Protein Engineering

gb1 · Sequence CNN

reference_gb1_cnn_randomf3_20261104-154457

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
train0.13780.98680.98600.973556291.00000.882424.00001.00001.69622.01760.00000.88461.00001.74552.52950.20000.94681.00001.71572.52950.30000.96041.00001.31212.52950.81500.9896
validation0.20940.97990.97890.959618803.00000.871556.00001.00001.69001.93620.10000.00000.92261.00001.63352.08880.30000.00000.95171.00001.60472.14550.42000.00000.96571.00001.31362.14550.80690.00000.9879
test0.21180.97960.97900.959118942.00000.8653101.00001.00001.62581.91300.00000.00000.90121.00001.65052.11100.30000.00000.95391.00001.61492.11100.43000.00000.96380.99911.28902.25940.78170.00000.9863

Loss per epoch

training validation

Config

name: reference_gb1_cnn_randomf3
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 3
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