Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_randomf1_20261104-150443

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.14920.98560.98480.971356332.00000.87931468.00001.00001.71071.93620.00000.89921.00001.71382.11100.18000.93821.00001.67512.11100.30000.94901.00001.30262.45390.79450.9879
validation0.20000.98060.97920.961518825.00000.8638799.00001.00001.67252.09420.10000.92921.00001.58542.09420.20000.94841.00001.57202.09420.43000.96231.00001.29822.28590.78920.9864
test0.20270.98040.97890.961118879.00000.866173.00001.00001.67221.85270.00000.90011.00001.65472.01760.36000.95251.00001.60532.52950.47000.96231.00001.31032.52950.79100.9869

Loss per epoch

training validation

Config

name: reference_gb1_gcn_randomf1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: random
  split_fold: 1
model:
  name: gcn
  filters:
  - 128
  - 128
  - 128
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7