Protein Engineering

ube4b · Linear

reference_ube4b_lr_modulof4_20261104-170321

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
train2.54370.59230.56350.34406783.00000.470553.00000.90004.39926.18800.00000.00000.64870.90003.75328.62460.24000.00000.67560.92003.51469.15370.26000.00000.69620.93713.43549.15370.45030.00000.7830
validation3.41510.01000.0032-0.0465645.0000-0.09482064.00000.1000-1.47840.45660.00000.0000-0.04400.1000-1.53932.10100.00000.0000-0.06850.1900-1.26482.23240.02000.0000-0.00930.0714-1.74660.45660.00000.0000-0.1044
test3.8957-0.0643-0.0630-0.1255318.0000-0.05181236.00000.0000-2.5284-0.32100.00000.0000-0.16330.0400-2.44051.30610.00000.0000-0.20160.0700-2.30132.04160.03000.0000-0.19780.0000-2.4728-0.32100.00000.0000-0.1716

Loss per epoch

training validation

Config

name: reference_ube4b_lr_modulof4
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 4
model:
  name: lr
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7