Protein Engineering

bgl3 · Graph CNN

reference_bgl3_gcn_plm_modulof3_20261105-035904

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
train1.36370.55200.50770.30293467.00000.06974021.00000.70000.94552.20540.00000.00000.41060.60000.62302.94050.02000.00000.35630.61000.57622.94050.05000.00000.35850.60610.57512.94050.04040.00000.3577
validation1.20350.33330.31670.1109437.0000-0.13231181.00000.3000-0.33461.69460.00000.00000.02110.4000-0.13352.36370.02000.00000.10990.47000.05572.36370.09000.00000.20970.50000.09272.36370.06250.00000.1796
test1.25690.30670.23410.0884437.0000-0.1122368.00000.4000-0.09031.48330.00000.00000.10470.3000-0.22111.94590.02000.00000.07830.2800-0.32071.94590.04000.00000.04260.3125-0.03971.94590.00000.00000.1273

Loss per epoch

training validation

Config

name: reference_bgl3_gcn_plm_modulof3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 6
  split_scheme: modulo
  split_fold: 3
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