Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_randomf0_20261104-142018

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train0.15740.98490.98420.969756570.00000.8836409.00001.00001.75442.09420.10000.91371.00001.71952.11100.16000.94321.00001.67402.11100.26000.95221.00001.30812.28590.80130.9889
validation0.20740.98010.97860.960218879.00000.871948.00001.00001.68751.92400.00000.00000.90351.00001.69612.52950.36000.00000.96221.00001.61982.52950.51000.00000.96580.99911.31282.52950.79480.00000.9875
test0.20740.98000.97880.960118587.00000.8668445.00001.00001.66011.83750.00000.00000.91371.00001.67591.99510.42000.00000.96031.00001.62872.09750.50000.00000.96971.00001.28772.45390.77330.00000.9849

Loss per epoch

training validation

Config

name: reference_gb1_cnn_randomf0
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 0
model:
  name: cnn
  conv:
  - - 128
    - 17
  - - 128
    - 17
  - - 128
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7