Protein Engineering

ube4b · Graph CNN

reference_ube4b_gcn_plm_contiguousf0_20261104-175846

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
train2.41960.64920.59540.42054241.00000.5024546.00001.00005.89317.74370.30000.00000.86171.00004.85947.74370.32000.00000.84550.99004.47777.74370.39000.00000.85690.99063.86897.74370.45070.00000.8461
validation3.05260.38120.39820.1398458.0000-0.06531971.00000.80000.53372.27710.00000.00000.38900.56000.01103.09080.10000.00000.36930.4100-0.30054.42140.08000.00000.34140.5000-0.08593.09080.03850.00000.3135
test2.12030.26670.19580.06671218.00000.02031242.00000.2000-0.52212.42630.00000.00000.05680.4400-0.26983.07130.04000.00000.13050.4200-0.32283.66400.06000.00000.13580.4651-0.19483.07130.04650.00000.1445

Loss per epoch

training validation

Config

name: reference_ube4b_gcn_plm_contiguousf0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 0
model:
  name: gcn
  filters:
  - 128
  - 128
  - 128
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7