Protein Engineering

ube4b · Fully connected

reference_ube4b_fc_plm_contiguousf1_20261104-182106

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
train2.11750.60590.58760.32939072.00000.260172.00001.00004.45656.15800.20000.00000.73561.00003.47856.15800.14000.00000.70441.00003.37117.62880.17000.00000.75010.98122.81677.62880.41550.00000.8085
validation4.96260.38970.41700.144388.00000.037555.00000.60000.11911.64000.00000.00000.27220.38000.02294.53270.16000.00000.34890.3500-0.00115.70470.40000.00000.47580.75000.34021.64000.00000.00000.2741
test3.26490.29830.32300.0800458.0000-0.09162087.00000.6000-0.05051.03880.00000.00000.28510.5000-0.09073.46860.04000.00000.34680.4200-0.19634.42140.10000.00000.36770.53850.05243.46860.03850.00000.3411

Loss per epoch

training validation

Config

name: reference_ube4b_fc_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: 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