Protein Engineering

ube4b · Sequence CNN

reference_ube4b_cnn_plm_modulof2_20261104-184249

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
train2.00000.62920.62610.39545464.00000.2465460.00001.00004.46176.12790.20000.00000.75811.00003.17496.12790.18000.00000.71181.00002.98646.12790.22000.00000.74950.97132.33386.39900.31540.00000.7472
validation2.68570.34090.35750.1132418.0000-0.0936762.00000.4000-0.96201.07930.00000.00000.07190.4200-0.59872.04920.02000.00000.19340.4300-0.52123.99860.07000.00000.25010.4444-0.56171.07930.00000.00000.1700
test4.53520.26760.29110.0570819.0000-0.16552504.00000.1000-1.68980.85310.00000.0000-0.07810.2000-0.82975.58030.02000.00000.04910.2500-0.82755.58030.01000.00000.05480.0938-1.18950.85310.00000.0000-0.0091

Loss per epoch

training validation

Config

name: reference_ube4b_cnn_plm_modulof2
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 2
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