Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_randomf2_20261104-154738

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
train0.06850.97140.86610.93923073.00000.2638376.00000.60003.68653.90810.00000.72040.56003.72524.03070.04000.78040.64003.75994.10680.11000.82570.60803.75014.10680.16670.8623
validation0.09640.95740.85520.9140965.00000.2986356.00000.70003.74323.98400.20000.00000.80230.50003.68004.05640.08000.00000.79530.57003.71824.05640.12000.00000.84450.55563.70874.05640.11110.00000.8399
test0.08570.96260.86130.92351006.00000.274493.00000.40003.68413.88670.00000.00000.75500.52003.72413.98810.08000.00000.82640.60003.74104.10790.21000.00000.86320.58333.73854.10790.20370.00000.8644

Loss per epoch

training validation

Config

name: reference_avgfp_fc_randomf2
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: random
  split_fold: 2
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