Protein Engineering

ube4b · Linear

reference_ube4b_lr_plm_modulof0_20261104-175330

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
train2.46140.64240.63280.39375520.00000.507024.00001.00005.67897.82590.20000.00000.83020.98004.76858.62460.34000.00000.82540.98004.43468.62460.43000.00000.83470.98374.17348.62460.59180.00000.8867
validation2.81020.29650.29720.0773571.00000.02402314.00000.50000.16921.71300.00000.00000.31330.4400-0.15242.79450.06000.00000.32810.3600-0.50562.79450.06000.00000.27620.4194-0.04752.11960.03230.00000.3201
test3.08790.25580.25490.0537645.00000.0157403.00000.2000-1.24470.25100.00000.0000-0.00300.3400-0.54012.10100.00000.00000.15120.2900-0.68572.10100.02000.00000.13640.2857-0.77371.74610.00000.00000.0914

Loss per epoch

training validation

Config

name: reference_ube4b_lr_plm_modulof0
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7