Protein Engineering

pab1 · Graph CNN

reference_pab1_gcn_plm_randomf0_20261104-174808

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
train0.37100.94920.94140.90102767.00000.0911386.00000.90000.47511.16150.10000.00000.78570.80000.22361.16150.10000.00000.76450.72000.17531.16150.10000.00000.78190.75920.15911.16150.16330.00000.8247
validation0.42650.94140.93030.8860898.00000.1141156.00000.6000-0.00680.56400.00000.00000.65450.62000.03270.84200.06000.00000.74520.62000.02910.84200.12000.00000.78050.63410.03670.84200.10980.00000.7724
test0.44730.93880.92910.8813851.00000.0671265.00000.50000.05580.46070.00000.00000.73460.60000.09320.73310.08000.00000.79780.62000.07050.73310.10000.00000.82090.63410.07980.73310.09760.00000.8151

Loss per epoch

training validation

Config

name: reference_pab1_gcn_plm_randomf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: random
  split_fold: 0
model:
  name: gcn
  filters:
  - 32
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7