Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_randomf3_20261104-154517

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
train0.15530.98500.98400.970256291.00000.8757497.00001.00001.67331.82200.00000.87971.00001.67812.09420.08000.93151.00001.64182.19520.17000.94321.00001.30232.52950.79020.9870
validation0.20290.98030.97900.960918803.00000.8676449.00001.00001.73601.93620.10000.93301.00001.60982.01090.26000.94611.00001.58882.01090.40000.96181.00001.30212.14550.78080.9848
test0.20420.98020.97930.960618942.00000.8614244.00001.00001.59962.11100.10000.89541.00001.61892.11100.30000.94651.00001.56962.11100.40000.95291.00001.28692.25940.77240.9858

Loss per epoch

training validation

Config

name: reference_gb1_gcn_randomf3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: random
  split_fold: 3
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