MojiDiff

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r2s-cur-d02-w384-508979a-1a8a1eac-47646604

completed —

Hypothesis

With dropout 0.2 holding back overfitting, width 384 transcribes validation renders better than v9. Pass requires the paired 95% bootstrap interval on the per-icon reduction in mean 72 px pixel error on the 339 validation renders to exclude zero against each v9 run of the same protocol (seeds 7001-7003 on the B300, the H100 rerun, the RTX 4080 original). Its greedy latency on the RTX 4080 is recorded.

Visual output

samples
samples.png

Written result

Hypothesis. With dropout 0.2 holding back overfitting, width 384 transcribes validation renders better than v9. Pass requires the paired 95% bootstrap interval on the per-icon reduction in mean 72 px pixel error on the 339 validation renders to exclude zero against each v9 run of the same protocol (seeds 7001-7003 on the B300, the H100 rerun, the RTX 4080 original). Its greedy latency on the RTX 4080 is recorded.

Result

measurevalue
icons evaluated339 (primary/validation)
model pixel error, mean [95% CI]0.0704 [0.0654, 0.0755]
model pixel error, median0.0678
exact program rate0.050
rendered rate1.000
blank canvas pixel error0.1720
nearest training icon pixel error0.0897 [0.0848, 0.0947]
error reduction vs nearest icon0.0194 [0.0153, 0.0233]
icons where model beats nearest icon245
CLIP top-1, model greedy (32 Gate N icons)0.562
CLIP top-1, nearest training icon0.344
CLIP top-1, OmniSVG 4B zero-shot (Gate N)0.609

Resources

measurevalue
deviceNVIDIA B300 SXM6 AC
parameters19,762,402
train seconds4823
peak VRAM GiB6.41351842880249
latency ms/icon, batch 1, median2595.1
latency ms/icon, batch 1, p954752.6
throughput ms/icon, batch 6482.6
model calls per icon (decoding)898.0
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. running2026-10-30T15:49:50Z
  2. completed2026-10-30T17:12:22Z

Run record

Verbatim from runs/r2s-cur-d02-w384-508979a-1a8a1eac-47646604/run.yaml, the record committed before launch.

schema_version
2
run_id
r2s-cur-d02-w384-508979a-1a8a1eac-47646604
state
completed
planned_at
2026-10-30T15:49:50Z
hypothesis
With dropout 0.2 holding back overfitting, width 384 transcribes validation renders better than v9. Pass requires the paired 95% bootstrap interval on the per-icon reduction in mean 72 px pixel error on the 339 validation renders to exclude zero against each v9 run of the same protocol (seeds 7001-7003 on the B300, the H100 rerun, the RTX 4080 original). Its greedy latency on the RTX 4080 is recorded.
parent_run
r2s-cur-dropout02
git_commit
508979ab7de93d1b98088d64682d64c73554c4df
dirty_patch_sha256
config
configs/render2svg/cur-d02-w384.yaml
config_sha256
1a8a1eac7dc69c08…
config_resolved
model
image_size
144
d_model
384
heads
8
encoder_layers
2
decoder_layers
6
feedforward
1536
dropout
0.2
metric
true
fourier
10
order
path
sources
0
training
steps
60000
batch_size
32
learning_rate
0.0005
weight_decay
0.01
warmup_steps
1000
seed
7001
eval_every
2000
eval_icons
64
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
339
clip_icons
32
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
19762402
command
.venv/bin/python -m mojidiff.learning.render2svg --config configs/render2svg/cur-d02-w384.yaml
outputs
run_dir
runs/r2s-cur-d02-w384-508979a-1a8a1eac-47646604
checkpoints
/home/eai-jdkxz/eai-team11/mojidiff/cache/runs/r2s-cur-d02-w384-508979a-1a8a1eac-47646604
notes
completed_at
2026-10-30T17:12:22Z
resource
device
NVIDIA B300 SXM6 AC
torch_version
2.14.1+cu130
cuda_version
13.0
python_version
3.12.3
peak_vram_gib
6.41351842880249
train_seconds
4822.926530333003
inference_ms_per_icon
2595.080937986495
inference_p95_ms_per_icon
4752.554344013333
icons_per_second
0.385344435837093
batched_ms_per_icon
82.60650898409949
batched_icons_per_call
64
excludes
rendering the output SVG to pixels
baselines
blank_canvas_pixel_error
0.1720480552069557
nearest_training_icon_pixel_error
0.08973124639576185
gate_n_omnisvg_zero_shot_top1
0.609375
nearest_training_icon_clip_top1
0.34375
result
icons
339
model_pixel_error
0.07037478786353867, 0.06544174050998135, 0.07546730172748982
model_pixel_error_median
0.06775952875614166
exact_program_rate
0.05014749262536873
rendered_rate
1.0
blank_pixel_error
0.1720480552069557
selected_step
52000
nearest_training_icon_pixel_error
0.08973124639576185, 0.0848205749792233, 0.09466393787711656
model_minus_baseline_error_reduction
0.01935645853222319, 0.015277188952938309, 0.023268639081167445
icons_model_beats_baseline
245
clip_retrieval
model_greedy
top1_rate
0.5625
top5_rate
0.9375
mean_rank
2.9375
clip_to_reference_mean
0.9215214140713215
chance_top1
0.03125
icons
32
nearest_training_icon
top1_rate
0.34375
top5_rate
0.59375
mean_rank
7.40625
clip_to_reference_mean
0.8630617223680019
chance_top1
0.03125
icons
32
gate_n_omnisvg_zero_shot_top1
0.609375
gate_n_omnisvg_best_of_12_top1
0.828125
model_calls_per_icon
898