Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_plm_contiguousf1_20261104-181614

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
train1.85450.31570.26640.05205657.0000-0.06883980.00000.80000.75932.20540.00000.00000.31860.60000.16722.20540.00000.00000.16850.54000.07872.20540.00000.00000.14880.52670.07452.50020.01330.00000.1530
validation2.06000.19330.11360.03521465.0000-0.03901591.00000.2000-0.16662.14660.00000.00000.10100.4200-0.37632.14660.02000.00000.04130.3700-0.45912.31360.03000.00000.01320.4884-0.14102.14660.00000.00000.1217
test1.76640.29170.2914-0.06641203.00000.00391852.00000.60000.50092.01740.00000.00000.29860.48000.18472.31360.04000.00000.20080.37000.03682.31360.03000.00000.15260.47060.22642.01740.00000.00000.2108

Loss per epoch

training validation

Config

name: reference_bgl3_fc_plm_contiguousf1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 1
model:
  name: fcn
  hidden:
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7