Protein Engineering

ube4b · Sequence CNN

reference_ube4b_cnn_plm_contiguousf1_20261104-182038

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
train2.26910.56080.53810.28139072.00000.2383341.00001.00003.91106.15800.10000.00000.66621.00003.38916.15800.08000.00000.69131.00003.29937.55330.16000.00000.73860.97182.66847.62880.37790.00000.7795
validation5.14820.39150.42930.112388.00000.037377.00000.2000-0.70572.64950.00000.00000.14120.3200-0.23613.54530.12000.00000.29300.3400-0.08615.70470.39000.00000.45040.2500-0.59760.24510.00000.00000.1412
test3.29810.28070.30270.0706458.0000-0.12362069.00000.4000-0.78321.50640.00000.00000.15490.4600-0.25363.46860.02000.00000.31070.4200-0.29773.46860.08000.00000.34210.5385-0.24241.50640.00000.00000.2822

Loss per epoch

training validation

Config

name: reference_ube4b_cnn_plm_contiguousf1
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 1
model:
  name: cnn
  conv:
  - - 128
    - 3
  - - 128
    - 3
  - - 128
    - 3
  - - 128
    - 3
  - - 128
    - 3
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7