Protein Engineering

ube4b · Graph CNN

reference_ube4b_gcn_plm_contiguousf4_20261105-043854

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
train3.86040.30690.34320.09392870.0000-0.012914282.00000.3000-0.39630.87170.00000.00000.15940.56000.05704.65300.00000.00000.24310.4300-0.18934.65300.01000.00000.22710.3684-0.33074.65300.00580.00000.2221
validation2.28700.22610.1656-0.00661218.00000.019866.00000.4000-0.36291.87170.00000.00000.08750.4000-0.40641.87170.00000.00000.09790.3300-0.45215.64210.02000.00000.10020.3721-0.50671.87170.00000.00000.0719
test2.37750.38330.32920.1462933.0000-0.06491117.00000.2000-1.16930.30150.00000.0000-0.01370.2600-0.82301.54560.00000.00000.06610.2700-0.70631.54560.00000.00000.10960.2368-0.89521.44700.00000.00000.0460

Loss per epoch

training validation

Config

name: reference_ube4b_gcn_plm_contiguousf4
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  graph_threshold: 7
  split_scheme: contiguous
  split_fold: 4
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