Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_plm_contiguousf2_20261104-184505

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
train0.30740.95780.96070.906340274.00000.61407208.00001.00001.11311.34720.00000.00000.81241.00001.10841.45260.04000.00000.87211.00001.07281.45260.19000.00000.89100.99580.77561.85050.43490.00000.9197
validation7.61890.50990.5278-0.38922473.0000-0.15163746.00000.5000-1.91540.24330.00000.00000.30150.4600-0.96570.47920.00000.00000.50020.2800-1.45060.54210.00000.00000.40690.2150-1.65010.71120.00000.00000.3731
test12.06870.31130.2769-1.23732092.0000-0.00916806.00000.3000-1.69630.59690.00000.00000.35860.3000-2.15791.33270.00000.00000.28310.3000-1.88801.33270.00000.00000.33930.2687-2.06381.34990.01490.00000.3134

Loss per epoch

training validation

Config

name: reference_gb1_gcn_plm_contiguousf2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 2
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