Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_contiguousf0_20261104-144952

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
train0.49660.95760.93030.915132275.00000.63902299.00001.00001.54271.92400.00000.87661.00001.47811.92400.02000.89891.00001.46251.92400.03000.91160.99791.28892.25940.57700.9614
validation3.22790.20030.1147-0.59965403.00000.07595231.00000.1000-1.13470.32170.00000.0000-0.05130.0800-1.11490.57670.00000.0000-0.04640.1300-1.03180.72220.00000.0000-0.00870.1841-1.02580.72220.00000.0000-0.0061
test3.33520.52390.4516-0.08651866.00000.04164258.00000.0000-1.8354-0.66930.00000.00000.05640.0200-1.91460.04330.00000.00000.03300.0100-1.89370.04330.00000.00000.04160.0498-1.48020.45530.00000.00000.1988

Loss per epoch

training validation

Config

name: reference_gb1_gcn_contiguousf0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  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