Protein Engineering

avgfp · Fully connected

reference_avgfp_fc_plm_contiguousf0_20261104-175351

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
train0.76460.67670.5674-0.19632295.00000.09214613.00000.10003.64023.87220.00000.00000.48020.42003.68923.92710.00000.00000.58840.46003.67174.09680.03000.00000.59270.42653.66454.09680.02940.00000.5968
validation1.00120.06830.02260.004160.0000-0.0474133.00000.00002.68713.64800.00000.0000-0.13950.08002.82223.85870.08000.0000-0.01360.06002.67413.85870.10000.0000-0.17670.00002.80933.64800.00000.0000-0.0236
test0.84470.25700.1996-0.1895109.00000.051979.00000.20003.14393.85010.00000.0000-0.04300.16003.03123.91780.10000.0000-0.22310.17003.22703.99610.17000.00000.08290.00002.89063.62200.00000.0000-0.3682

Loss per epoch

training validation

Config

name: reference_avgfp_fc_plm_contiguousf0
task: dms
data:
  dataset: avgfp
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 0
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