Protein Engineering

bgl3 · Linear

reference_bgl3_lr_randomf3_20261104-154439

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
train1.20650.63220.60120.38946140.00000.21295159.00001.00001.30721.94590.00000.47260.94001.27522.45670.02000.53030.91001.22112.45670.03000.54500.92501.22553.09270.06880.5707
validation1.38840.52470.48060.27532018.00000.13528.00001.00001.40733.11600.10000.00000.55210.86000.93773.11600.06000.00000.45490.82000.86983.11600.05000.00000.46310.86790.96243.11600.07550.00000.4661
test1.38860.54090.50430.29122110.00000.1313151.00000.90001.04201.78560.00000.00000.44860.86000.97092.26100.02000.00000.47550.75000.73202.26100.05000.00000.40670.84910.95982.26100.01890.00000.4734

Loss per epoch

training validation

Config

name: reference_bgl3_lr_randomf3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7