Protein Engineering

pab1 · Sequence CNN

reference_pab1_cnn_plm_contiguousf4_20261105-043736

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
train0.51470.94070.92710.87611652.00000.0790802.00000.70000.09200.48350.00000.00000.74060.72000.10440.83950.02000.00000.80170.65000.05510.83950.06000.00000.81250.57780.00210.83950.11110.00000.8177
validation1.77410.72990.73000.5214222.0000-0.02322117.00000.2000-0.28630.06340.00000.00000.75140.1800-0.30920.37230.04000.00000.78030.1800-0.39210.37230.06000.00000.77640.1633-0.32310.23730.02040.00000.7748
test1.42060.75060.61550.2384931.00000.03521380.00000.2000-0.20980.23310.00000.00000.39110.2000-0.33650.86010.04000.00000.37940.2400-0.32590.86010.03000.00000.41620.2222-0.33530.86010.04440.00000.3760

Loss per epoch

training validation

Config

name: reference_pab1_cnn_plm_contiguousf4
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 4
model:
  name: cnn
  conv:
  - - 128
    - 17
  - - 128
    - 17
  - - 128
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7