Protein Engineering

gb1 · Linear

reference_gb1_lr_mr5_randomf2_20261105-013254

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
train0.71260.92890.96300.862956304.00000.801194.00001.00001.71062.09420.10000.00000.90311.00001.60872.09420.08000.00000.92441.00001.62242.52950.20000.00000.94540.99971.28042.52950.76740.00000.9825
validation0.71790.92820.96290.861518603.00000.800756.00001.00001.65711.99510.10000.00000.92291.00001.58361.99510.28000.00000.94591.00001.57032.08880.42000.00000.95971.00001.28122.08880.76000.00000.9838
test0.72310.92800.96220.861118674.00000.8028247.00001.00001.66691.93620.20000.00000.93301.00001.62402.01760.32000.00000.95641.00001.61632.01760.55000.00000.97260.99911.26332.09750.75720.00000.9815

Loss per epoch

training validation

Config

name: reference_gb1_lr_mr5_randomf2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 2
  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