Protein Engineering

gb1 · Linear

reference_gb1_lr_modulof1_20261104-153622

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
train1.20570.88010.90480.764735035.00000.41632344.00001.00001.60461.92400.00000.85821.00001.45841.92400.02000.87451.00001.37292.01760.05000.87670.97650.99612.20420.32910.8803
validation5.2720-0.0207-0.0195-0.18731545.0000-0.240714949.00000.0000-2.4391-0.91820.00000.00000.09050.0200-2.84100.11990.00000.0000-0.01810.0200-2.89670.11990.00000.0000-0.03440.0398-3.09000.36020.00000.0000-0.0916
test6.8461-0.2182-0.1856-0.18064408.00000.036715545.00000.0000-4.3723-0.13550.00000.0000-0.51620.0000-4.4638-0.04710.00000.0000-0.56900.0300-4.26891.36440.01000.0000-0.52910.0503-4.29511.36440.01010.0000-0.5506

Loss per epoch

training validation

Config

name: reference_gb1_lr_modulof1
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7