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r2s-cur-d02-lr3-s4-8e367a7-b1ea4d89-47646604

completed —

Hypothesis

With a learning rate of 3e-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 3e-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]0.0880 [0.0826, 0.0936]
model pixel error, median0.0850
exact program rate0.006
rendered rate1.000
blank canvas pixel error0.1720
nearest training icon pixel error0.0897 [0.0848, 0.0947]
error reduction vs nearest icon0.0017 [-0.0030, 0.0064]
icons where model beats nearest icon189
CLIP top-1, model greedy (32 Gate N icons)0.594
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 seconds2631
peak VRAM GiB4.388660430908203
latency ms/icon, batch 1, median4950.1
latency ms/icon, batch 1, p954991.5
throughput ms/icon, batch 64131.8
model calls per icon (decoding)1011.0
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. running2026-10-31T00:59:10Z
  2. completed2026-10-31T01:46:02Z

Run record

Verbatim from runs/r2s-cur-d02-lr3-s4-8e367a7-b1ea4d89-47646604/run.yaml, the record committed before launch.

schema_version
2
run_id
r2s-cur-d02-lr3-s4-8e367a7-b1ea4d89-47646604
state
completed
planned_at
2026-10-31T00:59:10Z
hypothesis
With a learning rate of 3e-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
8e367a70bf39659e61188db527635cf15cc6a554
dirty_patch_sha256
config
configs/render2svg/cur-d02-lr3-s4.yaml
config_sha256
b1ea4d8940c53fd1…
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
0.0003
weight_decay
0.01
warmup_steps
1000
seed
7004
eval_every
2000
eval_icons
64
train_icons
None
evaluate_on_train
false
augment_variants
0
augment_seed
9004
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
7004
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-lr3-s4.yaml
outputs
run_dir
runs/r2s-cur-d02-lr3-s4-8e367a7-b1ea4d89-47646604
checkpoints
/home/eai-jdkxz/eai-team11/mojidiff/cache/runs/r2s-cur-d02-lr3-s4-8e367a7-b1ea4d89-47646604
notes
completed_at
2026-10-31T01:46:02Z
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
2631.230361173977
inference_ms_per_icon
4950.129164499231
inference_p95_ms_per_icon
4991.473593981937
icons_per_second
0.20201493067528126
batched_ms_per_icon
131.8398467501538
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
0.08802136023986293, 0.08257164272247397, 0.09360285109452626
model_pixel_error_median
0.08497211337089539
exact_program_rate
0.0058997050147492625
rendered_rate
1.0
blank_pixel_error
0.1720480552069557
selected_step
36000
nearest_training_icon_pixel_error
0.08973124639576185, 0.0848205749792233, 0.09466393787711656
model_minus_baseline_error_reduction
0.0017098861558989217, -0.003001135401951443, 0.006422984273322985
icons_model_beats_baseline
189
clip_retrieval
model_greedy
top1_rate
0.59375
top5_rate
0.96875
mean_rank
2.1875
clip_to_reference_mean
0.9236323423683643
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
1011