Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_mr5_randomf2_20261105-012830

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
train0.15400.98520.98440.970456304.00000.884929.00001.00001.69961.85270.00000.00000.90071.00001.70362.52950.24000.00000.94621.00001.67732.52950.27000.00000.95831.00001.31092.52950.82410.00000.9906
validation0.20560.98010.97900.960318603.00000.871328.00001.00001.57441.78590.00000.00000.90421.00001.63642.08880.32000.00000.95831.00001.59402.08880.48000.00000.96541.00001.30272.08880.80950.00000.9895
test0.20990.97980.97840.959718674.00000.871760.00001.00001.65191.93620.10000.00000.92961.00001.66872.01760.44000.00000.96701.00001.63692.09750.59000.00000.97751.00001.29022.09750.80020.00000.9886

Loss per epoch

training validation

Config

name: reference_gb1_cnn_mr5_randomf2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 2
  min_reads: 5
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