list | grep "spot[RiverPython]" pip
spotPython 0.2.34
spotRiver 0.0.93
Note: you may need to restart the kernel to use updated packages.
In this tutorial, we will show how spotPython
can be integrated into the PyTorch
training workflow for a classifiaction task.
Ensure that the correspondiing data is available as ./data/VBDP/train.csv
.
This document refers to the following software versions:
python
: 3.10.10torch
: 2.0.1torchvision
: 0.15.0list | grep "spot[RiverPython]" pip
spotPython 0.2.34
spotRiver 0.0.93
Note: you may need to restart the kernel to use updated packages.
spotPython
can be installed via pip. Alternatively, the source code can be downloaded from gitHub: https://github.com/sequential-parameter-optimization/spotPython.
!pip install spotPython
spotPython
from gitHub.# import sys
# !{sys.executable} -m pip install --upgrade build
# !{sys.executable} -m pip install --upgrade --force-reinstall spotPython
Before we consider the detailed experimental setup, we select the parameters that affect run time, initial design size and the device that is used.
= 60
MAX_TIME = 10
INIT_SIZE = None # "cpu" # "cuda:0" DEVICE
from spotPython.utils.device import getDevice
= getDevice(DEVICE)
DEVICE print(DEVICE)
mps
import os
import copy
import socket
from datetime import datetime
from dateutil.tz import tzlocal
= datetime.now(tzlocal())
start_time = socket.gethostname().split(".")[0]
HOSTNAME = '25-torch' + "_" + HOSTNAME + "_" + str(MAX_TIME) + "min_" + str(INIT_SIZE) + "init_" + str(start_time).split(".", 1)[0].replace(' ', '_')
experiment_name = experiment_name.replace(':', '-')
experiment_name print(experiment_name)
if not os.path.exists('./figures'):
'./figures') os.makedirs(
25-torch_p040025_60min_10init_2023-06-17_17-19-50
fun_control
DictionaryspotPython
uses a Python dictionary for storing the information required for the hyperparameter tuning process, which was described in Section 14.2.
from spotPython.utils.init import fun_control_init
= fun_control_init(task="classification",
fun_control ="runs/25_spot_torch_vbdp",
tensorboard_path=DEVICE) device
import pandas as pd
from sklearn.preprocessing import OrdinalEncoder
= pd.read_csv('./data/VBDP/train.csv')
train_df # remove the id column
= train_df.drop(columns=['id'])
train_df = train_df.shape[0]
n_samples = train_df.shape[1] - 1
n_features = "prognosis"
target_column # # Encoder our prognosis labels as integers for easier decoding later
= OrdinalEncoder()
enc = enc.fit_transform(train_df[[target_column]])
train_df[target_column]
train_df.head()
# convert all entries to int for faster processing
= train_df.astype(int) train_df
from spotPython.data.vbdp import combine_features
= train_df.copy()
df_new # save the target column using "target_column" as the column name
= train_df[target_column]
target # remove the target column
= df_new.drop(columns=[target_column])
df_new = combine_features(df_new)
train_df # add the target column back
= target
train_df[target_column] train_df.head()
sudden_fever | headache | mouth_bleed | nose_bleed | muscle_pain | joint_pain | vomiting | rash | diarrhea | hypotension | ... | 6039 | 6040 | 6041 | 6042 | 6043 | 6044 | 6045 | 6046 | 6047 | prognosis | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
2 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 3 |
3 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 6 |
5 rows × 6113 columns
from sklearn.model_selection import train_test_split
import numpy as np
= train_df.shape[0]
n_samples = train_df.shape[1] - 1
n_features = [f"x{i}" for i in range(1, n_features+1)] + [target_column]
train_df.columns train_df.head()
x1 | x2 | x3 | x4 | x5 | x6 | x7 | x8 | x9 | x10 | ... | x6104 | x6105 | x6106 | x6107 | x6108 | x6109 | x6110 | x6111 | x6112 | prognosis | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 |
2 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | ... | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 3 |
3 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 |
4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 6 |
5 rows × 6113 columns
train_df[target_column].head()
0 3
1 7
2 3
3 10
4 6
Name: prognosis, dtype: int64
= train_test_split(train_df.drop(target_column, axis=1), train_df[target_column],
X_train, X_test, y_train, y_test =42,
random_state=0.25,
test_size=train_df[target_column])
stratify= pd.DataFrame(np.hstack((X_train, np.array(y_train).reshape(-1, 1))))
trainset = pd.DataFrame(np.hstack((X_test, np.array(y_test).reshape(-1, 1))))
testset = [f"x{i}" for i in range(1, n_features+1)] + [target_column]
trainset.columns = [f"x{i}" for i in range(1, n_features+1)] + [target_column]
testset.columns print(train_df.shape)
print(trainset.shape)
print(testset.shape)
(707, 6113)
(530, 6113)
(177, 6113)
import torch
from sklearn.model_selection import train_test_split
from spotPython.torch.dataframedataset import DataFrameDataset
= torch.float32
dtype_x = torch.long
dtype_y = DataFrameDataset(train_df, target_column=target_column, dtype_x=dtype_x, dtype_y=dtype_y)
train_df = DataFrameDataset(trainset, target_column=target_column, dtype_x=dtype_x, dtype_y=dtype_y)
train = DataFrameDataset(testset, target_column=target_column, dtype_x=dtype_x, dtype_y=dtype_y)
test = len(train) n_samples
# add the dataset to the fun_control
"data": train_df, # full dataset,
fun_control.update({"train": train,
"test": test,
"n_samples": n_samples,
"target_column": target_column})
After the training and test data are specified and added to the fun_control
dictionary, spotPython
allows the specification of a data preprocessing pipeline, e.g., for the scaling of the data or for the one-hot encoding of categorical variables, see Section 14.4.1. This feature is not used here, so we do not change the default value (which is None
).
algorithm
and core_model_hyper_dict
spotPython
includes the Net_vbdp
class which is implemented in the file netvbdp.py
. The class is imported here.
This class inherits from the class Net_Core
which is implemented in the file netcore.py
, see Section 14.4.3.
from spotPython.torch.netvbdp import Net_vbdp
from spotPython.data.torch_hyper_dict import TorchHyperDict
from spotPython.hyperparameters.values import add_core_model_to_fun_control
= add_core_model_to_fun_control(core_model=Net_vbdp,
fun_control =fun_control,
fun_control=TorchHyperDict) hyper_dict
spotPython
provides functions for modifying the hyperparameters, their bounds and factors as well as for activating and de-activating hyperparameters without re-compilation of the Python source code. These functions were described in Section 14.5.3.
epochs
is set to 2 and 3 for demonstration purposes. These values are too small for a real application.from spotPython.hyperparameters.values import modify_hyper_parameter_bounds
= modify_hyper_parameter_bounds(fun_control, "_L0", bounds=[n_features, n_features])
fun_control = modify_hyper_parameter_bounds(fun_control, "l1", bounds=[6, 13])
fun_control = modify_hyper_parameter_bounds(fun_control, "epochs", bounds=[2, 2])
fun_control = modify_hyper_parameter_bounds(fun_control, "patience", bounds=[2, 6])
fun_control = modify_hyper_parameter_bounds(fun_control, "lr_mult", bounds=[1e-3, 1e-3])
fun_control = modify_hyper_parameter_bounds(fun_control, "sgd_momentum", bounds=[0.9, 0.9]) fun_control
from spotPython.hyperparameters.values import modify_hyper_parameter_levels
= modify_hyper_parameter_levels(fun_control, "optimizer",["Adam", "AdamW", "Adamax", "NAdam"])
fun_control # fun_control = modify_hyper_parameter_levels(fun_control, "optimizer", ["Adam"])
# fun_control = modify_hyper_parameter_levels(fun_control, "leaf_model", ["LinearRegression"])
# fun_control["core_model_hyper_dict"]
= modify_hyper_parameter_bounds(fun_control,
fun_control "lr_mult", bounds=[1e-3, 1e-3])
= modify_hyper_parameter_bounds(fun_control,
fun_control "sgd_momentum", bounds=[0.9, 0.9])
Optimizers are described in Section 14.6.
The evaluation procedure requires the specification of two elements:
The loss function is specified by the key "loss_function"
. We will use CrossEntropy loss for the multiclass-classification task.
from torch.nn import CrossEntropyLoss
= CrossEntropyLoss()
loss_function "loss_function": loss_function}) fun_control.update({
from spotPython.torch.mapk import MAPK
import torch
= MAPK(k=2)
mapk = torch.tensor([0, 1, 2, 2])
target = torch.tensor(
preds
[0.5, 0.2, 0.2], # 0 is in top 2
[0.3, 0.4, 0.2], # 1 is in top 2
[0.2, 0.4, 0.3], # 2 is in top 2
[0.7, 0.2, 0.1], # 2 isn't in top 2
[
]
)
mapk.update(preds, target)print(mapk.compute()) # tensor(0.6250)
tensor(0.6250)
from spotPython.torch.mapk import MAPK
import torchmetrics
= MAPK(k=3)
metric_torch "metric_torch": metric_torch}) fun_control.update({
The following code passes the information about the parameter ranges and bounds to spot
.
# extract the variable types, names, and bounds
from spotPython.hyperparameters.values import (get_bound_values,
get_var_name,
get_var_type,)= get_var_type(fun_control)
var_type = get_var_name(fun_control)
var_name "var_type": var_type,
fun_control.update({"var_name": var_name})
= get_bound_values(fun_control, "lower")
lower = get_bound_values(fun_control, "upper") upper
Now, the dictionary fun_control
contains all information needed for the hyperparameter tuning. Before the hyperparameter tuning is started, it is recommended to take a look at the experimental design. The method gen_design_table
generates a design table as follows:
from spotPython.utils.eda import gen_design_table
print(gen_design_table(fun_control))
| name | type | default | lower | upper | transform |
|--------------|--------|-----------|----------|----------|-----------------------|
| _L0 | int | 64 | 6112 | 6112 | None |
| l1 | int | 8 | 6 | 13 | transform_power_2_int |
| dropout_prob | float | 0.01 | 0 | 0.9 | None |
| lr_mult | float | 1.0 | 0.001 | 0.001 | None |
| batch_size | int | 4 | 1 | 4 | transform_power_2_int |
| epochs | int | 4 | 2 | 2 | transform_power_2_int |
| k_folds | int | 1 | 1 | 1 | None |
| patience | int | 2 | 2 | 6 | transform_power_2_int |
| optimizer | factor | SGD | 0 | 3 | None |
| sgd_momentum | float | 0.0 | 0.9 | 0.9 | None |
This allows to check if all information is available and if the information is correct.
fun_torch
The objective function fun_torch
is selected next. It implements an interface from PyTorch
’s training, validation, and testing methods to spotPython
.
from spotPython.fun.hypertorch import HyperTorch
= HyperTorch().fun_torch fun
from spotPython.hyperparameters.values import get_default_hyperparameters_as_array
=TorchHyperDict().load()
hyper_dict= get_default_hyperparameters_as_array(fun_control, hyper_dict) X_start
The spotPython
hyperparameter tuning is started by calling the Spot
function as described in Section 14.12.
import numpy as np
from spotPython.spot import spot
from math import inf
= spot.Spot(fun=fun,
spot_tuner = lower,
lower = upper,
upper = inf,
fun_evals = 1,
fun_repeats = MAX_TIME,
max_time = False,
noise = np.sqrt(np.spacing(1)),
tolerance_x = var_type,
var_type = var_name,
var_name = "y",
infill_criterion = 1,
n_points =123,
seed= 50,
log_level = False,
show_models= True,
show_progress= fun_control,
fun_control ={"init_size": INIT_SIZE,
design_control"repeats": 1},
={"noise": True,
surrogate_control"cod_type": "norm",
"min_theta": -4,
"max_theta": 3,
"n_theta": len(var_name),
"model_fun_evals": 10_000,
"log_level": 50
})=X_start) spot_tuner.run(X_start
config: {'_L0': 6112, 'l1': 1024, 'dropout_prob': 0.26515610830779995, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'Adamax', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3980805697264493
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.15740741789340973
Epoch: 2
Loss on hold-out set: 2.398154276388663
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.1527777910232544
Epoch: 3
Loss on hold-out set: 2.398083730980202
Accuracy on hold-out set: 0.05188679245283019
MAPK value on hold-out data: 0.14351852238178253
Epoch: 4
Loss on hold-out set: 2.3980880931571678
Accuracy on hold-out set: 0.05188679245283019
MAPK value on hold-out data: 0.14351852238178253
Returned to Spot: Validation loss: 2.3980880931571678
----------------------------------------------
config: {'_L0': 6112, 'l1': 256, 'dropout_prob': 0.6368989501775649, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'Adamax', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3985713922752523
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.16981133818626404
Epoch: 2
Loss on hold-out set: 2.3985618285413057
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.1800314486026764
Epoch: 3
Loss on hold-out set: 2.3986199127053314
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.17531448602676392
Epoch: 4
Loss on hold-out set: 2.39854777534053
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.1808176189661026
Returned to Spot: Validation loss: 2.39854777534053
----------------------------------------------
config: {'_L0': 6112, 'l1': 512, 'dropout_prob': 0.06795318590380832, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 8, 'optimizer': 'Adamax', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3978671217864416
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.18317610025405884
Epoch: 2
Loss on hold-out set: 2.397839073864919
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17610064148902893
Epoch: 3
Loss on hold-out set: 2.397796297973057
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.18160377442836761
Epoch: 4
Loss on hold-out set: 2.397783207443525
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.1871069073677063
Returned to Spot: Validation loss: 2.397783207443525
----------------------------------------------
config: {'_L0': 6112, 'l1': 128, 'dropout_prob': 0.456533346732735, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3989526640694097
Accuracy on hold-out set: 0.07075471698113207
MAPK value on hold-out data: 0.1391509622335434
Epoch: 2
Loss on hold-out set: 2.398837669840399
Accuracy on hold-out set: 0.05660377358490566
MAPK value on hold-out data: 0.1320754885673523
Epoch: 3
Loss on hold-out set: 2.3989325154502437
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.14150945842266083
Epoch: 4
Loss on hold-out set: 2.3988740894029723
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.15094342827796936
Returned to Spot: Validation loss: 2.3988740894029723
----------------------------------------------
config: {'_L0': 6112, 'l1': 2048, 'dropout_prob': 0.435068640608333, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3984142850946495
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.125
Epoch: 2
Loss on hold-out set: 2.3983853658040366
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.1180555671453476
Epoch: 3
Loss on hold-out set: 2.3983127894224943
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.125
Epoch: 4
Loss on hold-out set: 2.3982978132036
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.12191358208656311
Returned to Spot: Validation loss: 2.3982978132036
----------------------------------------------
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.3175980093998585, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973114805401496
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.20833329856395721
Epoch: 2
Loss on hold-out set: 2.396766887520844
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.2146226465702057
Epoch: 3
Loss on hold-out set: 2.39617502014592
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.21147796511650085
Epoch: 4
Loss on hold-out set: 2.3950315736374765
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.21698111295700073
Returned to Spot: Validation loss: 2.3950315736374765
----------------------------------------------
config: {'_L0': 6112, 'l1': 128, 'dropout_prob': 0.10217787740156026, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 4, 'optimizer': 'Adam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.399325688680013
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.14351852238178253
Epoch: 2
Loss on hold-out set: 2.3993267748090954
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.1388888955116272
Epoch: 3
Loss on hold-out set: 2.3992787996927896
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.1419753134250641
Epoch: 4
Loss on hold-out set: 2.39928016839204
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.1419752985239029
Returned to Spot: Validation loss: 2.39928016839204
----------------------------------------------
config: {'_L0': 6112, 'l1': 4096, 'dropout_prob': 0.5582660802134882, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 8, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3980693728835494
Accuracy on hold-out set: 0.05188679245283019
MAPK value on hold-out data: 0.1080247014760971
Epoch: 2
Loss on hold-out set: 2.398130081318043
Accuracy on hold-out set: 0.06132075471698113
MAPK value on hold-out data: 0.10648149996995926
Epoch: 3
Loss on hold-out set: 2.397997767836959
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.11419753730297089
Epoch: 4
Loss on hold-out set: 2.397959682676527
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.11651235073804855
Returned to Spot: Validation loss: 2.397959682676527
----------------------------------------------
config: {'_L0': 6112, 'l1': 4096, 'dropout_prob': 0.8475085430864048, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 4, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397449090795697
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.16273587942123413
Epoch: 2
Loss on hold-out set: 2.3975592289330825
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.16116352379322052
Epoch: 3
Loss on hold-out set: 2.397425554833322
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.1595912128686905
Epoch: 4
Loss on hold-out set: 2.3975984870262868
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.15723273158073425
Returned to Spot: Validation loss: 2.3975984870262868
----------------------------------------------
config: {'_L0': 6112, 'l1': 64, 'dropout_prob': 0.8086972970888939, 'lr_mult': 0.001, 'batch_size': 16, 'epochs': 4, 'k_folds': 1, 'patience': 64, 'optimizer': 'Adam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.4004036017826627
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.1517857164144516
Epoch: 2
Loss on hold-out set: 2.400071450642177
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.1607142984867096
Epoch: 3
Loss on hold-out set: 2.4000504868371144
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.1517857164144516
Epoch: 4
Loss on hold-out set: 2.3999014922550748
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.1629464328289032
Returned to Spot: Validation loss: 2.3999014922550748
----------------------------------------------
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.7894801479330897, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 4, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973938429130697
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.20440252125263214
Epoch: 2
Loss on hold-out set: 2.3972465587112137
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.21776728332042694
Epoch: 3
Loss on hold-out set: 2.396949327216958
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.2083333432674408
Epoch: 4
Loss on hold-out set: 2.396790068104582
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.21226416528224945
Returned to Spot: Validation loss: 2.396790068104582
----------------------------------------------
spotPython tuning: 2.3950315736374765 [----------] 0.35%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.6710735654782591, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 64, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397988904197261
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.15723271667957306
Epoch: 2
Loss on hold-out set: 2.397735838620168
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.1603773534297943
Epoch: 3
Loss on hold-out set: 2.3971929685124813
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2083333283662796
Epoch: 4
Loss on hold-out set: 2.397037407137313
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.20518867671489716
Returned to Spot: Validation loss: 2.397037407137313
----------------------------------------------
spotPython tuning: 2.3950315736374765 [----------] 0.67%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.7900113652555035, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397920043380172
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.1705246865749359
Epoch: 2
Loss on hold-out set: 2.397611459096273
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.19212962687015533
Epoch: 3
Loss on hold-out set: 2.3973968823750815
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.21759259700775146
Epoch: 4
Loss on hold-out set: 2.3971683625821716
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.20061728358268738
Returned to Spot: Validation loss: 2.3971683625821716
----------------------------------------------
spotPython tuning: 2.3950315736374765 [----------] 0.84%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.19277948377079854, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397103451332956
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.23899370431900024
Epoch: 2
Loss on hold-out set: 2.3957948504753834
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.23191824555397034
Epoch: 3
Loss on hold-out set: 2.393412916165478
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.23349057137966156
Epoch: 4
Loss on hold-out set: 2.389379121222586
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.2830188572406769
Returned to Spot: Validation loss: 2.389379121222586
----------------------------------------------
spotPython tuning: 2.389379121222586 [----------] 1.47%
config: {'_L0': 6112, 'l1': 512, 'dropout_prob': 0.060808660903882934, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3979099314167813
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.18474839627742767
Epoch: 2
Loss on hold-out set: 2.3978598567674743
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.1941823661327362
Epoch: 3
Loss on hold-out set: 2.3977224871797382
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.18946537375450134
Epoch: 4
Loss on hold-out set: 2.3975800613187395
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.19732701778411865
Returned to Spot: Validation loss: 2.3975800613187395
----------------------------------------------
spotPython tuning: 2.389379121222586 [----------] 1.63%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.18213606561155593, 'lr_mult': 0.001, 'batch_size': 8, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975447901973017
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.18672840297222137
Epoch: 2
Loss on hold-out set: 2.397189661308571
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2013888955116272
Epoch: 3
Loss on hold-out set: 2.396685662092986
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.21759258210659027
Epoch: 4
Loss on hold-out set: 2.3960089683532715
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.1975308656692505
Returned to Spot: Validation loss: 2.3960089683532715
----------------------------------------------
spotPython tuning: 2.389379121222586 [----------] 1.81%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.13233200256075756, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 4, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397072139775978
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.23427671194076538
Epoch: 2
Loss on hold-out set: 2.3959165406676957
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.24528303742408752
Epoch: 3
Loss on hold-out set: 2.393714340227955
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2979559302330017
Epoch: 4
Loss on hold-out set: 2.389391946342756
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.3238993287086487
Returned to Spot: Validation loss: 2.389391946342756
----------------------------------------------
spotPython tuning: 2.389379121222586 [----------] 2.44%
config: {'_L0': 6112, 'l1': 4096, 'dropout_prob': 0.09292259924694028, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975301733556784
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2279873937368393
Epoch: 2
Loss on hold-out set: 2.396934601495851
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.22720122337341309
Epoch: 3
Loss on hold-out set: 2.3958640638387427
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.24056600034236908
Epoch: 4
Loss on hold-out set: 2.3942570416432507
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.24606913328170776
Returned to Spot: Validation loss: 2.3942570416432507
----------------------------------------------
spotPython tuning: 2.389379121222586 [----------] 2.76%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.13895086663047265, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.396697264797283
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2767294645309448
Epoch: 2
Loss on hold-out set: 2.3951494851202333
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.3026728332042694
Epoch: 3
Loss on hold-out set: 2.3924217246613413
Accuracy on hold-out set: 0.2169811320754717
MAPK value on hold-out data: 0.33726415038108826
Epoch: 4
Loss on hold-out set: 2.387000063680253
Accuracy on hold-out set: 0.23113207547169812
MAPK value on hold-out data: 0.3411949574947357
Returned to Spot: Validation loss: 2.387000063680253
----------------------------------------------
spotPython tuning: 2.387000063680253 [----------] 3.43%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.06439896599751695, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397111616044674
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.17924530804157257
Epoch: 2
Loss on hold-out set: 2.395652339143573
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.16902513802051544
Epoch: 3
Loss on hold-out set: 2.3936799044878976
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.1674528270959854
Epoch: 4
Loss on hold-out set: 2.3912858040827625
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.20204398036003113
Returned to Spot: Validation loss: 2.3912858040827625
----------------------------------------------
spotPython tuning: 2.387000063680253 [----------] 4.11%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.15546640677818002, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397697334019643
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.15251575410366058
Epoch: 2
Loss on hold-out set: 2.397228958471766
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.16509436070919037
Epoch: 3
Loss on hold-out set: 2.3966626513679072
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.16981133818626404
Epoch: 4
Loss on hold-out set: 2.395865264928566
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.19575472176074982
Returned to Spot: Validation loss: 2.395865264928566
----------------------------------------------
spotPython tuning: 2.387000063680253 [----------] 4.77%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.14615400105486473, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3969592485787734
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.28616344928741455
Epoch: 2
Loss on hold-out set: 2.395423065941289
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.30031436681747437
Epoch: 3
Loss on hold-out set: 2.392437844906213
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.31367915868759155
Epoch: 4
Loss on hold-out set: 2.3862778510687486
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.3262578248977661
Returned to Spot: Validation loss: 2.3862778510687486
----------------------------------------------
spotPython tuning: 2.3862778510687486 [#---------] 5.48%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.12528681110846807, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397440051132778
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.21855342388153076
Epoch: 2
Loss on hold-out set: 2.396888939839489
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.22562891244888306
Epoch: 3
Loss on hold-out set: 2.3961525503194556
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.22405655682086945
Epoch: 4
Loss on hold-out set: 2.3951557852187246
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.2067609578371048
Returned to Spot: Validation loss: 2.3951557852187246
----------------------------------------------
spotPython tuning: 2.3862778510687486 [#---------] 6.15%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.10807358039768722, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975375215962247
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.20361635088920593
Epoch: 2
Loss on hold-out set: 2.3970631585930877
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.18867924809455872
Epoch: 3
Loss on hold-out set: 2.3964440305277988
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1933962106704712
Epoch: 4
Loss on hold-out set: 2.3954852054703912
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.19968552887439728
Returned to Spot: Validation loss: 2.3954852054703912
----------------------------------------------
spotPython tuning: 2.3862778510687486 [#---------] 6.79%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.11815002692942611, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397423615995443
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.18238994479179382
Epoch: 2
Loss on hold-out set: 2.396933614083056
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.18867924809455872
Epoch: 3
Loss on hold-out set: 2.3963320075340993
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19025160372257233
Epoch: 4
Loss on hold-out set: 2.395507706786102
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19654090702533722
Returned to Spot: Validation loss: 2.395507706786102
----------------------------------------------
spotPython tuning: 2.3862778510687486 [#---------] 7.43%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.13620340138857875, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3977840171670013
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.18632075190544128
Epoch: 2
Loss on hold-out set: 2.3975013539476215
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.21305032074451447
Epoch: 3
Loss on hold-out set: 2.3971912905855
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.2012578845024109
Epoch: 4
Loss on hold-out set: 2.3967186100078077
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.1878930777311325
Returned to Spot: Validation loss: 2.3967186100078077
----------------------------------------------
spotPython tuning: 2.3862778510687486 [#---------] 8.05%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.16050204287317724, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 32, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.396700586912767
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2987420856952667
Epoch: 2
Loss on hold-out set: 2.3948713361092335
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.3105345368385315
Epoch: 3
Loss on hold-out set: 2.3916190795178682
Accuracy on hold-out set: 0.20754716981132076
MAPK value on hold-out data: 0.28066033124923706
Epoch: 4
Loss on hold-out set: 2.3856273349725976
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.26493707299232483
Returned to Spot: Validation loss: 2.3856273349725976
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 8.69%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09110021574244813, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975045636015118
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.21855342388153076
Epoch: 2
Loss on hold-out set: 2.3968885439746783
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.2539307773113251
Epoch: 3
Loss on hold-out set: 2.3961802091238633
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.27358484268188477
Epoch: 4
Loss on hold-out set: 2.39500677810525
Accuracy on hold-out set: 0.22169811320754718
MAPK value on hold-out data: 0.2948112487792969
Returned to Spot: Validation loss: 2.39500677810525
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 9.35%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.06890213159939086, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972784415730892
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.19654089212417603
Epoch: 2
Loss on hold-out set: 2.3966817788358004
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.20990565419197083
Epoch: 3
Loss on hold-out set: 2.3958914257445425
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.23034588992595673
Epoch: 4
Loss on hold-out set: 2.3948483287163502
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2421383410692215
Returned to Spot: Validation loss: 2.3948483287163502
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 9.97%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0558348539799957, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975754976272583
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.2012578845024109
Epoch: 2
Loss on hold-out set: 2.397182586058131
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.19811323285102844
Epoch: 3
Loss on hold-out set: 2.396720787264266
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.20990565419197083
Epoch: 4
Loss on hold-out set: 2.3960996416379823
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.21698111295700073
Returned to Spot: Validation loss: 2.3960996416379823
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 10.59%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08981734748370006, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39781036017076
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.19889935851097107
Epoch: 2
Loss on hold-out set: 2.3974060517437055
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2342766970396042
Epoch: 3
Loss on hold-out set: 2.396831879075968
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23034587502479553
Epoch: 4
Loss on hold-out set: 2.396133634279359
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.23034587502479553
Returned to Spot: Validation loss: 2.396133634279359
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 11.20%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09158000659876485, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397331566180823
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.22012579441070557
Epoch: 2
Loss on hold-out set: 2.396729480545476
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.29402512311935425
Epoch: 3
Loss on hold-out set: 2.396060325064749
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.30738985538482666
Epoch: 4
Loss on hold-out set: 2.3951294557103573
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.33569180965423584
Returned to Spot: Validation loss: 2.3951294557103573
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 11.80%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09106644899566055, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397423213382937
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.21305032074451447
Epoch: 2
Loss on hold-out set: 2.3968667691608645
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.2853773236274719
Epoch: 3
Loss on hold-out set: 2.396169864906455
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.28616344928741455
Epoch: 4
Loss on hold-out set: 2.3950917450886853
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2759433686733246
Returned to Spot: Validation loss: 2.3950917450886853
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 12.42%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09067301764229323, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974063081561394
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.21226412057876587
Epoch: 2
Loss on hold-out set: 2.39685365164055
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.21933957934379578
Epoch: 3
Loss on hold-out set: 2.39617608628183
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.22955970466136932
Epoch: 4
Loss on hold-out set: 2.3952333724723673
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.23191815614700317
Returned to Spot: Validation loss: 2.3952333724723673
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 13.03%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09080312243722831, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975971352379277
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.1808176040649414
Epoch: 2
Loss on hold-out set: 2.397065315606459
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.1745283007621765
Epoch: 3
Loss on hold-out set: 2.396321175233373
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.16509436070919037
Epoch: 4
Loss on hold-out set: 2.395322822174936
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.16823899745941162
Returned to Spot: Validation loss: 2.395322822174936
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 13.65%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.09061979097208507, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973867690788127
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.19575472176074982
Epoch: 2
Loss on hold-out set: 2.3968471018773205
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2138364613056183
Epoch: 3
Loss on hold-out set: 2.396116738049489
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.24135218560695648
Epoch: 4
Loss on hold-out set: 2.3951165496178395
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2775156497955322
Returned to Spot: Validation loss: 2.3951165496178395
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 14.27%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0900256156089932, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974888527168416
Accuracy on hold-out set: 0.07075471698113207
MAPK value on hold-out data: 0.1855345517396927
Epoch: 2
Loss on hold-out set: 2.3967920136901566
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.2499999850988388
Epoch: 3
Loss on hold-out set: 2.3959404320087074
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.27830183506011963
Epoch: 4
Loss on hold-out set: 2.3948177998920657
Accuracy on hold-out set: 0.23113207547169812
MAPK value on hold-out data: 0.32154083251953125
Returned to Spot: Validation loss: 2.3948177998920657
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#---------] 14.88%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08966950794635833, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397404504272173
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.23191823065280914
Epoch: 2
Loss on hold-out set: 2.3968356285455092
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.24764148890972137
Epoch: 3
Loss on hold-out set: 2.396087702715172
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2696540653705597
Epoch: 4
Loss on hold-out set: 2.395176259976513
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2649371027946472
Returned to Spot: Validation loss: 2.395176259976513
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 15.53%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08947136090983329, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397610603638415
Accuracy on hold-out set: 0.06132075471698113
MAPK value on hold-out data: 0.16902516782283783
Epoch: 2
Loss on hold-out set: 2.397065952139081
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.20204399526119232
Epoch: 3
Loss on hold-out set: 2.396347702674146
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.22484275698661804
Epoch: 4
Loss on hold-out set: 2.395444728293509
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24449683725833893
Returned to Spot: Validation loss: 2.395444728293509
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 16.15%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08951425740140692, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397337070051229
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.20990562438964844
Epoch: 2
Loss on hold-out set: 2.3967167701361314
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.23191818594932556
Epoch: 3
Loss on hold-out set: 2.395952915245632
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.24371063709259033
Epoch: 4
Loss on hold-out set: 2.394885650220907
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.26650938391685486
Returned to Spot: Validation loss: 2.394885650220907
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 16.83%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08918532795211898, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397609881634982
Accuracy on hold-out set: 0.08018867924528301
MAPK value on hold-out data: 0.15172958374023438
Epoch: 2
Loss on hold-out set: 2.3970171033211476
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.1871069222688675
Epoch: 3
Loss on hold-out set: 2.3963475227355957
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.21069180965423584
Epoch: 4
Loss on hold-out set: 2.3953429033171454
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.220911905169487
Returned to Spot: Validation loss: 2.3953429033171454
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 17.48%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08914245414635565, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3979003676828348
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.1470126062631607
Epoch: 2
Loss on hold-out set: 2.3972894425662057
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.16509436070919037
Epoch: 3
Loss on hold-out set: 2.3965474277172447
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.18867923319339752
Epoch: 4
Loss on hold-out set: 2.3955322683982128
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.21226415038108826
Returned to Spot: Validation loss: 2.3955322683982128
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 18.12%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08930719413841784, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397019532491576
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.31682389974594116
Epoch: 2
Loss on hold-out set: 2.396302250196349
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.3270440399646759
Epoch: 3
Loss on hold-out set: 2.395412321360606
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.331760972738266
Epoch: 4
Loss on hold-out set: 2.394127121511495
Accuracy on hold-out set: 0.2169811320754717
MAPK value on hold-out data: 0.3333333134651184
Returned to Spot: Validation loss: 2.394127121511495
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 18.74%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08943314475336468, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397651933274179
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.23270440101623535
Epoch: 2
Loss on hold-out set: 2.3971106713672854
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.30974841117858887
Epoch: 3
Loss on hold-out set: 2.39641627500642
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.3176099956035614
Epoch: 4
Loss on hold-out set: 2.3954921983323008
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.3396226465702057
Returned to Spot: Validation loss: 2.3954921983323008
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 19.38%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08952288757366074, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397435449204355
Accuracy on hold-out set: 0.07075471698113207
MAPK value on hold-out data: 0.16430819034576416
Epoch: 2
Loss on hold-out set: 2.396874209619918
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.1878930926322937
Epoch: 3
Loss on hold-out set: 2.3960121307732924
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19261004030704498
Epoch: 4
Loss on hold-out set: 2.394875449954339
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.22012579441070557
Returned to Spot: Validation loss: 2.394875449954339
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 20.02%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08902987242915406, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397615945564126
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.16823898255825043
Epoch: 2
Loss on hold-out set: 2.397011601699973
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.21698111295700073
Epoch: 3
Loss on hold-out set: 2.396247539880141
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.26100626587867737
Epoch: 4
Loss on hold-out set: 2.39516078526119
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.29481130838394165
Returned to Spot: Validation loss: 2.39516078526119
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 20.66%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08919205339692007, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974263668060303
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.209119513630867
Epoch: 2
Loss on hold-out set: 2.3969092661479734
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.23034590482711792
Epoch: 3
Loss on hold-out set: 2.3962003554937974
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2499999850988388
Epoch: 4
Loss on hold-out set: 2.3951582458783998
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.24764153361320496
Returned to Spot: Validation loss: 2.3951582458783998
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 21.29%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08906708253084379, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3978287656352206
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.15251575410366058
Epoch: 2
Loss on hold-out set: 2.397273643961493
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.17688675224781036
Epoch: 3
Loss on hold-out set: 2.3965619487582512
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.22012577950954437
Epoch: 4
Loss on hold-out set: 2.395521105460401
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.21698112785816193
Returned to Spot: Validation loss: 2.395521105460401
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 21.93%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08894338233306005, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397323473444525
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.2830188274383545
Epoch: 2
Loss on hold-out set: 2.396685735234674
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.2767295241355896
Epoch: 3
Loss on hold-out set: 2.395880031135847
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2539307475090027
Epoch: 4
Loss on hold-out set: 2.394791398408278
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2602200508117676
Returned to Spot: Validation loss: 2.394791398408278
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 22.57%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0889417906352505, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397804710100282
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.1391509622335434
Epoch: 2
Loss on hold-out set: 2.397265852622266
Accuracy on hold-out set: 0.07075471698113207
MAPK value on hold-out data: 0.14150944352149963
Epoch: 3
Loss on hold-out set: 2.3966349543265575
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.15566039085388184
Epoch: 4
Loss on hold-out set: 2.395777018565052
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.16509434580802917
Returned to Spot: Validation loss: 2.395777018565052
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 23.21%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0893562336937487, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975971352379277
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.15880505740642548
Epoch: 2
Loss on hold-out set: 2.3971161549946047
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1611635386943817
Epoch: 3
Loss on hold-out set: 2.396414594830207
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1816037893295288
Epoch: 4
Loss on hold-out set: 2.395422982719709
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.20361630618572235
Returned to Spot: Validation loss: 2.395422982719709
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 23.85%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0891041557766644, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397318232734248
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.23899370431900024
Epoch: 2
Loss on hold-out set: 2.3967746473708242
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.21305032074451447
Epoch: 3
Loss on hold-out set: 2.396063509977089
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.1949685513973236
Epoch: 4
Loss on hold-out set: 2.3950331885859653
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2004716992378235
Returned to Spot: Validation loss: 2.3950331885859653
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##--------] 24.58%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08901562940576731, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974039037272616
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.2893081307411194
Epoch: 2
Loss on hold-out set: 2.396766664846888
Accuracy on hold-out set: 0.2169811320754717
MAPK value on hold-out data: 0.3034590482711792
Epoch: 3
Loss on hold-out set: 2.395917253674201
Accuracy on hold-out set: 0.2169811320754717
MAPK value on hold-out data: 0.32232701778411865
Epoch: 4
Loss on hold-out set: 2.394782799594807
Accuracy on hold-out set: 0.2358490566037736
MAPK value on hold-out data: 0.30660372972488403
Returned to Spot: Validation loss: 2.394782799594807
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 25.29%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08871914437891885, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974993768728003
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2004716694355011
Epoch: 2
Loss on hold-out set: 2.3968968818772516
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.23191826045513153
Epoch: 3
Loss on hold-out set: 2.396146942984383
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.23270440101623535
Epoch: 4
Loss on hold-out set: 2.3950949592410393
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.250786155462265
Returned to Spot: Validation loss: 2.3950949592410393
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 25.92%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08882856874816587, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3971499969374457
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2704402208328247
Epoch: 2
Loss on hold-out set: 2.3964717005783656
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.29952821135520935
Epoch: 3
Loss on hold-out set: 2.3956415383320935
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.29402509331703186
Epoch: 4
Loss on hold-out set: 2.394447328909388
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.2979559302330017
Returned to Spot: Validation loss: 2.394447328909388
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 26.55%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0886041722170289, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975442355533816
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17059749364852905
Epoch: 2
Loss on hold-out set: 2.3971265689382015
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17767293751239777
Epoch: 3
Loss on hold-out set: 2.3965011925067543
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.16823899745941162
Epoch: 4
Loss on hold-out set: 2.3957312399486326
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.16194969415664673
Returned to Spot: Validation loss: 2.3957312399486326
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 27.18%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0889899335647692, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973029784436495
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2075471580028534
Epoch: 2
Loss on hold-out set: 2.396698256708541
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2075471580028534
Epoch: 3
Loss on hold-out set: 2.395893591754841
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.21855343878269196
Epoch: 4
Loss on hold-out set: 2.39480863202293
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2358490228652954
Returned to Spot: Validation loss: 2.39480863202293
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 27.83%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08880775574169078, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974315737778285
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2083333432674408
Epoch: 2
Loss on hold-out set: 2.3968047173518054
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.26650938391685486
Epoch: 3
Loss on hold-out set: 2.395832565595519
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.2720125615596771
Epoch: 4
Loss on hold-out set: 2.394766371205168
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2696540355682373
Returned to Spot: Validation loss: 2.394766371205168
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 28.46%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08859848489585893, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397242991429455
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.2295597344636917
Epoch: 2
Loss on hold-out set: 2.396629607902383
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.21776728332042694
Epoch: 3
Loss on hold-out set: 2.395867446683488
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.21226415038108826
Epoch: 4
Loss on hold-out set: 2.3947508312621206
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.22562894225120544
Returned to Spot: Validation loss: 2.3947508312621206
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 29.12%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08810362894344526, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39743314374168
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19811318814754486
Epoch: 2
Loss on hold-out set: 2.396861006628792
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.22012577950954437
Epoch: 3
Loss on hold-out set: 2.396034706313655
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.23191821575164795
Epoch: 4
Loss on hold-out set: 2.3948447231976493
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.2287735641002655
Returned to Spot: Validation loss: 2.3948447231976493
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 29.75%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08783621163952181, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973595961084904
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.19025154411792755
Epoch: 2
Loss on hold-out set: 2.3966763986731476
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.22405657172203064
Epoch: 3
Loss on hold-out set: 2.3957654597624294
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2908804416656494
Epoch: 4
Loss on hold-out set: 2.394543026978115
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.3238993287086487
Returned to Spot: Validation loss: 2.394543026978115
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 30.39%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08768512497986942, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39740762620602
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2216981202363968
Epoch: 2
Loss on hold-out set: 2.3969696152885005
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2342766970396042
Epoch: 3
Loss on hold-out set: 2.3963293804312653
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.23270437121391296
Epoch: 4
Loss on hold-out set: 2.395515059525112
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.23899365961551666
Returned to Spot: Validation loss: 2.395515059525112
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 31.02%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08774460334025179, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972662687301636
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24056601524353027
Epoch: 2
Loss on hold-out set: 2.396669884897628
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.29245278239250183
Epoch: 3
Loss on hold-out set: 2.3959843999934645
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.3223269581794739
Epoch: 4
Loss on hold-out set: 2.3950051811506166
Accuracy on hold-out set: 0.21226415094339623
MAPK value on hold-out data: 0.32311317324638367
Returned to Spot: Validation loss: 2.3950051811506166
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 31.66%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08757158189647335, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397391775868974
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2138364315032959
Epoch: 2
Loss on hold-out set: 2.3968084533259555
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2633647620677948
Epoch: 3
Loss on hold-out set: 2.396045390165077
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.26650938391685486
Epoch: 4
Loss on hold-out set: 2.394986885898518
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2625785768032074
Returned to Spot: Validation loss: 2.394986885898518
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 32.36%
config: {'_L0': 6112, 'l1': 4096, 'dropout_prob': 0.14469425596769764, 'lr_mult': 0.001, 'batch_size': 4, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'NAdam', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397575077020897
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2555031180381775
Epoch: 2
Loss on hold-out set: 2.3972968470375493
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.24606911838054657
Epoch: 3
Loss on hold-out set: 2.396989102633494
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.25864776968955994
Epoch: 4
Loss on hold-out set: 2.3965118516166255
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.27201253175735474
Returned to Spot: Validation loss: 2.3965118516166255
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 32.62%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08738011261671509, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974588547112807
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.19732703268527985
Epoch: 2
Loss on hold-out set: 2.3969167448439688
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2279873937368393
Epoch: 3
Loss on hold-out set: 2.396156038878099
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2499999850988388
Epoch: 4
Loss on hold-out set: 2.3950668168517777
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.26022011041641235
Returned to Spot: Validation loss: 2.3950668168517777
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 33.35%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08724987453827782, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397341528028812
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2413521707057953
Epoch: 2
Loss on hold-out set: 2.39674363946015
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2680816948413849
Epoch: 3
Loss on hold-out set: 2.395970063389472
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2696540653705597
Epoch: 4
Loss on hold-out set: 2.3948776564508116
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2751571834087372
Returned to Spot: Validation loss: 2.3948776564508116
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 34.10%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08740137645393235, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397308459821737
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.22877353429794312
Epoch: 2
Loss on hold-out set: 2.396661007179404
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2413521707057953
Epoch: 3
Loss on hold-out set: 2.395857768238715
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2492138296365738
Epoch: 4
Loss on hold-out set: 2.3947137481761427
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2633647322654724
Returned to Spot: Validation loss: 2.3947137481761427
----------------------------------------------
spotPython tuning: 2.3856273349725976 [###-------] 34.86%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08705157856564086, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397358480489479
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2617924213409424
Epoch: 2
Loss on hold-out set: 2.396820273039476
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.25943395495414734
Epoch: 3
Loss on hold-out set: 2.396119479863149
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.23270441591739655
Epoch: 4
Loss on hold-out set: 2.395125314874469
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2358490377664566
Returned to Spot: Validation loss: 2.395125314874469
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 35.64%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08655254781576151, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397447426364107
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17059749364852905
Epoch: 2
Loss on hold-out set: 2.396839384762746
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19025154411792755
Epoch: 3
Loss on hold-out set: 2.3960533569443903
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.20204398036003113
Epoch: 4
Loss on hold-out set: 2.394933893995465
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.19889934360980988
Returned to Spot: Validation loss: 2.394933893995465
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 36.44%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08629329627362926, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397417183192271
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.19811320304870605
Epoch: 2
Loss on hold-out set: 2.39684902946904
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.2130502611398697
Epoch: 3
Loss on hold-out set: 2.3960598752183735
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.2279874086380005
Epoch: 4
Loss on hold-out set: 2.3950974154022506
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.23742134869098663
Returned to Spot: Validation loss: 2.3950974154022506
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 37.22%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.086616292406231, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972231801950707
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.2499999850988388
Epoch: 2
Loss on hold-out set: 2.396780682059954
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.23899370431900024
Epoch: 3
Loss on hold-out set: 2.396157494131124
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.24606919288635254
Epoch: 4
Loss on hold-out set: 2.395236127781418
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2806603014469147
Returned to Spot: Validation loss: 2.395236127781418
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 37.96%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08629622012497637, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975964379760453
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.19339624047279358
Epoch: 2
Loss on hold-out set: 2.397119108236061
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19339624047279358
Epoch: 3
Loss on hold-out set: 2.396525610168025
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2012578696012497
Epoch: 4
Loss on hold-out set: 2.395726014982979
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19732703268527985
Returned to Spot: Validation loss: 2.395726014982979
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 38.90%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08755482938392858, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3976448077075885
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19339622557163239
Epoch: 2
Loss on hold-out set: 2.3971637262488312
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.20518866181373596
Epoch: 3
Loss on hold-out set: 2.3965664607173993
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.21698111295700073
Epoch: 4
Loss on hold-out set: 2.39570292886698
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.21540877223014832
Returned to Spot: Validation loss: 2.39570292886698
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 39.88%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08760988179144982, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972128674669086
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.18317611515522003
Epoch: 2
Loss on hold-out set: 2.3967550205734542
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.20204399526119232
Epoch: 3
Loss on hold-out set: 2.3961834030331306
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.21698111295700073
Epoch: 4
Loss on hold-out set: 2.3953154919282444
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.21855342388153076
Returned to Spot: Validation loss: 2.3953154919282444
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 40.92%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08807388522222931, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397221122147902
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.23742136359214783
Epoch: 2
Loss on hold-out set: 2.3966071155836
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.25943395495414734
Epoch: 3
Loss on hold-out set: 2.3957608780770934
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.2822326719760895
Epoch: 4
Loss on hold-out set: 2.3944713866935587
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.32389935851097107
Returned to Spot: Validation loss: 2.3944713866935587
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 41.84%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08749917604481748, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39747173831148
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.22091194987297058
Epoch: 2
Loss on hold-out set: 2.396832715790227
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2672955393791199
Epoch: 3
Loss on hold-out set: 2.3960577114573063
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2822326123714447
Epoch: 4
Loss on hold-out set: 2.394935135571462
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.30503135919570923
Returned to Spot: Validation loss: 2.394935135571462
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 42.68%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08733018156482725, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397481432500875
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1745283156633377
Epoch: 2
Loss on hold-out set: 2.3968537303636657
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.21619494259357452
Epoch: 3
Loss on hold-out set: 2.3961375974259287
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.23034587502479553
Epoch: 4
Loss on hold-out set: 2.3951101460546815
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.23427674174308777
Returned to Spot: Validation loss: 2.3951101460546815
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 43.55%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08766157550448957, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973046406260075
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.20361635088920593
Epoch: 2
Loss on hold-out set: 2.3967517187010565
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2578616142272949
Epoch: 3
Loss on hold-out set: 2.395987533173471
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.2720125615596771
Epoch: 4
Loss on hold-out set: 2.3949501536927134
Accuracy on hold-out set: 0.20754716981132076
MAPK value on hold-out data: 0.28852197527885437
Returned to Spot: Validation loss: 2.3949501536927134
----------------------------------------------
spotPython tuning: 2.3856273349725976 [####------] 44.40%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08711861053375036, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397205834118825
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.22641508281230927
Epoch: 2
Loss on hold-out set: 2.3965125218877255
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.27122634649276733
Epoch: 3
Loss on hold-out set: 2.3957258777798347
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2908804416656494
Epoch: 4
Loss on hold-out set: 2.394466026773993
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2995282709598541
Returned to Spot: Validation loss: 2.394466026773993
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 45.25%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08713801670926113, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973569015287004
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2845911383628845
Epoch: 2
Loss on hold-out set: 2.3968567488328465
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.3238993287086487
Epoch: 3
Loss on hold-out set: 2.3960934967364906
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.316823810338974
Epoch: 4
Loss on hold-out set: 2.3950595270912602
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.31603771448135376
Returned to Spot: Validation loss: 2.3950595270912602
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 46.23%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08703910795297276, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974783263116515
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.19732706248760223
Epoch: 2
Loss on hold-out set: 2.396938278989972
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.20361635088920593
Epoch: 3
Loss on hold-out set: 2.3961974337415874
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2004716992378235
Epoch: 4
Loss on hold-out set: 2.395132361717944
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2004716992378235
Returned to Spot: Validation loss: 2.395132361717944
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 47.08%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08661773534835199, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397219219297733
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.2429244965314865
Epoch: 2
Loss on hold-out set: 2.3966517043563553
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.25786155462265015
Epoch: 3
Loss on hold-out set: 2.3958735016157044
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2806603014469147
Epoch: 4
Loss on hold-out set: 2.394813447628381
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.3223269581794739
Returned to Spot: Validation loss: 2.394813447628381
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 47.87%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08625100551470281, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975740198819144
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.18238990008831024
Epoch: 2
Loss on hold-out set: 2.396988621297872
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.19968551397323608
Epoch: 3
Loss on hold-out set: 2.3963698171219736
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.21383649110794067
Epoch: 4
Loss on hold-out set: 2.395548975692605
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.22405660152435303
Returned to Spot: Validation loss: 2.395548975692605
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 48.68%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08682011391855202, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972422221921525
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.21226413547992706
Epoch: 2
Loss on hold-out set: 2.3966372800323197
Accuracy on hold-out set: 0.09433962264150944
MAPK value on hold-out data: 0.20283019542694092
Epoch: 3
Loss on hold-out set: 2.3958438095056787
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19811320304870605
Epoch: 4
Loss on hold-out set: 2.394684762324927
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.20597484707832336
Returned to Spot: Validation loss: 2.394684762324927
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 49.46%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08687531808521552, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397346606794393
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.1540880799293518
Epoch: 2
Loss on hold-out set: 2.3967172469732896
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.1949685662984848
Epoch: 3
Loss on hold-out set: 2.3958296078555987
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.19889935851097107
Epoch: 4
Loss on hold-out set: 2.394533933333631
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2154088169336319
Returned to Spot: Validation loss: 2.394533933333631
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 50.21%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0865237065661076, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397424333500412
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.22327041625976562
Epoch: 2
Loss on hold-out set: 2.3969103705208257
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2476414442062378
Epoch: 3
Loss on hold-out set: 2.396162021834895
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.23270440101623535
Epoch: 4
Loss on hold-out set: 2.395147499048485
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.22484271228313446
Returned to Spot: Validation loss: 2.395147499048485
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 50.99%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08651475151527585, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972096195760764
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.2342766970396042
Epoch: 2
Loss on hold-out set: 2.3966176779765003
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2641508877277374
Epoch: 3
Loss on hold-out set: 2.3958487510681152
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2743709981441498
Epoch: 4
Loss on hold-out set: 2.3947930380983173
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.277515709400177
Returned to Spot: Validation loss: 2.3947930380983173
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 51.76%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0862377209763059, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397357331131989
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.2688679099082947
Epoch: 2
Loss on hold-out set: 2.396740690717157
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.278301864862442
Epoch: 3
Loss on hold-out set: 2.3959791795262753
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.28694963455200195
Epoch: 4
Loss on hold-out set: 2.3949394810874507
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.31603771448135376
Returned to Spot: Validation loss: 2.3949394810874507
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 52.55%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08605461331440888, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973494633188785
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.24606911838054657
Epoch: 2
Loss on hold-out set: 2.3967568042143337
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2838049829006195
Epoch: 3
Loss on hold-out set: 2.3959540556061945
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2877357602119446
Epoch: 4
Loss on hold-out set: 2.3949013656040408
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2916666567325592
Returned to Spot: Validation loss: 2.3949013656040408
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 53.32%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08583883300946811, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3971007972393394
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2484275847673416
Epoch: 2
Loss on hold-out set: 2.396569402712696
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.24685527384281158
Epoch: 3
Loss on hold-out set: 2.3957810424408823
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.24056600034236908
Epoch: 4
Loss on hold-out set: 2.394623925101082
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2350628674030304
Returned to Spot: Validation loss: 2.394623925101082
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 54.12%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08540890318136236, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3976264922124035
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.15566042065620422
Epoch: 2
Loss on hold-out set: 2.397104004643998
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.23113206028938293
Epoch: 3
Loss on hold-out set: 2.3963763826298266
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.2547169625759125
Epoch: 4
Loss on hold-out set: 2.395343524105144
Accuracy on hold-out set: 0.1650943396226415
MAPK value on hold-out data: 0.27908799052238464
Returned to Spot: Validation loss: 2.395343524105144
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#####-----] 54.88%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08570521283636486, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39737657555994
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.25314459204673767
Epoch: 2
Loss on hold-out set: 2.396861380001284
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.22641503810882568
Epoch: 3
Loss on hold-out set: 2.396214912522514
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.22955970466136932
Epoch: 4
Loss on hold-out set: 2.3952668252980933
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.2272011935710907
Returned to Spot: Validation loss: 2.3952668252980933
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 55.69%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08562238521110427, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973241999464214
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.2900943160057068
Epoch: 2
Loss on hold-out set: 2.3967320491682806
Accuracy on hold-out set: 0.25
MAPK value on hold-out data: 0.32940244674682617
Epoch: 3
Loss on hold-out set: 2.395845851808224
Accuracy on hold-out set: 0.25943396226415094
MAPK value on hold-out data: 0.34984275698661804
Epoch: 4
Loss on hold-out set: 2.394704485839268
Accuracy on hold-out set: 0.25
MAPK value on hold-out data: 0.3459119200706482
Returned to Spot: Validation loss: 2.394704485839268
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 56.53%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08527451461298183, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973566743562804
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23349054157733917
Epoch: 2
Loss on hold-out set: 2.3967878278696313
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2633647620677948
Epoch: 3
Loss on hold-out set: 2.3959673778066097
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.27279868721961975
Epoch: 4
Loss on hold-out set: 2.394903389912731
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.2759433388710022
Returned to Spot: Validation loss: 2.394903389912731
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 57.40%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0852827902214395, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973495240481393
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.19654086232185364
Epoch: 2
Loss on hold-out set: 2.396852194138293
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.22327041625976562
Epoch: 3
Loss on hold-out set: 2.3963172863114557
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2421383559703827
Epoch: 4
Loss on hold-out set: 2.3955051943940937
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2759433686733246
Returned to Spot: Validation loss: 2.3955051943940937
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 58.25%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08577506224657731, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3971692638577156
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.2696540355682373
Epoch: 2
Loss on hold-out set: 2.396521745987658
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.2499999850988388
Epoch: 3
Loss on hold-out set: 2.3955104620951526
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.24842767417430878
Epoch: 4
Loss on hold-out set: 2.39415838133614
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.2358490377664566
Returned to Spot: Validation loss: 2.39415838133614
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 59.17%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08518889897278849, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397489711923419
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.18396228551864624
Epoch: 2
Loss on hold-out set: 2.3969660637513646
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.19025155901908875
Epoch: 3
Loss on hold-out set: 2.396170868063873
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.18474844098091125
Epoch: 4
Loss on hold-out set: 2.3950608878765465
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.18317611515522003
Returned to Spot: Validation loss: 2.3950608878765465
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 59.98%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08493582342137915, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973090581174166
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.2633647620677948
Epoch: 2
Loss on hold-out set: 2.3966640166516573
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.31446540355682373
Epoch: 3
Loss on hold-out set: 2.395869925337018
Accuracy on hold-out set: 0.24056603773584906
MAPK value on hold-out data: 0.37264150381088257
Epoch: 4
Loss on hold-out set: 2.3948119271476314
Accuracy on hold-out set: 0.2783018867924528
MAPK value on hold-out data: 0.3891509771347046
Returned to Spot: Validation loss: 2.3948119271476314
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 60.80%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08466731097810193, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397526608323151
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2350628674030304
Epoch: 2
Loss on hold-out set: 2.397066021865269
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.24606914818286896
Epoch: 3
Loss on hold-out set: 2.3963744370442517
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.24764147400856018
Epoch: 4
Loss on hold-out set: 2.395404480538278
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.25786158442497253
Returned to Spot: Validation loss: 2.395404480538278
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 61.76%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0852750546665499, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972988331092977
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2012578696012497
Epoch: 2
Loss on hold-out set: 2.396726765722599
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.25235846638679504
Epoch: 3
Loss on hold-out set: 2.3959612778897554
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.25314459204673767
Epoch: 4
Loss on hold-out set: 2.394933279955162
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.25314459204673767
Returned to Spot: Validation loss: 2.394933279955162
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 62.78%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08512333011673164, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397283286418555
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.20597484707832336
Epoch: 2
Loss on hold-out set: 2.3966746127830363
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.22641505300998688
Epoch: 3
Loss on hold-out set: 2.3958295426278746
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.23742131888866425
Epoch: 4
Loss on hold-out set: 2.39467606004679
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.24528297781944275
Returned to Spot: Validation loss: 2.39467606004679
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 63.78%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08458705900978986, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972373076204985
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1878930777311325
Epoch: 2
Loss on hold-out set: 2.3966521092180937
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2075471132993698
Epoch: 3
Loss on hold-out set: 2.395895334909547
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19654084742069244
Epoch: 4
Loss on hold-out set: 2.394835724020904
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.2059747874736786
Returned to Spot: Validation loss: 2.394835724020904
----------------------------------------------
spotPython tuning: 2.3856273349725976 [######----] 64.79%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08449725255467057, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397298959066283
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23427671194076538
Epoch: 2
Loss on hold-out set: 2.3966129928264976
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2680816948413849
Epoch: 3
Loss on hold-out set: 2.3958344347072096
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.25157228112220764
Epoch: 4
Loss on hold-out set: 2.3946502186217398
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24449683725833893
Returned to Spot: Validation loss: 2.3946502186217398
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 65.82%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08407190071512578, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974624264915034
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.24528297781944275
Epoch: 2
Loss on hold-out set: 2.396987127807905
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.2704402208328247
Epoch: 3
Loss on hold-out set: 2.3962974863232307
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2838049829006195
Epoch: 4
Loss on hold-out set: 2.3951991931447445
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2830187976360321
Returned to Spot: Validation loss: 2.3951991931447445
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 66.89%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08425065306524619, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397372884570428
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.179245263338089
Epoch: 2
Loss on hold-out set: 2.396895278174922
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.21147790551185608
Epoch: 3
Loss on hold-out set: 2.396099677625692
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.22641503810882568
Epoch: 4
Loss on hold-out set: 2.3950968800850636
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.23742134869098663
Returned to Spot: Validation loss: 2.3950968800850636
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 67.93%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08417670644923704, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973298747584506
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.22562892735004425
Epoch: 2
Loss on hold-out set: 2.3967530120093867
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.28066036105155945
Epoch: 3
Loss on hold-out set: 2.396086524117668
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.30817607045173645
Epoch: 4
Loss on hold-out set: 2.395052765900234
Accuracy on hold-out set: 0.23113207547169812
MAPK value on hold-out data: 0.330974817276001
Returned to Spot: Validation loss: 2.395052765900234
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 69.16%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08417918420369369, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975374158823266
Accuracy on hold-out set: 0.0660377358490566
MAPK value on hold-out data: 0.2004716992378235
Epoch: 2
Loss on hold-out set: 2.3970119480816825
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2680817246437073
Epoch: 3
Loss on hold-out set: 2.3963106533266463
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2916666567325592
Epoch: 4
Loss on hold-out set: 2.3953741271540805
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.29323896765708923
Returned to Spot: Validation loss: 2.3953741271540805
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 70.28%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0845377349943858, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397714432680382
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.19103772938251495
Epoch: 2
Loss on hold-out set: 2.3971896756370112
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.22720122337341309
Epoch: 3
Loss on hold-out set: 2.3965370250198075
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.262578547000885
Epoch: 4
Loss on hold-out set: 2.3955917605813943
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.27122634649276733
Returned to Spot: Validation loss: 2.3955917605813943
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 71.38%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08509014754816153, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3974157459331007
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.19496853649616241
Epoch: 2
Loss on hold-out set: 2.396835927693349
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.24056604504585266
Epoch: 3
Loss on hold-out set: 2.395985571843273
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.24449683725833893
Epoch: 4
Loss on hold-out set: 2.3948009216560506
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.25157231092453003
Returned to Spot: Validation loss: 2.3948009216560506
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 72.47%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0848849250296861, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397466832736753
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19732701778411865
Epoch: 2
Loss on hold-out set: 2.3969073992855146
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2279873937368393
Epoch: 3
Loss on hold-out set: 2.3964097072493353
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.2578616142272949
Epoch: 4
Loss on hold-out set: 2.3955487057847797
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.2916666865348816
Returned to Spot: Validation loss: 2.3955487057847797
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 73.46%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08532059973010218, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972725868225098
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2688678801059723
Epoch: 2
Loss on hold-out set: 2.3967276181814805
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.25864776968955994
Epoch: 3
Loss on hold-out set: 2.3960414877477683
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2712263762950897
Epoch: 4
Loss on hold-out set: 2.3949981860394747
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2751571834087372
Returned to Spot: Validation loss: 2.3949981860394747
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#######---] 74.46%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08526144770955008, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973321667257346
Accuracy on hold-out set: 0.1792452830188679
MAPK value on hold-out data: 0.2555031180381775
Epoch: 2
Loss on hold-out set: 2.396693580555466
Accuracy on hold-out set: 0.25
MAPK value on hold-out data: 0.32783010601997375
Epoch: 3
Loss on hold-out set: 2.39585742635547
Accuracy on hold-out set: 0.25471698113207547
MAPK value on hold-out data: 0.3404087424278259
Epoch: 4
Loss on hold-out set: 2.3947381703358777
Accuracy on hold-out set: 0.22641509433962265
MAPK value on hold-out data: 0.31603774428367615
Returned to Spot: Validation loss: 2.3947381703358777
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 75.49%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08516828670802574, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397509496167021
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.19103772938251495
Epoch: 2
Loss on hold-out set: 2.39689438972833
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2161949872970581
Epoch: 3
Loss on hold-out set: 2.3960316855952426
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23349052667617798
Epoch: 4
Loss on hold-out set: 2.394927789580147
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2617924213409424
Returned to Spot: Validation loss: 2.394927789580147
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 76.53%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0850560161659006, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972964579204343
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2429244965314865
Epoch: 2
Loss on hold-out set: 2.396578941705092
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.28066033124923706
Epoch: 3
Loss on hold-out set: 2.395776741909531
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.30188673734664917
Epoch: 4
Loss on hold-out set: 2.394536999036681
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.31525149941444397
Returned to Spot: Validation loss: 2.394536999036681
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 77.56%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08458414256880957, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3969418372748033
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.23742134869098663
Epoch: 2
Loss on hold-out set: 2.3963029429597675
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.24449679255485535
Epoch: 3
Loss on hold-out set: 2.3954126632438517
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2633647322654724
Epoch: 4
Loss on hold-out set: 2.3942096098414005
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.2751571834087372
Returned to Spot: Validation loss: 2.3942096098414005
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 78.67%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08405875829096576, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39732207892076
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2555031180381775
Epoch: 2
Loss on hold-out set: 2.3967793167762035
Accuracy on hold-out set: 0.20754716981132076
MAPK value on hold-out data: 0.2971697449684143
Epoch: 3
Loss on hold-out set: 2.396090473768846
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.2814464867115021
Epoch: 4
Loss on hold-out set: 2.395099347492434
Accuracy on hold-out set: 0.18867924528301888
MAPK value on hold-out data: 0.29481127858161926
Returned to Spot: Validation loss: 2.395099347492434
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 79.87%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08411043508753036, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3978432371931255
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.1878930926322937
Epoch: 2
Loss on hold-out set: 2.3973400412865407
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.22562891244888306
Epoch: 3
Loss on hold-out set: 2.396651067823734
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.25393080711364746
Epoch: 4
Loss on hold-out set: 2.395717092280118
Accuracy on hold-out set: 0.18396226415094338
MAPK value on hold-out data: 0.2633647620677948
Returned to Spot: Validation loss: 2.395717092280118
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 80.88%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08470316280473927, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397134043135733
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2492138147354126
Epoch: 2
Loss on hold-out set: 2.3964645277779058
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24764150381088257
Epoch: 3
Loss on hold-out set: 2.39551521247288
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2555030882358551
Epoch: 4
Loss on hold-out set: 2.3943110861868226
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.26650938391685486
Returned to Spot: Validation loss: 2.3943110861868226
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 81.88%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08418536718662416, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397230658891066
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.20833328366279602
Epoch: 2
Loss on hold-out set: 2.3965917173421607
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.2130502611398697
Epoch: 3
Loss on hold-out set: 2.3958050125050097
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.23427671194076538
Epoch: 4
Loss on hold-out set: 2.394626651170119
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2499999701976776
Returned to Spot: Validation loss: 2.394626651170119
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 82.90%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08382693056341214, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397262022180377
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.247641459107399
Epoch: 2
Loss on hold-out set: 2.3965783344124847
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.25864776968955994
Epoch: 3
Loss on hold-out set: 2.3957088083591103
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.27201253175735474
Epoch: 4
Loss on hold-out set: 2.3945731082052553
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.2963835895061493
Returned to Spot: Validation loss: 2.3945731082052553
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 83.93%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.0833910780755122, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397332013777967
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.23349051177501678
Epoch: 2
Loss on hold-out set: 2.396812724617292
Accuracy on hold-out set: 0.10377358490566038
MAPK value on hold-out data: 0.23270435631275177
Epoch: 3
Loss on hold-out set: 2.3960362290436366
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.22248424589633942
Epoch: 4
Loss on hold-out set: 2.3950805933970325
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23113204538822174
Returned to Spot: Validation loss: 2.3950805933970325
----------------------------------------------
spotPython tuning: 2.3856273349725976 [########--] 84.93%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08345058777432388, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.39756281870716
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1745283007621765
Epoch: 2
Loss on hold-out set: 2.397103620025347
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17688679695129395
Epoch: 3
Loss on hold-out set: 2.3964695773034728
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.1603773534297943
Epoch: 4
Loss on hold-out set: 2.395535372338205
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.16194969415664673
Returned to Spot: Validation loss: 2.395535372338205
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 85.98%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08400857134540214, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3970993554817057
Accuracy on hold-out set: 0.1320754716981132
MAPK value on hold-out data: 0.22720122337341309
Epoch: 2
Loss on hold-out set: 2.3963920710221776
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.23742137849330902
Epoch: 3
Loss on hold-out set: 2.395505372083412
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.2499999850988388
Epoch: 4
Loss on hold-out set: 2.3941670611219585
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.24764148890972137
Returned to Spot: Validation loss: 2.3941670611219585
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 87.02%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08330551441853172, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3975390465754383
Accuracy on hold-out set: 0.16981132075471697
MAPK value on hold-out data: 0.24528297781944275
Epoch: 2
Loss on hold-out set: 2.396999127459976
Accuracy on hold-out set: 0.2028301886792453
MAPK value on hold-out data: 0.2696540653705597
Epoch: 3
Loss on hold-out set: 2.396265097384183
Accuracy on hold-out set: 0.15566037735849056
MAPK value on hold-out data: 0.2547169327735901
Epoch: 4
Loss on hold-out set: 2.395242652803097
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24449685215950012
Returned to Spot: Validation loss: 2.395242652803097
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 88.02%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08354119867015605, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3976548280356065
Accuracy on hold-out set: 0.09905660377358491
MAPK value on hold-out data: 0.17138361930847168
Epoch: 2
Loss on hold-out set: 2.3972388056089295
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.16116352379322052
Epoch: 3
Loss on hold-out set: 2.396736644349008
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17452828586101532
Epoch: 4
Loss on hold-out set: 2.3960609526004433
Accuracy on hold-out set: 0.08490566037735849
MAPK value on hold-out data: 0.17452827095985413
Returned to Spot: Validation loss: 2.3960609526004433
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 89.03%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08468095126331227, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3972297591983147
Accuracy on hold-out set: 0.08962264150943396
MAPK value on hold-out data: 0.2083333283662796
Epoch: 2
Loss on hold-out set: 2.3965890452546894
Accuracy on hold-out set: 0.12735849056603774
MAPK value on hold-out data: 0.23742134869098663
Epoch: 3
Loss on hold-out set: 2.39575131884161
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.2830188572406769
Epoch: 4
Loss on hold-out set: 2.394662713104824
Accuracy on hold-out set: 0.19811320754716982
MAPK value on hold-out data: 0.3333333432674408
Returned to Spot: Validation loss: 2.394662713104824
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 90.04%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08444136006437535, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397586869743635
Accuracy on hold-out set: 0.10849056603773585
MAPK value on hold-out data: 0.19732703268527985
Epoch: 2
Loss on hold-out set: 2.3971934048634655
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24449680745601654
Epoch: 3
Loss on hold-out set: 2.3966010179159776
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.247641459107399
Epoch: 4
Loss on hold-out set: 2.395775999663011
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.2507861256599426
Returned to Spot: Validation loss: 2.395775999663011
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 91.18%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08523901409519642, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3971951120304613
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24528293311595917
Epoch: 2
Loss on hold-out set: 2.3965999900170094
Accuracy on hold-out set: 0.13679245283018868
MAPK value on hold-out data: 0.24371066689491272
Epoch: 3
Loss on hold-out set: 2.39570540752051
Accuracy on hold-out set: 0.1509433962264151
MAPK value on hold-out data: 0.27358487248420715
Epoch: 4
Loss on hold-out set: 2.39459857175935
Accuracy on hold-out set: 0.17452830188679244
MAPK value on hold-out data: 0.30188676714897156
Returned to Spot: Validation loss: 2.39459857175935
----------------------------------------------
spotPython tuning: 2.3856273349725976 [#########-] 93.87%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08500096595715557, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.3973239412847556
Accuracy on hold-out set: 0.07547169811320754
MAPK value on hold-out data: 0.2216980755329132
Epoch: 2
Loss on hold-out set: 2.396727055873511
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.24764147400856018
Epoch: 3
Loss on hold-out set: 2.3959022827868193
Accuracy on hold-out set: 0.19339622641509435
MAPK value on hold-out data: 0.3050313889980316
Epoch: 4
Loss on hold-out set: 2.3948826092594073
Accuracy on hold-out set: 0.25
MAPK value on hold-out data: 0.348270446062088
Returned to Spot: Validation loss: 2.3948826092594073
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##########] 96.44%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.08488807676378791, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397420399593857
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.21462257206439972
Epoch: 2
Loss on hold-out set: 2.3967786195143215
Accuracy on hold-out set: 0.14150943396226415
MAPK value on hold-out data: 0.24135218560695648
Epoch: 3
Loss on hold-out set: 2.3959772654299467
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.2649371027946472
Epoch: 4
Loss on hold-out set: 2.3947303340120136
Accuracy on hold-out set: 0.16037735849056603
MAPK value on hold-out data: 0.27437102794647217
Returned to Spot: Validation loss: 2.3947303340120136
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##########] 98.67%
config: {'_L0': 6112, 'l1': 8192, 'dropout_prob': 0.084511910072702, 'lr_mult': 0.001, 'batch_size': 2, 'epochs': 4, 'k_folds': 1, 'patience': 16, 'optimizer': 'AdamW', 'sgd_momentum': 0.9}
Epoch: 1
Loss on hold-out set: 2.397269105011562
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.20676100254058838
Epoch: 2
Loss on hold-out set: 2.3967335494059436
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.2138364315032959
Epoch: 3
Loss on hold-out set: 2.3959907788150714
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.20283016562461853
Epoch: 4
Loss on hold-out set: 2.3949102253284096
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.20283019542694092
Returned to Spot: Validation loss: 2.3949102253284096
----------------------------------------------
spotPython tuning: 2.3856273349725976 [##########] 100.00% Done...
<spotPython.spot.spot.Spot at 0x2d7787220>
The textual output shown in the console (or code cell) can be visualized with Tensorboard as described in Section 14.13.
After the hyperparameter tuning run is finished, the results can be analyzed as described in Section 14.14.
=False,
spot_tuner.plot_progress(log_y="./figures/" + experiment_name+"_progress.png") filename
from spotPython.utils.eda import gen_design_table
print(gen_design_table(fun_control=fun_control, spot=spot_tuner))
| name | type | default | lower | upper | tuned | transform | importance | stars |
|--------------|--------|-----------|---------|---------|---------------------|-----------------------|--------------|---------|
| _L0 | int | 64 | 6112.0 | 6112.0 | 6112.0 | None | 0.00 | |
| l1 | int | 8 | 6.0 | 13.0 | 13.0 | transform_power_2_int | 42.46 | * |
| dropout_prob | float | 0.01 | 0.0 | 0.9 | 0.16050204287317724 | None | 76.62 | ** |
| lr_mult | float | 1.0 | 0.001 | 0.001 | 0.001 | None | 0.00 | |
| batch_size | int | 4 | 1.0 | 4.0 | 1.0 | transform_power_2_int | 100.00 | *** |
| epochs | int | 4 | 2.0 | 2.0 | 2.0 | transform_power_2_int | 0.00 | |
| k_folds | int | 1 | 1.0 | 1.0 | 1.0 | None | 0.00 | |
| patience | int | 2 | 2.0 | 6.0 | 5.0 | transform_power_2_int | 0.38 | . |
| optimizer | factor | SGD | 0.0 | 3.0 | 3.0 | None | 0.58 | . |
| sgd_momentum | float | 0.0 | 0.9 | 0.9 | 0.9 | None | 0.00 | |
=0.025,
spot_tuner.plot_importance(threshold="./figures/" + experiment_name+"_importance.png") filename
from spotPython.hyperparameters.values import get_one_core_model_from_X
= spot_tuner.to_all_dim(spot_tuner.min_X.reshape(1,-1))
X = get_one_core_model_from_X(X, fun_control)
model_spot model_spot
Net_vbdp(
(fc1): Linear(in_features=6112, out_features=8192, bias=True)
(fc2): Linear(in_features=8192, out_features=4096, bias=True)
(fc3): Linear(in_features=4096, out_features=2048, bias=True)
(fc4): Linear(in_features=2048, out_features=1024, bias=True)
(fc5): Linear(in_features=1024, out_features=11, bias=True)
(relu): ReLU()
(softmax): Softmax(dim=1)
(dropout1): Dropout(p=0.16050204287317724, inplace=False)
(dropout2): Dropout(p=0.08025102143658862, inplace=False)
)
from spotPython.torch.traintest import (
train_tuned,
test_tuned,
)=model_spot, train_dataset=train,
train_tuned(net=fun_control["loss_function"],
loss_function=fun_control["metric_torch"],
metric=True,
shuffle= fun_control["device"],
device =None,
path=fun_control["task"],) task
Epoch: 1
Loss on hold-out set: 2.396878476412791
Accuracy on hold-out set: 0.14622641509433962
MAPK value on hold-out data: 0.3152514398097992
Epoch: 2
Loss on hold-out set: 2.3955852153166286
Accuracy on hold-out set: 0.11320754716981132
MAPK value on hold-out data: 0.30738988518714905
Epoch: 3
Loss on hold-out set: 2.393184853049944
Accuracy on hold-out set: 0.1179245283018868
MAPK value on hold-out data: 0.30031442642211914
Epoch: 4
Loss on hold-out set: 2.3897103768474652
Accuracy on hold-out set: 0.12264150943396226
MAPK value on hold-out data: 0.29481127858161926
Returned to Spot: Validation loss: 2.3897103768474652
----------------------------------------------
If path
is set to a filename, e.g., path = "model_spot_trained.pt"
, the weights of the trained model will be loaded from this file.
=model_spot, test_dataset=test,
test_tuned(net=False,
shuffle=fun_control["loss_function"],
loss_function=fun_control["metric_torch"],
metric= fun_control["device"],
device =fun_control["task"],) task
Loss on hold-out set: 2.3832428535718595
Accuracy on hold-out set: 0.1694915254237288
MAPK value on hold-out data: 0.33707863092422485
Final evaluation: Validation loss: 2.3832428535718595
Final evaluation: Validation metric: 0.33707863092422485
----------------------------------------------
(2.3832428535718595, nan, tensor(0.3371))
from spotPython.torch.traintest import evaluate_cv
# modify k-kolds:
setattr(model_spot, "k_folds", 10)
= evaluate_cv(net=model_spot,
df_eval, df_preds, df_metrics =fun_control["data"],
dataset=fun_control["loss_function"],
loss_function=fun_control["metric_torch"],
metric=fun_control["task"],
task=fun_control["writer"],
writer="model_spot_cv",
writerId= fun_control["device"]) device
Fold: 1
Epoch: 1
Loss on hold-out set: 2.3955075873268976
Accuracy on hold-out set: 0.11267605633802817
MAPK value on hold-out data: 0.1874999701976776
Epoch: 2
Loss on hold-out set: 2.3873102598720126
Accuracy on hold-out set: 0.15492957746478872
MAPK value on hold-out data: 0.2685185372829437
Epoch: 3
Loss on hold-out set: 2.362060825030009
Accuracy on hold-out set: 0.28169014084507044
MAPK value on hold-out data: 0.3680555522441864
Epoch: 4
Loss on hold-out set: 2.303971552186542
Accuracy on hold-out set: 0.29577464788732394
MAPK value on hold-out data: 0.409722238779068
Fold: 2
Epoch: 1
Loss on hold-out set: 2.395475685596466
Accuracy on hold-out set: 0.15492957746478872
MAPK value on hold-out data: 0.27314814925193787
Epoch: 2
Loss on hold-out set: 2.39027167028851
Accuracy on hold-out set: 0.11267605633802817
MAPK value on hold-out data: 0.23842589557170868
Epoch: 3
Loss on hold-out set: 2.3813089198536344
Accuracy on hold-out set: 0.19718309859154928
MAPK value on hold-out data: 0.30324074625968933
Epoch: 4
Loss on hold-out set: 2.3633686039182873
Accuracy on hold-out set: 0.2112676056338028
MAPK value on hold-out data: 0.3379629850387573
Fold: 3
Epoch: 1
Loss on hold-out set: 2.3942687975035772
Accuracy on hold-out set: 0.16901408450704225
MAPK value on hold-out data: 0.33796295523643494
Epoch: 2
Loss on hold-out set: 2.3863540358013577
Accuracy on hold-out set: 0.16901408450704225
MAPK value on hold-out data: 0.34259259700775146
Epoch: 3
Loss on hold-out set: 2.3707502815458508
Accuracy on hold-out set: 0.2535211267605634
MAPK value on hold-out data: 0.39814817905426025
Epoch: 4
Loss on hold-out set: 2.3529324332873025
Accuracy on hold-out set: 0.2535211267605634
MAPK value on hold-out data: 0.3865741193294525
Fold: 4
Epoch: 1
Loss on hold-out set: 2.3955457078086004
Accuracy on hold-out set: 0.1267605633802817
MAPK value on hold-out data: 0.2523147761821747
Epoch: 2
Loss on hold-out set: 2.3909303545951843
Accuracy on hold-out set: 0.1267605633802817
MAPK value on hold-out data: 0.2222222089767456
Epoch: 3
Loss on hold-out set: 2.382236295276218
Accuracy on hold-out set: 0.15492957746478872
MAPK value on hold-out data: 0.24074071645736694
Epoch: 4
Loss on hold-out set: 2.3735356993145413
Accuracy on hold-out set: 0.18309859154929578
MAPK value on hold-out data: 0.28935185074806213
Fold: 5
Epoch: 1
Loss on hold-out set: 2.3965154687563577
Accuracy on hold-out set: 0.14084507042253522
MAPK value on hold-out data: 0.21064813435077667
Epoch: 2
Loss on hold-out set: 2.3940890232721963
Accuracy on hold-out set: 0.1267605633802817
MAPK value on hold-out data: 0.17592591047286987
Epoch: 3
Loss on hold-out set: 2.386454588837094
Accuracy on hold-out set: 0.19718309859154928
MAPK value on hold-out data: 0.2638888657093048
Epoch: 4
Loss on hold-out set: 2.3852467272016735
Accuracy on hold-out set: 0.1267605633802817
MAPK value on hold-out data: 0.2361111044883728
Fold: 6
Epoch: 1
Loss on hold-out set: 2.396067632569207
Accuracy on hold-out set: 0.09859154929577464
MAPK value on hold-out data: 0.2083333134651184
Epoch: 2
Loss on hold-out set: 2.391849464840359
Accuracy on hold-out set: 0.09859154929577464
MAPK value on hold-out data: 0.23148144781589508
Epoch: 3
Loss on hold-out set: 2.3869924081696405
Accuracy on hold-out set: 0.1267605633802817
MAPK value on hold-out data: 0.2847222089767456
Epoch: 4
Loss on hold-out set: 2.371515002515581
Accuracy on hold-out set: 0.19718309859154928
MAPK value on hold-out data: 0.3333333134651184
Fold: 7
Epoch: 1
Loss on hold-out set: 2.395629253652361
Accuracy on hold-out set: 0.11267605633802817
MAPK value on hold-out data: 0.24537035822868347
Epoch: 2
Loss on hold-out set: 2.3895583748817444
Accuracy on hold-out set: 0.15492957746478872
MAPK value on hold-out data: 0.2430555522441864
Epoch: 3
Loss on hold-out set: 2.3755536013179355
Accuracy on hold-out set: 0.23943661971830985
MAPK value on hold-out data: 0.31712964177131653
Epoch: 4
Loss on hold-out set: 2.358691652615865
Accuracy on hold-out set: 0.23943661971830985
MAPK value on hold-out data: 0.3240740895271301
Fold: 8
Epoch: 1
Loss on hold-out set: 2.3963683673313687
Accuracy on hold-out set: 0.07142857142857142
MAPK value on hold-out data: 0.18095238506793976
Epoch: 2
Loss on hold-out set: 2.3931380135672433
Accuracy on hold-out set: 0.07142857142857142
MAPK value on hold-out data: 0.18333332240581512
Epoch: 3
Loss on hold-out set: 2.386047567640032
Accuracy on hold-out set: 0.1
MAPK value on hold-out data: 0.22857141494750977
Epoch: 4
Loss on hold-out set: 2.3698794841766357
Accuracy on hold-out set: 0.2571428571428571
MAPK value on hold-out data: 0.3619047999382019
Fold: 9
Epoch: 1
Loss on hold-out set: 2.395477546964373
Accuracy on hold-out set: 0.12857142857142856
MAPK value on hold-out data: 0.20476190745830536
Epoch: 2
Loss on hold-out set: 2.3903437682560513
Accuracy on hold-out set: 0.12857142857142856
MAPK value on hold-out data: 0.20952381193637848
Epoch: 3
Loss on hold-out set: 2.3808996064322336
Accuracy on hold-out set: 0.18571428571428572
MAPK value on hold-out data: 0.2571428716182709
Epoch: 4
Loss on hold-out set: 2.3610705511910575
Accuracy on hold-out set: 0.22857142857142856
MAPK value on hold-out data: 0.33571428060531616
Fold: 10
Epoch: 1
Loss on hold-out set: 2.3958696024758477
Accuracy on hold-out set: 0.15714285714285714
MAPK value on hold-out data: 0.23571428656578064
Epoch: 2
Loss on hold-out set: 2.390469121932983
Accuracy on hold-out set: 0.2
MAPK value on hold-out data: 0.2904762327671051
Epoch: 3
Loss on hold-out set: 2.3773350511278424
Accuracy on hold-out set: 0.21428571428571427
MAPK value on hold-out data: 0.32380950450897217
Epoch: 4
Loss on hold-out set: 2.3638267857687816
Accuracy on hold-out set: 0.2
MAPK value on hold-out data: 0.3333333432674408
= type(fun_control["metric_torch"]).__name__
metric_name print(f"loss: {df_eval}, Cross-validated {metric_name}: {df_metrics}")
loss: 2.3604038492176267, Cross-validated MAPK: 0.33480820059776306
= "./figures/" + experiment_name
filename =filename) spot_tuner.plot_important_hyperparameter_contour(filename
l1: 42.45954046546032
dropout_prob: 76.62173243063258
batch_size: 99.99999999999999
patience: 0.3813373827124728
optimizer: 0.5848307013773063
spot_tuner.parallel_plot()
Parallel coordinates plots
# close tensorbaoard writer
if fun_control["writer"] is not None:
"writer"].close() fun_control[
= False
PLOT_ALL if PLOT_ALL:
= spot_tuner.k
n for i in range(n-1):
for j in range(i+1, n):
=i, j=j, min_z=min_z, max_z = max_z) spot_tuner.plot_contour(i