Protein Engineering

gb1 · Linear

reference_gb1_lr_randomf0_20261104-142438

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.71050.92910.96310.863156570.00000.79951036.00001.00001.73342.09420.10000.90911.00001.59652.09420.04000.91511.00001.59142.11100.19000.93290.99941.28032.28590.75960.9815
validation0.72540.92790.96210.860918879.00000.807238.00001.00001.70351.92400.00000.00000.90701.00001.67432.52950.36000.00000.95711.00001.63422.52950.53000.00000.96920.99911.28832.52950.75090.00000.9811
test0.72270.92790.96230.861118587.00000.7918458.00001.00001.66291.99510.10000.00000.91441.00001.64141.99510.30000.00000.95221.00001.61801.99510.47000.00000.96710.99911.27272.45390.76030.00000.9809

Loss per epoch

training validation

Config

name: reference_gb1_lr_randomf0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 0
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7