Protein Engineering

ube4b · Graph CNN

reference_ube4b_gcn_plm_randomf0_20261104-174858

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
train1.98160.69490.66090.480612442.00000.47733.00001.00006.59029.18450.30000.00000.85791.00005.57359.18450.32000.00000.87261.00005.13499.18450.37000.00000.87360.99663.97549.18450.56100.00000.8909
validation2.15610.65690.61720.43094135.00000.4444354.00001.00005.20736.57580.10000.00000.81871.00004.40136.57580.36000.00000.81561.00004.16406.57580.41000.00000.84660.97973.80876.57580.52280.00000.8662
test2.15920.65040.61400.42244174.00000.4198120.00001.00005.20187.82590.10000.00000.78291.00004.63348.04830.34000.00000.83820.99004.28578.04830.49000.00000.86260.98983.78338.62460.55840.00000.8618

Loss per epoch

training validation

Config

name: reference_ube4b_gcn_plm_randomf0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: random
  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