Protein Engineering

avgfp · Linear

reference_avgfp_lr_randomf1_20261104-150040

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.32390.84420.85810.71173013.00000.25631138.00000.70003.78804.03070.00000.80460.68003.76924.10680.08000.82140.68003.75664.10680.07000.83110.58953.73264.10680.12350.8526
validation0.36060.82410.85490.67791006.00000.2366104.00000.30003.63303.87860.00000.00000.71850.50003.66894.00420.08000.00000.78480.54003.69294.00420.12000.00000.82580.56483.70334.10790.16670.00000.8369
test0.36430.82390.85280.67761025.00000.2030960.00000.30003.38493.84470.00000.00000.52300.46003.65154.07250.06000.00000.75610.49003.69364.08600.08000.00000.81410.48153.69534.08600.07410.00000.8185

Loss per epoch

training validation

Config

name: reference_avgfp_lr_randomf1
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7