Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_modulof1_20261104-153210

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
train0.27630.87220.77560.69691273.00000.161149.00000.30003.63953.89370.00000.61420.46003.68944.09560.02000.70590.39003.67664.09560.05000.72120.40453.68054.09560.03370.7206
validation0.4880-0.0835-0.1027-0.0499135.00000.077766.00000.00002.84063.70340.00000.0000-0.91390.08003.11263.78640.02000.0000-0.49530.09003.16193.93670.07000.0000-0.42660.00002.70383.70340.00000.0000-1.1432
test0.5473-0.2863-0.2349-0.0834216.00000.0109903.00000.20002.68763.79780.00000.0000-0.94220.16002.81823.79780.00000.0000-0.90910.16002.71803.85430.08000.0000-1.18350.18182.75723.79780.00000.0000-0.8489

Loss per epoch

training validation

Config

name: reference_avgfp_fc_modulof1
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7