Protein Engineering

gb1 · Linear

reference_gb1_lr_plm_modulof3_20261105-035942

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
train1.24210.88720.92210.769929512.00000.45792052.00001.00000.92311.10570.00000.00000.82501.00000.91591.47200.06000.00000.87341.00000.84011.47200.03000.00000.87190.98320.66481.76940.24860.00000.9127
validation4.98270.03730.0267-0.07843230.0000-0.210918857.00000.0000-3.6350-3.03500.00000.0000-0.35710.0400-3.71710.36050.00000.0000-0.39320.0300-3.80050.36050.00000.0000-0.42520.0498-3.77120.39530.00000.0000-0.4284
test4.26890.21240.17970.02674705.0000-0.09146496.00000.3000-0.88651.21420.00000.00000.25540.3000-0.99291.24700.00000.00000.24540.2800-1.10491.61320.01000.00000.22100.2400-1.22501.61320.00500.00000.1940

Loss per epoch

training validation

Config

name: reference_gb1_lr_plm_modulof3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7