Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_contiguousf3_20261105-040920

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
train2.18600.68520.64410.43705445.00000.48354744.00001.00004.71936.43390.10000.00000.70441.00004.82808.62460.30000.00000.83451.00004.55088.62460.43000.00000.85531.00004.31358.62460.60450.00000.9031
validation2.33250.40670.33330.1624933.0000-0.05671167.00000.3000-1.12330.41600.00000.0000-0.00510.2800-0.74751.54560.00000.00000.08430.2800-0.74581.54560.00000.00000.09850.2632-0.79051.05610.00000.00000.0700
test3.58110.32670.34980.0459323.0000-0.0874484.00000.3000-0.18080.78480.00000.00000.25840.3200-0.41073.15840.02000.00000.28350.3200-0.43483.87920.07000.00000.32330.2400-0.62600.78480.00000.00000.2190

Loss per epoch

training validation

Config

name: reference_ube4b_fc_plm_contiguousf3
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7