Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_s5_20261104-141129

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
test0.19770.98090.97900.96229438.00000.867716.00001.00001.64261.93620.10000.00000.92661.00001.62592.08880.52000.00000.97351.00001.56192.08880.64000.00000.97871.00001.29962.08880.79100.00000.9867
train0.16830.98370.98260.967676104.00000.8731142.00001.00001.76342.09420.00000.89211.00001.69642.11100.08000.92251.00001.67172.19520.19000.93891.00001.30602.52950.79780.9881
validation0.20150.98040.97980.96128494.00000.87536.00001.00001.68191.93520.10000.00000.95881.00001.58591.93520.44000.00000.96761.00001.55551.93520.65000.00000.98081.00001.31091.93520.78840.00000.9885

Loss per epoch

training validation

Config

name: reference_gb1_gcn_s5
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: 5