Protein Engineering

pab1 · Linear

reference_pab1_lr_plm_randomf1_20261104-180714

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
train0.65550.90810.92030.82462683.00000.04292497.00000.80000.17150.51660.00000.00000.70800.58000.04070.73310.02000.00000.71720.53000.04490.73310.04000.00000.74630.57960.05360.87440.10200.00000.7919
validation0.69270.90420.91530.8175935.00000.00732013.00000.6000-0.08250.38360.00000.00000.62790.60000.04200.56440.02000.00000.74260.62000.05650.82500.08000.00000.78770.60980.04670.82500.03660.00000.7729
test0.68180.90440.91560.8177898.00000.0698240.00000.60000.00030.26550.00000.00000.65700.70000.05260.86010.04000.00000.75290.66000.04010.86010.04000.00000.78490.65850.04470.86010.02440.00000.7755

Loss per epoch

training validation

Config

name: reference_pab1_lr_plm_randomf1
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7