MojiDiff

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r2s-smoke-v9-w16-67bab78-30dc1c5d-47646604

completed —

Hypothesis

Trained on the 2,681 family-disjoint training icons with metric coordinates, path-major order, online exact augmentation and compositions, the 9.0M-parameter render-to-program model transcribes held-out validation renders better than retrieving the closest training icon. Pass requires all three: (1) mean 72 px pixel error below the nearest-training-icon baseline with the paired 95% interval on the reduction excluding zero; (2) CLIP top-1 on Gate N's 32 validation icons at or above OmniSVG 4B zero-shot, 0.609; (3) median single-icon latency on the RTX 4080 under 500 ms.

Visual output

samples
samples.png

Written result

Hypothesis. Trained on the 2,681 family-disjoint training icons with metric coordinates, path-major order, online exact augmentation and compositions, the 9.0M-parameter render-to-program model transcribes held-out validation renders better than retrieving the closest training icon. Pass requires all three: (1) mean 72 px pixel error below the nearest-training-icon baseline with the paired 95% interval on the reduction excluding zero; (2) CLIP top-1 on Gate N's 32 validation icons at or above OmniSVG 4B zero-shot, 0.609; (3) median single-icon latency on the RTX 4080 under 500 ms.

Result

measurevalue
icons evaluated32 (primary/validation)
model pixel error, mean [95% CI]0.1603 [0.1351, 0.1882]
model pixel error, median0.1225
exact program rate0.000
rendered rate1.000
blank canvas pixel error0.1627
nearest training icon pixel error0.0943 [0.0816, 0.1074]
error reduction vs nearest icon-0.0660 [-0.0956, -0.0399]
icons where model beats nearest icon6
CLIP top-1, model greedy (8 Gate N icons)0.125
CLIP top-1, nearest training icon0.375
CLIP top-1, OmniSVG 4B zero-shot (Gate N)0.609

Resources

measurevalue
deviceNVIDIA B300 SXM6 AC
parameters9,025,826
train seconds133
peak VRAM GiB4.388385772705078
latency ms/icon, batch 1, median2266.3
latency ms/icon, batch 1, p952270.7
throughput ms/icon, batch 32222.9
model calls per icon (decoding)441.0
torch / CUDA2.14.1+cu130 / 13.0

Latency covers encoding and decoding to a validated token program; it excludes rasterising the SVG. Samples: samples.png, rows are reference, model, nearest training icon.

State transitions

  1. running2026-10-30T13:47:28Z
  2. completed2026-10-30T13:51:10Z

Run record

Verbatim from runs/r2s-smoke-v9-w16-67bab78-30dc1c5d-47646604/run.yaml, the record committed before launch.

schema_version
2
run_id
r2s-smoke-v9-w16-67bab78-30dc1c5d-47646604
state
completed
planned_at
2026-10-30T13:47:28Z
hypothesis
Trained on the 2,681 family-disjoint training icons with metric coordinates, path-major order, online exact augmentation and compositions, the 9.0M-parameter render-to-program model transcribes held-out validation renders better than retrieving the closest training icon. Pass requires all three: (1) mean 72 px pixel error below the nearest-training-icon baseline with the paired 95% interval on the reduction excluding zero; (2) CLIP top-1 on Gate N's 32 validation icons at or above OmniSVG 4B zero-shot, 0.609; (3) median single-icon latency on the RTX 4080 under 500 ms.
parent_run
r2s-full-v9-colour
git_commit
67bab78fdc1a5143a1b131f59e45979d02cdf2c0
dirty_patch_sha256
config
configs/render2svg/smoke-v9-w16.yaml
config_sha256
30dc1c5d3f515374…
config_resolved
model
image_size
144
d_model
256
heads
8
encoder_layers
2
decoder_layers
6
feedforward
1024
dropout
0.1
metric
true
fourier
10
order
path
sources
0
training
steps
1200
batch_size
32
learning_rate
0.0005
weight_decay
0.01
warmup_steps
100
seed
7001
eval_every
400
eval_icons
32
train_icons
None
evaluate_on_train
false
augment_variants
0
augment_seed
9001
augment_mirror
0.5
augment_max_shift
48
augment_colour
0.1
augment_online
true
compose_probability
0.5
compose_parts
4
augment_original
0.1
loader_workers
16
extra_training
bf16
true
final_eval_icons
32
clip_icons
8
dataset
pilot_config
configs/learning/openmoji-g1-geometric-gate-v16.yaml
cache_sha256
476466042da98d72…
train_icons
2681
augmented_variants
0
extra_training
None
augmented_sha256
None
evaluated_on
primary/validation
seed
7001
determinism
seeded; cuDNN and SDPA kernels not forced deterministic
model_parameters
9025826
command
.venv/bin/python -m mojidiff.learning.render2svg --config configs/render2svg/smoke-v9-w16.yaml
outputs
run_dir
runs/r2s-smoke-v9-w16-67bab78-30dc1c5d-47646604
checkpoints
/home/eai-jdkxz/eai-team11/mojidiff/cache/runs/r2s-smoke-v9-w16-67bab78-30dc1c5d-47646604
notes
completed_at
2026-10-30T13:51:10Z
resource
device
NVIDIA B300 SXM6 AC
torch_version
2.14.1+cu130
cuda_version
13.0
python_version
3.12.3
peak_vram_gib
4.388385772705078
train_seconds
133.42488472600235
inference_ms_per_icon
2266.3335204997566
inference_p95_ms_per_icon
2270.6726340111345
icons_per_second
0.441241322583221
batched_ms_per_icon
222.89912287487823
batched_icons_per_call
32
excludes
rendering the output SVG to pixels
baselines
blank_canvas_pixel_error
0.16265273559838533
nearest_training_icon_pixel_error
0.09432368678972125
gate_n_omnisvg_zero_shot_top1
0.609375
nearest_training_icon_clip_top1
0.375
result
icons
32
model_pixel_error
0.16028745949734002, 0.1351036772946827, 0.18823951802914962
model_pixel_error_median
0.12253741919994354
exact_program_rate
0.0
rendered_rate
1.0
blank_pixel_error
0.16265273559838533
selected_step
1200
nearest_training_icon_pixel_error
0.09432368678972125, 0.08160671039076987, 0.10738429491466377
model_minus_baseline_error_reduction
-0.06596377270761877, -0.09559567327960394, -0.039855239578173496
icons_model_beats_baseline
6
clip_retrieval
model_greedy
top1_rate
0.125
top5_rate
0.75
mean_rank
4.25
clip_to_reference_mean
0.7936437204480171
chance_top1
0.125
icons
8
nearest_training_icon
top1_rate
0.375
top5_rate
1.0
mean_rank
2.125
clip_to_reference_mean
0.8379977643489838
chance_top1
0.125
icons
8
gate_n_omnisvg_zero_shot_top1
0.609375
gate_n_omnisvg_best_of_12_top1
0.828125
model_calls_per_icon
441