Protein Engineering

gb1 · Linear

reference_gb1_lr_mr5_randomf1_20261105-011139

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
train0.71410.92860.96280.862355995.00000.8014114.00001.00001.62641.92400.00000.00000.88751.00001.61042.09420.14000.00000.92241.00001.60932.11100.22000.00000.94141.00001.27862.52950.76310.00000.9834
validation0.72280.92800.96220.861218674.00000.8049232.00001.00001.66691.93620.20000.00000.93301.00001.62872.01760.32000.00000.95751.00001.61952.01760.56000.00000.97340.99911.26562.09750.76100.00000.9821
test0.71340.92900.96330.863018912.00000.804863.00001.00001.65211.77200.00000.00000.92921.00001.59881.94820.24000.00000.95091.00001.59372.19520.46000.00000.96540.99911.28552.19520.75440.00000.9807

Loss per epoch

training validation

Config

name: reference_gb1_lr_mr5_randomf1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
  min_reads: 5
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7