Protein Engineering

gb1 · Graph CNN

reference_gb1_gcn_modulof1_20261104-153445

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
train0.64910.93530.93410.873335035.00000.501536.00001.00001.56552.01760.00000.84971.00001.54932.52950.10000.89541.00001.57282.52950.19000.92400.99421.19312.52950.50550.9324
validation3.72350.54130.54870.16151545.00000.13173029.00000.0000-2.6011-0.04760.00000.00000.04700.0400-2.28840.26950.00000.00000.13660.0800-2.40990.30260.00000.00000.10460.1443-2.05920.66620.01000.00000.2094
test8.04230.16980.1902-0.38694408.00000.16896094.00000.0000-5.0242-3.87240.00000.0000-0.68370.0000-4.9394-3.15530.00000.0000-0.69780.0000-5.0821-3.15530.00000.0000-0.75490.0000-5.1066-3.15530.00000.0000-0.7820

Loss per epoch

training validation

Config

name: reference_gb1_gcn_modulof1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  graph_threshold: 7
  split_scheme: modulo
  split_fold: 1
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