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r2s-cur-d02-lr7-s5-d42025b-53ddbe55-47646604

completed —

Hypothesis

With a learning rate of 7e-4 instead of 5e-4 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 a learning rate of 7e-4 instead of 5e-4 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]0.0736 [0.0686, 0.0785]
model pixel error, median0.0668
exact program rate0.068
rendered rate1.000
blank canvas pixel error0.1720
nearest training icon pixel error0.0897 [0.0848, 0.0947]
error reduction vs nearest icon0.0162 [0.0119, 0.0203]
icons where model beats nearest icon233
CLIP top-1, model greedy (32 Gate N icons)0.844
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 seconds2618
peak VRAM GiB4.388660430908203
latency ms/icon, batch 1, median3135.6
latency ms/icon, batch 1, p953168.8
throughput ms/icon, batch 64100.6
model calls per icon (decoding)639.0
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. running2026-10-31T07:37:06Z
  2. completed2026-10-31T08:23:11Z

Run record

Verbatim from runs/r2s-cur-d02-lr7-s5-d42025b-53ddbe55-47646604/run.yaml, the record committed before launch.

schema_version
2
run_id
r2s-cur-d02-lr7-s5-d42025b-53ddbe55-47646604
state
completed
planned_at
2026-10-31T07:37:06Z
hypothesis
With a learning rate of 7e-4 instead of 5e-4 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
c2133429933f496b…
config
configs/render2svg/cur-d02-lr7-s5.yaml
config_sha256
53ddbe555b77ad4f…
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
0.0007
weight_decay
0.01
warmup_steps
1000
seed
7005
eval_every
2000
eval_icons
64
train_icons
None
evaluate_on_train
false
augment_variants
0
augment_seed
9005
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
7005
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-lr7-s5.yaml
outputs
run_dir
runs/r2s-cur-d02-lr7-s5-d42025b-53ddbe55-47646604
checkpoints
/home/eai-jdkxz/eai-team11/mojidiff/cache/runs/r2s-cur-d02-lr7-s5-d42025b-53ddbe55-47646604
notes
completed_at
2026-10-31T08:23:11Z
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
2617.5739713700023
inference_ms_per_icon
3135.6302534695715
inference_p95_ms_per_icon
3168.7865459825844
icons_per_second
0.3189151523504728
batched_ms_per_icon
100.61121192120481
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
0.0735762980642109, 0.06859199941301838, 0.07854515156127397
model_pixel_error_median
0.06680157035589218
exact_program_rate
0.06784660766961652
rendered_rate
1.0
blank_pixel_error
0.1720480552069557
selected_step
44000
nearest_training_icon_pixel_error
0.08973124639576185, 0.0848205749792233, 0.09466393787711656
model_minus_baseline_error_reduction
0.016154948331550956, 0.011907142297993894, 0.020257236124450326
icons_model_beats_baseline
233
clip_retrieval
model_greedy
top1_rate
0.84375
top5_rate
0.9375
mean_rank
1.59375
clip_to_reference_mean
0.9275542218238115
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
639