Protein Engineering

gb1 · Linear

reference_gb1_lr_plm_randomf3_20261105-035331

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
train0.71580.92880.96290.862556291.00000.798998.00001.00001.60341.92400.00000.00000.86471.00001.66622.09420.12000.00000.92881.00001.65922.52950.23000.00000.94730.99941.28262.52950.76100.00000.9818
validation0.70980.92910.96330.863218803.00000.8090177.00001.00001.65101.93620.10000.00000.91391.00001.56782.01090.24000.00000.93621.00001.55802.08880.37000.00000.95441.00001.28832.14550.75930.00000.9811
test0.71360.92870.96340.862418942.00000.792298.00001.00001.56601.77200.00000.00000.88791.00001.59682.11100.22000.00000.94131.00001.58832.25940.42000.00000.95740.99811.26862.25940.75280.00000.9809

Loss per epoch

training validation

Config

name: reference_gb1_lr_plm_randomf3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  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