Protein Engineering

ube4b · Sequence CNN

reference_ube4b_cnn_plm_contiguousf4_20261105-043843

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
train2.77420.64850.58940.34892870.00000.5343146.00001.00005.14627.10650.30000.00000.79711.00004.16767.10650.20000.00000.78671.00003.97367.10650.39000.00000.82091.00003.75639.18450.42110.00000.8477
validation2.38170.21330.1717-0.04831218.00000.023458.00000.4000-0.21461.87170.00000.00000.11610.3600-0.45971.87170.00000.00000.08510.3500-0.37575.64210.02000.00000.12120.4186-0.44471.87170.00000.00000.0864
test2.51650.37520.32580.0963933.0000-0.06351062.00000.3000-1.11820.36640.00000.0000-0.00410.2400-0.87291.44700.00000.00000.05400.2800-0.79321.54560.00000.00000.08520.2368-0.93880.45660.00000.00000.0361

Loss per epoch

training validation

Config

name: reference_ube4b_cnn_plm_contiguousf4
task: dms
data:
  dataset: ube4b
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 4
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