Protein Engineering

ube4b · Linear

reference_ube4b_lr_plm_modulof1_20261104-181501

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
train2.36780.53400.56910.27624756.00000.1963738.00001.00003.85096.12790.20000.00000.71060.96002.80576.12790.10000.00000.68370.93002.38546.12790.17000.00000.67400.84191.68436.39900.26920.00000.6249
validation4.62590.28270.27630.0381819.00000.00962107.00000.4000-0.41792.27380.00000.00000.09960.3600-0.23613.15840.00000.00000.14580.3800-0.28403.15840.00000.00000.15290.3438-0.19623.15840.00000.00000.1450
test2.82070.29220.29140.0739571.00000.02292351.00000.4000-0.01221.71300.00000.00000.27880.3800-0.23172.79450.06000.00000.30850.3700-0.53602.79450.06000.00000.26750.3871-0.11722.11960.03230.00000.3045

Loss per epoch

training validation

Config

name: reference_ube4b_lr_plm_modulof1
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7