Protein Engineering

gb1 · Linear

reference_gb1_lr_plm_randomf4_20261105-041516

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
train0.71320.92890.96310.862956646.00000.8039107.00001.00001.66231.92400.00000.00000.87941.00001.64452.09420.06000.00000.92211.00001.62682.11100.20000.00000.93930.99911.28052.52950.75600.00000.9816
validation0.72040.92820.96260.861518587.00000.7965492.00001.00001.70691.99510.10000.00000.92421.00001.63851.99510.30000.00000.95151.00001.59991.99510.44000.00000.96280.99911.26952.45390.75470.00000.9801
test0.71030.92900.96320.863118803.00000.8130159.00001.00001.65101.93620.10000.00000.91391.00001.58172.01090.26000.00000.93951.00001.55042.08880.37000.00000.95261.00001.28792.14550.75930.00000.9810

Loss per epoch

training validation

Config

name: reference_gb1_lr_plm_randomf4
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 4
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7