Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_randomf0_20261104-142108

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
train0.16010.98450.98380.969256570.00000.88232088.00001.00001.69901.93620.00000.90161.00001.65852.09420.08000.92921.00001.66982.11100.28000.95121.00001.30742.28590.80500.9887
validation0.20490.98020.97900.960718879.00000.872252.00001.00001.68371.92400.00000.00000.90261.00001.63622.19520.28000.00000.94821.00001.62482.52950.51000.00000.96701.00001.31572.52950.80130.00000.9883
test0.20610.98000.97900.960418587.00000.8677586.00001.00001.70822.09750.10000.00000.92451.00001.65922.09750.32000.00000.95641.00001.62002.09750.49000.00000.96761.00001.29282.45390.78080.00000.9863

Loss per epoch

training validation

Config

name: reference_gb1_gcn_randomf0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: random
  split_fold: 0
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