Protein Engineering

pab1 · Linear

reference_pab1_lr_s5_20261104-024924

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
test0.74130.89730.90110.8051477.00000.1335402.00000.6000-0.05830.51660.00000.00000.66760.66000.08061.16150.20000.00000.80420.5900-0.00631.16150.27000.00000.80740.63410.05021.16150.19510.00000.7803
train0.66800.90680.91530.82223650.00000.21320.00000.74360.08000.75720.09000.76650.16310.8133
validation0.69710.89870.90260.8076389.00000.1225507.00000.3000-0.39890.35770.00000.00000.54560.5000-0.08930.84450.14000.00000.73590.4600-0.12060.86620.17000.00000.75990.4324-0.14970.84450.10810.00000.6946

Loss per epoch

training validation

Config

name: reference_pab1_lr_s5
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: pab1/splits/main
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 5