Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_plm_contiguousf4_20261105-043250

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
train1.50080.53450.48540.23785893.00000.10686110.00000.80001.01032.36370.00000.00000.40200.74000.86172.41130.00000.00000.39740.79000.84682.41130.03000.00000.41320.75660.75072.41130.03290.00000.3918
validation1.80030.32370.30440.10161218.0000-0.0443876.00000.50000.32072.20540.00000.00000.28470.4000-0.04572.20540.02000.00000.21230.3700-0.08632.45670.04000.00000.21410.3953-0.08122.20540.02330.00000.1973
test1.81310.25870.1977-0.02091997.0000-0.1401265.00000.60000.15541.04800.00000.00000.11610.5000-0.05531.48330.00000.00000.05180.4400-0.03372.08410.01000.00000.06430.5106-0.07311.35810.00000.00000.0447

Loss per epoch

training validation

Config

name: reference_bgl3_fc_plm_contiguousf4
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 4
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