
  "trackPopulationMetrics": true,
  "freeEnergyBeta": 0.01,
  "miNumBins": 30,
  "adaptiveBatch": true,
  "batchMin": 8,
  "batchMax": 64,
  "batchStep": 4,
  "calmStepsBeforeRestore": 200,
  "fitnessAlpha": 1,
  "complexityMode": "entropy",
  "diversityBonus": 0.05,
  "diversityDecay": "cosine",
  "searchMode": "ffn-activation-search",
  "activationPool": [
    "gelu",
    "silu",
    "relu",
    "swiglu",
    "universal",
    "kan_spline"
  ],
  "searchStrategy": "evolutionary",
  "populationSize": 50000,
  "generations": 20,
  "selectionStrategy": "topk",
  "tournamentK": 3,
  "mutationRate": 0.5,
  "stepsPerCandidate": 3000,
  "rankBy": "valLoss",
  "perfWeight": 0,
  "stabilityWeight": 0,
  "writeReport": true,
  "writeCandidates": true,
  "writeSummary": true
}
Checkpoints (0) ?
No checkpoints saved
{
  "vocabSize": 4000,
  "blockSize": 512,
  "nLayer": 8,
  "nEmbd": 384,
  "nHead": 8,
  "dropout": 0.1,
  "ffnActivation": "swiglu",
  "ffnDim": 1024
}
{
  "iters": 50000,
  "batchSize": 12,
  "lr": 0.00005,
  "lrMin": 0.000005,
  "warmupIters": 1000,
  "beta1": 0.9,
  "beta2": 0.95,
  "eps": 0.000001,
  "weightDecay": 0.1,
  "gradClip": 1,
  "evalInterval": 1000,
  "evalIters": 10,
  "seed": 42,
  "backend": "helios",
  "tokenizer": "bpe-4k",
  "optimizer": "adamw",
  "logLevel": "info",
  "trace": false,
  "gradAccumSteps": 1,
  "sampleInterval": 500,
  "spikeThreshold": 10,
  "syncEvery": 1,
  "gcEvery": 0,
  "packed": false,
  "symbio": true,
  "symbioConfig": {
    "cusumSensitivity": 4,
    "cusumBaselineWindow": 5,
    "metricsInterval": 10,
    "trackWeightEntropy": true,
    "trackEffectiveRank": true,
    "trackFreeEnergy": true,
    "trackMIProfiles": true,
    "trackPopulationMetrics": true,
    "freeEnergyBeta": 0.01,
    "miNumBins": 30,
    "adaptiveBatch": true,
    "batchMin": 8,
    "batchMax": 64,
    "batchStep": 4,
    "calmStepsBeforeRestore": 200,
    "fitnessAlpha": 1,
    "complexityMode": "entropy",
    "diversityBonus": 0.05,
    "diversityDecay": "cosine",
    "searchMode": "ffn-activation-search",
    "activationPool": [
      "gelu",
      "silu",
      "relu",
      "swiglu",
      "universal",
      "kan_spline"
    ],
    "searchStrategy": "evolutionary",
    "populationSize": 50000,
    "generations": 20,
    "selectionStrategy": "topk",
    "tournamentK": 3,
    "mutationRate": 0.5,
    "stepsPerCandidate": 3000,
    "rankBy": "valLoss",
    "perfWeight": 0,
    "stabilityWeight": 0,
    "writeReport": true,
    "writeCandidates": true,
    "writeSummary": true
  }
}