Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_s1_20261104-020151

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
test0.20080.98070.97900.96169438.00000.861717.00001.00001.66811.93620.10000.00000.93241.00001.62552.08880.48000.00000.97341.00001.56492.08880.66000.00000.97951.00001.29252.08880.76490.00000.9849
train0.17570.98300.98190.966276104.00000.86560.00000.86650.06000.91940.20000.94070.79130.9871
validation0.20540.98010.97950.96058494.00000.86729.00001.00001.70601.93520.30000.00000.96441.00001.60961.93520.48000.00000.97341.00001.54191.93520.61000.00000.97741.00001.30951.93520.79460.00000.9881

Loss per epoch

training validation

Config

name: reference_gb1_gcn_s1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: gb1/splits/main
  graph_threshold: 7
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: 1