Protein Engineering

bgl3 · Linear

reference_bgl3_lr_randomf0_20261104-141924

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
train1.11870.66060.63640.43196172.00000.25343.00001.00001.62233.11600.10000.59571.00001.42923.11600.04000.59020.99001.42063.11600.04000.61770.97501.36973.11600.05000.6230
validation1.37580.54860.49870.29902050.00000.11381492.00000.80001.01062.26100.00000.00000.41170.82000.97122.36370.06000.00000.47190.77000.86322.45670.05000.00000.46840.81130.96252.36370.07550.00000.4719
test1.40380.52700.48660.27382046.00000.12882055.00001.00001.09801.35810.00000.00000.44940.96001.12621.86900.00000.00000.53050.84000.91272.08410.01000.00000.48630.94341.09191.86900.00000.00000.5205

Loss per epoch

training validation

Config

name: reference_bgl3_lr_randomf0
task: dms
data:
  dataset: bgl3
  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