Protein Engineering

bgl3 · Linear

reference_bgl3_lr_plm_randomf1_20261104-180428

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
train1.16190.63520.60400.39996174.00000.22764943.00001.00001.59583.11600.10000.00000.57341.00001.42903.11600.08000.00000.58460.98001.29943.11600.04000.00000.57300.95631.23883.11600.04370.00000.5730
validation1.44620.53750.49670.28812044.00000.13192091.00001.00001.04001.48330.00000.00000.44860.86000.95732.50020.02000.00000.47440.75000.71542.50020.05000.00000.41260.86790.96252.50020.01890.00000.4788
test1.39000.54120.48910.29182050.00000.10291971.00000.90000.88282.36370.00000.00000.37260.70000.58172.36370.02000.00000.33120.70000.61262.36370.04000.00000.37050.69810.56942.36370.01890.00000.3290

Loss per epoch

training validation

Config

name: reference_bgl3_lr_plm_randomf1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  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