MojiDiff

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r2s-cur-d02-c07-s6-d42025b-e90693a5-47646604

completed —

Hypothesis

With compositions with probability 0.7 instead of 0.5 and everything else as dropout 0.2 at 60k steps, the model transcribes the 339 validation renders better than the dropout-0.2 run of the same seed. Judged over seeds 7001-7008: the mean seed-matched difference with a bootstrap interval over seeds excluding zero.

Visual output

samples
samples.png

Written result

Hypothesis. With compositions with probability 0.7 instead of 0.5 and everything else as dropout 0.2 at 60k steps, the model transcribes the 339 validation renders better than the dropout-0.2 run of the same seed. Judged over seeds 7001-7008: the mean seed-matched difference with a bootstrap interval over seeds excluding zero.

Result

measurevalue
icons evaluated339 (primary/validation)
model pixel error, mean [95% CI]0.0748 [0.0695, 0.0800]
model pixel error, median0.0704
exact program rate0.029
rendered rate1.000
blank canvas pixel error0.1720
nearest training icon pixel error0.0897 [0.0848, 0.0947]
error reduction vs nearest icon0.0150 [0.0106, 0.0193]
icons where model beats nearest icon240
CLIP top-1, model greedy (32 Gate N icons)0.625
CLIP top-1, nearest training icon0.344
CLIP top-1, OmniSVG 4B zero-shot (Gate N)0.609

Resources

measurevalue
deviceNVIDIA B300 SXM6 AC
parameters9,025,826
train seconds2642
peak VRAM GiB4.388660430908203
latency ms/icon, batch 1, median2976.9
latency ms/icon, batch 1, p952992.8
throughput ms/icon, batch 64109.1
model calls per icon (decoding)613.0
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. running2026-10-31T07:39:07Z
  2. completed2026-10-31T08:25:29Z

Run record

Verbatim from runs/r2s-cur-d02-c07-s6-d42025b-e90693a5-47646604/run.yaml, the record committed before launch.

schema_version
2
run_id
r2s-cur-d02-c07-s6-d42025b-e90693a5-47646604
state
completed
planned_at
2026-10-31T07:39:07Z
hypothesis
With compositions with probability 0.7 instead of 0.5 and everything else as dropout 0.2 at 60k steps, the model transcribes the 339 validation renders better than the dropout-0.2 run of the same seed. Judged over seeds 7001-7008: the mean seed-matched difference with a bootstrap interval over seeds excluding zero.
parent_run
r2s-cur-dropout02
git_commit
d42025bbdd3c3bc772917121e2841a4bdd94c431
dirty_patch_sha256
b9cda2b3412e48f9…
config
configs/render2svg/cur-d02-c07-s6.yaml
config_sha256
e90693a5ef0b77c6…
config_resolved
model
image_size
144
d_model
256
heads
8
encoder_layers
2
decoder_layers
6
feedforward
1024
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
7006
eval_every
2000
eval_icons
64
train_icons
None
evaluate_on_train
false
augment_variants
0
augment_seed
9006
augment_mirror
0.5
augment_max_shift
48
augment_colour
0.1
augment_online
true
compose_probability
0.7
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
7006
determinism
seeded; cuDNN and SDPA kernels not forced deterministic
model_parameters
9025826
command
.venv/bin/python -m mojidiff.learning.render2svg --config configs/render2svg/cur-d02-c07-s6.yaml
outputs
run_dir
runs/r2s-cur-d02-c07-s6-d42025b-e90693a5-47646604
checkpoints
/home/eai-jdkxz/eai-team11/mojidiff/cache/runs/r2s-cur-d02-c07-s6-d42025b-e90693a5-47646604
notes
completed_at
2026-10-31T08:25:29Z
resource
device
NVIDIA B300 SXM6 AC
torch_version
2.14.1+cu130
cuda_version
13.0
python_version
3.12.3
peak_vram_gib
4.388660430908203
train_seconds
2641.8642916980316
inference_ms_per_icon
2976.8505599931814
inference_p95_ms_per_icon
2992.7933950093575
icons_per_second
0.33592549570318053
batched_ms_per_icon
109.0819612809355
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
0.07476482407341349, 0.06950606045669551, 0.08004790966053331
model_pixel_error_median
0.0703892782330513
exact_program_rate
0.029498525073746312
rendered_rate
1.0
blank_pixel_error
0.1720480552069557
selected_step
46000
nearest_training_icon_pixel_error
0.08973124639576185, 0.0848205749792233, 0.09466393787711656
model_minus_baseline_error_reduction
0.01496642232234837, 0.01055947298890685, 0.01925047229738768
icons_model_beats_baseline
240
clip_retrieval
model_greedy
top1_rate
0.625
top5_rate
0.84375
mean_rank
4.28125
clip_to_reference_mean
0.912436418235302
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
613