2. Perturbation Prediction with CellDISECT

This tutorial demonstrates how to use CellDISECT for perturbation prediction on real single-cell data. We use the Norman combinatorial perturbation dataset preprocessed by GEARS and GenePT gene embeddings.

CellDISECT treats perturbations as a categorical covariate with predefined external embeddings (e.g. GenePT, ESM, scGPT) instead of learned embeddings. For combinatorial perturbations like GeneA+GeneB, the combined embedding is the sum of the atomic component embeddings. This enables:

1. Seen perturbation prediction — predicting expression under a perturbation that was part of the training set (single or combinatorial).

2. Unseen perturbation prediction — predicting expression under a novel perturbation not seen during training, using its predefined embedding.

3. Combinatorial perturbation prediction — predicting expression under simultaneous perturbations (e.g. GeneA+GeneB).

We hold out a random set of perturbations for evaluation, train the model on the remaining perturbations, and then evaluate on both unseen (held-out) and seen (training) perturbations.

2.1. 0. Setup & Data Download

import os
import subprocess
import zipfile

DATA_DIR = "data"
os.makedirs(DATA_DIR, exist_ok=True)

# Define paths
zip_path = os.path.join(DATA_DIR, "norman.zip")
extract_path = os.path.join(DATA_DIR, "norman")
h5ad_path = os.path.join(extract_path, "perturb_processed.h5ad")

if not os.path.exists(h5ad_path):
    # 1. Download the zip file
    print("Downloading Norman dataset (zip)...")
    subprocess.run(
        ["wget", "-q", "-O", zip_path,
         "https://dataverse.harvard.edu/api/access/datafile/6154020"],
        check=True,
    )

    # 2. Extract the zip file
    print(f"Extracting to {extract_path}...")
    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
        zip_ref.extractall(DATA_DIR)

    # 3. Clean up the zip file to save space (optional)
    os.remove(zip_path)
    print("Extraction complete. Zip file removed.")
else:
    print(f"Dataset already exists at {h5ad_path}")

# Quick verification
if os.path.exists(h5ad_path):
    print(f"Success! File ready at: {h5ad_path}")

Dataset already exists at data/norman/perturb_processed.h5ad
Success! File ready at: data/norman/perturb_processed.h5ad

genept_zip = os.path.join(DATA_DIR, "GenePT_emebdding_v2.zip")
genept_pickle = os.path.join(DATA_DIR, "GenePT_gene_embedding_ada_text.pickle")

if not os.path.exists(genept_pickle):
    if not os.path.exists(genept_zip):
        print("Downloading GenePT embeddings...")
        subprocess.run(
            ["wget", "-q", "-O", genept_zip,
             "https://zenodo.org/records/10833191/files/GenePT_emebdding_v2.zip?download=1"],
            check=True,
        )
    print("Extracting GenePT embeddings...")
    subprocess.run(
        ["unzip", "-o", "-j", genept_zip,
         "GenePT_gene_embedding_ada_text.pickle", "-d", DATA_DIR],
        check=True,
    )
    print("Done.")
else:
    print(f"GenePT embeddings already exist at {genept_pickle}")

GenePT embeddings already exist at data/GenePT_gene_embedding_ada_text.pickle

%load_ext autoreload
%autoreload 2
%matplotlib inline

import pickle
import numpy as np
import pandas as pd
import scanpy as sc
import scvi
import torch
import matplotlib.pyplot as plt
from scipy.stats import pearsonr

torch.set_float32_matmul_precision('medium')
scvi.settings.seed = 42

import warnings
warnings.filterwarnings('ignore')

from celldisect import CellDISECT, perturbation_metrics

Global seed set to 0
Global seed set to 42

2.2. 1. Data Preparation

adata = sc.read_h5ad(h5ad_path)
print(f"Loaded: {adata.n_obs} cells x {adata.n_vars} genes")
print(f"Obs columns: {list(adata.obs.columns)}")
adata

Loaded: 91205 cells x 5045 genes
Obs columns: ['condition', 'cell_type', 'dose_val', 'control', 'condition_name']

AnnData object with n_obs × n_vars = 91205 × 5045
    obs: 'condition', 'cell_type', 'dose_val', 'control', 'condition_name'
    var: 'gene_name'
    uns: 'non_dropout_gene_idx', 'non_zeros_gene_idx', 'rank_genes_groups_cov_all', 'top_non_dropout_de_20', 'top_non_zero_de_20'
    layers: 'counts'

2.2.1. 1.1 Identify perturbation and control columns

The Norman dataset uses condition for perturbation labels. Single-gene perturbations are encoded as ctrl+GENE or GENE+ctrl, and true combinatorial perturbations as GENEA+GENEB. The only label without + is ctrl.

perturbation_key = 'perturbation'
control_label = 'ctrl'

if 'condition' in adata.obs.columns and perturbation_key not in adata.obs.columns:
    adata.obs[perturbation_key] = adata.obs['condition'].copy()

adata.X = adata.layers['counts'].copy()

# Remove empty cells
sc.pp.filter_cells(adata, min_counts=1)

print(f"Perturbation column: '{perturbation_key}'")
print(f"Unique perturbations: {adata.obs[perturbation_key].nunique()}")
print(f"Control cells: {(adata.obs[perturbation_key] == control_label).sum()}")
adata.obs[perturbation_key].value_counts().head(10)

Perturbation column: 'perturbation'
Unique perturbations: 284
Control cells: 7353

perturbation
ctrl             7353
CEBPE+RUNX1T1    1030
KLF1+ctrl         997
TBX3+TBX2         969
SLC4A1+ctrl       853
ETS2+CNN1         785
DUSP9+ETS2        698
UBASH3B+OSR2      677
DUSP9+ctrl        662
ctrl+ETS2         656
Name: count, dtype: int64

2.2.2. 1.2 Normalize perturbation labels

Single-gene perturbations in the Norman dataset appear as ctrl+GENE or GENE+ctrl. We strip the ctrl component so that single-gene perturbations become just GENE and true combinatorial perturbations remain GENEA+GENEB. This ensures CellDISECT only looks up real gene embeddings.

DELIMITER = '+'

def normalize_pert_label(label, ctrl='ctrl', delimiter='+'):
    """Strip the ctrl component from perturbation labels.

    'ctrl+GENE' / 'GENE+ctrl' -> 'GENE'
    'GENEA+GENEB' -> 'GENEA+GENEB' (unchanged)
    'ctrl' -> 'ctrl' (unchanged)
    """
    if label == ctrl:
        return label
    parts = [p.strip() for p in label.split(delimiter)]
    gene_parts = [p for p in parts if p != ctrl]
    return delimiter.join(gene_parts)

# Show before/after for a few examples
raw_labels = adata.obs[perturbation_key].unique().tolist()
examples = [l for l in raw_labels if l != control_label][:6]
for ex in examples:
    print(f"  '{ex}' -> '{normalize_pert_label(ex)}'")

# Apply normalization
adata.obs[perturbation_key] = adata.obs[perturbation_key].map(
    lambda x: normalize_pert_label(x, ctrl=control_label, delimiter=DELIMITER)
)

print(f"\nAfter normalization:")
print(f"  Unique perturbations: {adata.obs[perturbation_key].nunique()}")
adata.obs[perturbation_key].value_counts().head(10)

  'TSC22D1+ctrl' -> 'TSC22D1'
  'KLF1+MAP2K6' -> 'KLF1+MAP2K6'
  'CEBPE+RUNX1T1' -> 'CEBPE+RUNX1T1'
  'MAML2+ctrl' -> 'MAML2'
  'ctrl+CEBPE' -> 'CEBPE'
  'CBL+PTPN9' -> 'CBL+PTPN9'

After normalization:
  Unique perturbations: 237

perturbation
ctrl             7353
KLF1             1641
BAK1             1171
CEBPE            1039
ETS2             1031
CEBPE+RUNX1T1    1030
UBASH3B           983
TBX3+TBX2         969
OSR2              858
SLC4A1            853
Name: count, dtype: int64

2.2.3. 1.3 Inspect single vs combinatorial perturbations

all_perts = [p for p in adata.obs[perturbation_key].unique() if p != control_label]
single_perts = [p for p in all_perts if DELIMITER not in p]
combo_perts = [p for p in all_perts if DELIMITER in p]

# Collect all atomic gene names
all_atomic_genes = set()
for p in all_perts:
    all_atomic_genes.update(p.split(DELIMITER))

print(f"Single-gene perturbations: {len(single_perts)}")
print(f"Combinatorial perturbations: {len(combo_perts)}")
print(f"Unique atomic genes across all perturbations: {len(all_atomic_genes)}")
print(f"\nExample singles: {single_perts[:5]}")
print(f"Example combos:  {combo_perts[:5]}")

Single-gene perturbations: 105
Combinatorial perturbations: 131
Unique atomic genes across all perturbations: 105

Example singles: ['TSC22D1', 'MAML2', 'CEBPE', 'DUSP9', 'ELMSAN1']
Example combos:  ['KLF1+MAP2K6', 'CEBPE+RUNX1T1', 'CBL+PTPN9', 'TGFBR2+ETS2', 'SGK1+TBX3']

2.2.4. 1.4 Load GenePT gene embeddings

with open(genept_pickle, 'rb') as f:
    gene_embeddings_raw = pickle.load(f)

gene_embeddings = {
    k: np.array(v, dtype=np.float32) for k, v in gene_embeddings_raw.items()
}

example_gene = list(gene_embeddings.keys())[0]
print(f"GenePT embeddings: {len(gene_embeddings)} genes")
print(f"Embedding dim: {gene_embeddings[example_gene].shape[0]}")
print(f"Example: '{example_gene}' -> shape {gene_embeddings[example_gene].shape}")

GenePT embeddings: 93800 genes
Embedding dim: 1536
Example: 'A1BG' -> shape (1536,)

2.2.5. 1.5 Filter to perturbations with available embeddings

For combinatorial perturbations GeneA+GeneB, both atomic components must have a GenePT embedding. CellDISECT automatically computes the combined embedding by summing.

def has_all_embeddings(pert, emb_dict, delimiter='+'):
    """Check whether all atomic components of a perturbation have embeddings."""
    return all(g in emb_dict for g in pert.split(delimiter) if g != control_label)

perts_with_emb = [p for p in all_perts if has_all_embeddings(p, gene_embeddings, DELIMITER)]
perts_without_emb = [p for p in all_perts if not has_all_embeddings(p, gene_embeddings, DELIMITER)]

print(f"Perturbations with all embeddings: {len(perts_with_emb)}")
print(f"Perturbations missing >=1 embedding (removed): {len(perts_without_emb)}")
if perts_without_emb:
    print(f"  Examples: {perts_without_emb[:5]}")

keep_mask = (
    (adata.obs[perturbation_key] == control_label) |
    (adata.obs[perturbation_key].isin(perts_with_emb))
)
adata = adata[keep_mask].copy()

# Recount
remaining_perts = [p for p in adata.obs[perturbation_key].unique() if p != control_label]
remaining_single = [p for p in remaining_perts if DELIMITER not in p]
remaining_combo = [p for p in remaining_perts if DELIMITER in p]
print(f"\nFiltered: {adata.n_obs} cells")
print(f"  Single-gene perturbations: {len(remaining_single)}")
print(f"  Combinatorial perturbations: {len(remaining_combo)}")
print(f"  Total (+ ctrl): {adata.obs[perturbation_key].nunique()}")

Perturbations with all embeddings: 232
Perturbations missing >=1 embedding (removed): 4
  Examples: ['RHOXF2BB', 'KIAA1804', 'RHOXF2BB+ZBTB25', 'RHOXF2BB+SET']

Filtered: 90231 cells
  Single-gene perturbations: 103
  Combinatorial perturbations: 129
  Total (+ ctrl): 233

2.2.6. 1.6 Train / test split — hold out random perturbations

We randomly select a set of perturbations as unseen (test). We hold out both single-gene and combinatorial perturbations to evaluate both scenarios.

np.random.seed(42)

N_HOLDOUT_SINGLE = 5
N_HOLDOUT_COMBO = 5

holdout_single = list(np.random.choice(
    remaining_single, size=min(N_HOLDOUT_SINGLE, len(remaining_single)), replace=False
))
holdout_combo = list(np.random.choice(
    remaining_combo, size=min(N_HOLDOUT_COMBO, len(remaining_combo)), replace=False
))
holdout_perts = holdout_single + holdout_combo

train_perts = [p for p in remaining_perts if p not in holdout_perts]
train_single = [p for p in train_perts if DELIMITER not in p]
train_combo = [p for p in train_perts if DELIMITER in p]

print(f"Held-out single-gene perturbations ({len(holdout_single)}): {holdout_single}")
print(f"Held-out combinatorial perturbations ({len(holdout_combo)}): {holdout_combo}")
print(f"\nTraining perturbations: {len(train_perts)} ({len(train_single)} single + {len(train_combo)} combo)")

Held-out single-gene perturbations (5): ['FOXO4', 'FOXL2', 'ARRDC3', 'C19orf26', 'PTPN12']
Held-out combinatorial perturbations (5): ['MAP2K6+IKZF3', 'FEV+ISL2', 'FOXA3+FOXL2', 'LHX1+ELMSAN1', 'FOXA1+FOXL2']

Training perturbations: 222 (98 single + 124 combo)

train_mask = (
    (adata.obs[perturbation_key] == control_label) |
    (adata.obs[perturbation_key].isin(train_perts))
)
adata_train = adata[train_mask].copy()
adata_eval = adata.copy()

print(f"Training data: {adata_train.n_obs} cells, {adata_train.obs[perturbation_key].nunique()} perturbations (incl. ctrl)")
print(f"Evaluation data: {adata_eval.n_obs} cells")

Training data: 86623 cells, 223 perturbations (incl. ctrl)
Evaluation data: 90231 cells

2.2.7. 1.7 Store embeddings in AnnData

gene_embeddings['ctrl'] = np.zeros_like(gene_embeddings['MAP2K6'])

adata_train.uns['pert_embeddings'] = gene_embeddings
adata_eval.uns['pert_embeddings'] = gene_embeddings

2.3. 2. Model Setup and Training

cats = [perturbation_key]
cell_type_included = True

arch_dict = {'n_layers': 2,
 'n_hidden': 128,
 'n_latent_shared': 32,
 'n_latent_attribute': 32,
 'dropout_rate': 0.1,
 'weighted_classifier': False,
}
train_dict = {
 'max_epochs': 1000,
 'batch_size': 256,
 'recon_weight': 20,
 'cf_weight': 0.8,
 'beta': 0.003,
 'clf_weight': 0.05,
 'adv_clf_weight': 0.014,
 'adv_period': 5,
 'n_cf': 1,
 'early_stopping_patience': 6,
 'early_stopping': True,
 'save_best': True,
 'kappa_optimizer2': False,
 'n_epochs_pretrain_ae': 0,
}

plan_kwargs = {
 'lr': 0.003,
 'weight_decay': 0.00005,
 'ensemble_method_cf': True,
 'lr_patience': 5,
 'lr_factor': 0.5,
 'lr_scheduler_metric': 'loss_validation',
 'n_epochs_kl_warmup': 10,
}

CellDISECT.setup_anndata(
    adata_train,
    layer='counts',
    categorical_covariate_keys=cats,
    continuous_covariate_keys=[],
    perturbation_key=perturbation_key,
    perturbation_embedding_key='pert_embeddings',
    perturbation_combination_delimiter=DELIMITER,
)

An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.

model = CellDISECT(
    adata_train,
    **arch_dict
)
print(model)

CellDISECT Model with the following params:
n_hidden: 128, n_latent_shared: 32, n_latent_attribute: 32, n_layers: 2, dropout_rate: 0.1, gene_likelihood: zinb,
latent_distribution: normal
Training status: Not Trained
Model's adata is minified?: False

model.train(**train_dict, plan_kwargs=plan_kwargs, )

GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [MIG-GPU-c92e82f0-acdb-bfba-5c7c-90306242f281/13/0]

Epoch 2/1000:   0%|          | 1/1000 [00:11<3:14:02, 11.65s/it, v_num=1, loss_validation=6.11, x_0_validation=0.279, x_1_validation=0.29, rec_x_cf_validation=0.201, z_1_validation=28.5, ce_validation=5.12, acc_validation=0.087, f1_validation=0.087, adv_ce_validation=4.98, adv_acc_validation=0.0854, adv_f1_validation=0.0854, loss_train=7.74, x_0_train=0.363, x_1_train=0.366, rec_x_cf_train=0.24, z_1_train=21.3, ce_train=5.26, acc_train=0.0682, f1_train=0.0682, adv_ce_train=5.11, adv_acc_train=0.0784, adv_f1_train=0.0784]

Epoch 00001: loss_validation reached. Module best state updated.

Epoch 6/1000:   0%|          | 5/1000 [00:43<2:18:12,  8.33s/it, v_num=1, loss_validation=6.03, x_0_validation=0.278, x_1_validation=0.28, rec_x_cf_validation=0.198, z_1_validation=32.6, ce_validation=5.1, acc_validation=0.0858, f1_validation=0.0858, adv_ce_validation=4.81, adv_acc_validation=0.0941, adv_f1_validation=0.0941, loss_train=6.04, x_0_train=0.278, x_1_train=0.28, rec_x_cf_train=0.198, z_1_train=35.4, ce_train=5.11, acc_train=0.0869, f1_train=0.0869, adv_ce_train=4.84, adv_acc_train=0.0939, adv_f1_train=0.0939]

Epoch 00005: loss_validation reached. Module best state updated.

Epoch 7/1000:   1%|          | 6/1000 [00:56<2:40:14,  9.67s/it, v_num=1, loss_validation=5.6, x_0_validation=0.258, x_1_validation=0.259, rec_x_cf_validation=0.193, z_1_validation=11.8, ce_validation=5, acc_validation=0.0941, f1_validation=0.0941, adv_ce_validation=4.86, adv_acc_validation=0.0936, adv_f1_validation=0.0936, loss_train=5.72, x_0_train=0.266, x_1_train=0.267, rec_x_cf_train=0.195, z_1_train=16.4, ce_train=5.05, acc_train=0.0894, f1_train=0.0894, adv_ce_train=4.86, adv_acc_train=0.0928, adv_f1_train=0.0928]

Epoch 00006: loss_validation reached. Module best state updated.

Epoch 11/1000:   1%|          | 10/1000 [01:28<2:18:08,  8.37s/it, v_num=1, loss_validation=5.6, x_0_validation=0.258, x_1_validation=0.259, rec_x_cf_validation=0.193, z_1_validation=10.9, ce_validation=4.98, acc_validation=0.093, f1_validation=0.093, adv_ce_validation=4.82, adv_acc_validation=0.0939, adv_f1_validation=0.0939, loss_train=5.6, x_0_train=0.258, x_1_train=0.259, rec_x_cf_train=0.193, z_1_train=12.4, ce_train=4.99, acc_train=0.0932, f1_train=0.0932, adv_ce_train=4.83, adv_acc_train=0.0935, adv_f1_train=0.0935]

Epoch 00010: loss_validation reached. Module best state updated.

Epoch 12/1000:   1%|          | 11/1000 [01:40<2:37:42,  9.57s/it, v_num=1, loss_validation=5.46, x_0_validation=0.252, x_1_validation=0.253, rec_x_cf_validation=0.192, z_1_validation=5.81, ce_validation=4.91, acc_validation=0.0974, f1_validation=0.0974, adv_ce_validation=4.89, adv_acc_validation=0.0899, adv_f1_validation=0.0899, loss_train=5.46, x_0_train=0.254, x_1_train=0.255, rec_x_cf_train=0.192, z_1_train=8.55, ce_train=4.96, acc_train=0.0953, f1_train=0.0953, adv_ce_train=4.87, adv_acc_train=0.0921, adv_f1_train=0.0921]

Epoch 00011: loss_validation reached. Module best state updated.

Epoch 16/1000:   2%|▏         | 15/1000 [02:13<2:19:53,  8.52s/it, v_num=1, loss_validation=5.46, x_0_validation=0.252, x_1_validation=0.252, rec_x_cf_validation=0.192, z_1_validation=5.68, ce_validation=4.91, acc_validation=0.0986, f1_validation=0.0986, adv_ce_validation=4.86, adv_acc_validation=0.0911, adv_f1_validation=0.0911, loss_train=5.46, x_0_train=0.252, x_1_train=0.252, rec_x_cf_train=0.192, z_1_train=6.88, ce_train=4.91, acc_train=0.0979, f1_train=0.0979, adv_ce_train=4.87, adv_acc_train=0.092, adv_f1_train=0.092]

Epoch 00015: loss_validation reached. Module best state updated.

Epoch 17/1000:   2%|▏         | 16/1000 [02:25<2:38:24,  9.66s/it, v_num=1, loss_validation=5.38, x_0_validation=0.248, x_1_validation=0.249, rec_x_cf_validation=0.192, z_1_validation=5.09, ce_validation=4.8, acc_validation=0.101, f1_validation=0.101, adv_ce_validation=4.86, adv_acc_validation=0.0912, adv_f1_validation=0.0912, loss_train=5.35, x_0_train=0.25, x_1_train=0.251, rec_x_cf_train=0.192, z_1_train=6.3, ce_train=4.87, acc_train=0.1, f1_train=0.1, adv_ce_train=4.86, adv_acc_train=0.0916, adv_f1_train=0.0916]

Epoch 00016: loss_validation reached. Module best state updated.

Epoch 19/1000:   2%|▏         | 18/1000 [02:41<2:24:37,  8.84s/it, v_num=1, loss_validation=5.38, x_0_validation=0.248, x_1_validation=0.249, rec_x_cf_validation=0.192, z_1_validation=4.85, ce_validation=4.81, acc_validation=0.102, f1_validation=0.102, adv_ce_validation=4.84, adv_acc_validation=0.0917, adv_f1_validation=0.0917, loss_train=5.38, x_0_train=0.248, x_1_train=0.249, rec_x_cf_train=0.191, z_1_train=5.91, ce_train=4.82, acc_train=0.103, f1_train=0.103, adv_ce_train=4.86, adv_acc_train=0.0922, adv_f1_train=0.0922]

Epoch 00018: loss_validation reached. Module best state updated.

Epoch 21/1000:   2%|▏         | 20/1000 [02:58<2:17:43,  8.43s/it, v_num=1, loss_validation=5.38, x_0_validation=0.248, x_1_validation=0.249, rec_x_cf_validation=0.192, z_1_validation=4.84, ce_validation=4.81, acc_validation=0.102, f1_validation=0.102, adv_ce_validation=4.84, adv_acc_validation=0.0922, adv_f1_validation=0.0922, loss_train=5.38, x_0_train=0.248, x_1_train=0.249, rec_x_cf_train=0.192, z_1_train=5.91, ce_train=4.82, acc_train=0.103, f1_train=0.103, adv_ce_train=4.85, adv_acc_train=0.0929, adv_f1_train=0.0929]

Epoch 00020: loss_validation reached. Module best state updated.

Epoch 22/1000:   2%|▏         | 21/1000 [03:10<2:36:37,  9.60s/it, v_num=1, loss_validation=5.33, x_0_validation=0.246, x_1_validation=0.246, rec_x_cf_validation=0.192, z_1_validation=4.87, ce_validation=4.71, acc_validation=0.112, f1_validation=0.112, adv_ce_validation=4.85, adv_acc_validation=0.0913, adv_f1_validation=0.0913, loss_train=5.29, x_0_train=0.247, x_1_train=0.248, rec_x_cf_train=0.192, z_1_train=5.79, ce_train=4.77, acc_train=0.107, f1_train=0.107, adv_ce_train=4.85, adv_acc_train=0.0927, adv_f1_train=0.0927]

Epoch 00021: loss_validation reached. Module best state updated.

Epoch 23/1000:   2%|▏         | 22/1000 [03:18<2:29:14,  9.16s/it, v_num=1, loss_validation=5.32, x_0_validation=0.246, x_1_validation=0.246, rec_x_cf_validation=0.192, z_1_validation=4.65, ce_validation=4.71, acc_validation=0.114, f1_validation=0.114, adv_ce_validation=4.84, adv_acc_validation=0.0917, adv_f1_validation=0.0917, loss_train=5.33, x_0_train=0.246, x_1_train=0.246, rec_x_cf_train=0.192, z_1_train=5.66, ce_train=4.71, acc_train=0.112, f1_train=0.112, adv_ce_train=4.85, adv_acc_train=0.0926, adv_f1_train=0.0926]

Epoch 00022: loss_validation reached. Module best state updated.

Epoch 26/1000:   2%|▎         | 25/1000 [03:42<2:16:26,  8.40s/it, v_num=1, loss_validation=5.32, x_0_validation=0.246, x_1_validation=0.246, rec_x_cf_validation=0.192, z_1_validation=4.63, ce_validation=4.71, acc_validation=0.114, f1_validation=0.114, adv_ce_validation=4.84, adv_acc_validation=0.0914, adv_f1_validation=0.0914, loss_train=5.33, x_0_train=0.246, x_1_train=0.246, rec_x_cf_train=0.192, z_1_train=5.66, ce_train=4.71, acc_train=0.113, f1_train=0.113, adv_ce_train=4.84, adv_acc_train=0.0932, adv_f1_train=0.0932]

Epoch 00025: loss_validation reached. Module best state updated.

Epoch 27/1000:   3%|▎         | 26/1000 [03:54<2:35:20,  9.57s/it, v_num=1, loss_validation=5.28, x_0_validation=0.244, x_1_validation=0.244, rec_x_cf_validation=0.192, z_1_validation=4.46, ce_validation=4.6, acc_validation=0.123, f1_validation=0.123, adv_ce_validation=4.83, adv_acc_validation=0.0933, adv_f1_validation=0.0933, loss_train=5.24, x_0_train=0.245, x_1_train=0.245, rec_x_cf_train=0.191, z_1_train=5.63, ce_train=4.66, acc_train=0.118, f1_train=0.118, adv_ce_train=4.84, adv_acc_train=0.0929, adv_f1_train=0.0929]

Epoch 00026: loss_validation reached. Module best state updated.

Epoch 28/1000:   3%|▎         | 27/1000 [04:02<2:28:14,  9.14s/it, v_num=1, loss_validation=5.28, x_0_validation=0.244, x_1_validation=0.244, rec_x_cf_validation=0.192, z_1_validation=4.63, ce_validation=4.59, acc_validation=0.123, f1_validation=0.123, adv_ce_validation=4.82, adv_acc_validation=0.092, adv_f1_validation=0.092, loss_train=5.28, x_0_train=0.244, x_1_train=0.244, rec_x_cf_train=0.191, z_1_train=5.59, ce_train=4.6, acc_train=0.122, f1_train=0.122, adv_ce_train=4.83, adv_acc_train=0.0926, adv_f1_train=0.0926]

Epoch 00027: loss_validation reached. Module best state updated.

Epoch 31/1000:   3%|▎         | 30/1000 [04:27<2:16:06,  8.42s/it, v_num=1, loss_validation=5.28, x_0_validation=0.244, x_1_validation=0.244, rec_x_cf_validation=0.192, z_1_validation=4.66, ce_validation=4.58, acc_validation=0.124, f1_validation=0.124, adv_ce_validation=4.82, adv_acc_validation=0.0931, adv_f1_validation=0.0931, loss_train=5.28, x_0_train=0.244, x_1_train=0.244, rec_x_cf_train=0.191, z_1_train=5.59, ce_train=4.59, acc_train=0.122, f1_train=0.122, adv_ce_train=4.82, adv_acc_train=0.094, adv_f1_train=0.094]

Epoch 00030: loss_validation reached. Module best state updated.

Epoch 32/1000:   3%|▎         | 31/1000 [04:39<2:35:08,  9.61s/it, v_num=1, loss_validation=5.25, x_0_validation=0.242, x_1_validation=0.243, rec_x_cf_validation=0.192, z_1_validation=4.69, ce_validation=4.5, acc_validation=0.134, f1_validation=0.134, adv_ce_validation=4.83, adv_acc_validation=0.0926, adv_f1_validation=0.0926, loss_train=5.2, x_0_train=0.243, x_1_train=0.244, rec_x_cf_train=0.191, z_1_train=5.55, ce_train=4.52, acc_train=0.127, f1_train=0.127, adv_ce_train=4.83, adv_acc_train=0.0931, adv_f1_train=0.0931]

Epoch 00031: loss_validation reached. Module best state updated.

Epoch 34/1000:   3%|▎         | 33/1000 [04:55<2:21:59,  8.81s/it, v_num=1, loss_validation=5.24, x_0_validation=0.242, x_1_validation=0.243, rec_x_cf_validation=0.192, z_1_validation=4.53, ce_validation=4.42, acc_validation=0.135, f1_validation=0.135, adv_ce_validation=4.82, adv_acc_validation=0.092, adv_f1_validation=0.092, loss_train=5.24, x_0_train=0.242, x_1_train=0.243, rec_x_cf_train=0.192, z_1_train=5.45, ce_train=4.43, acc_train=0.134, f1_train=0.134, adv_ce_train=4.82, adv_acc_train=0.0935, adv_f1_train=0.0935]

Epoch 00033: loss_validation reached. Module best state updated.

Epoch 36/1000:   4%|▎         | 35/1000 [05:11<2:15:13,  8.41s/it, v_num=1, loss_validation=5.24, x_0_validation=0.242, x_1_validation=0.243, rec_x_cf_validation=0.192, z_1_validation=4.54, ce_validation=4.42, acc_validation=0.134, f1_validation=0.134, adv_ce_validation=4.81, adv_acc_validation=0.0925, adv_f1_validation=0.0925, loss_train=5.24, x_0_train=0.242, x_1_train=0.243, rec_x_cf_train=0.192, z_1_train=5.45, ce_train=4.43, acc_train=0.133, f1_train=0.133, adv_ce_train=4.82, adv_acc_train=0.0933, adv_f1_train=0.0933]

Epoch 00035: loss_validation reached. Module best state updated.

Epoch 37/1000:   4%|▎         | 36/1000 [05:24<2:34:32,  9.62s/it, v_num=1, loss_validation=5.21, x_0_validation=0.241, x_1_validation=0.242, rec_x_cf_validation=0.19, z_1_validation=4.27, ce_validation=4.33, acc_validation=0.144, f1_validation=0.144, adv_ce_validation=4.81, adv_acc_validation=0.0937, adv_f1_validation=0.0937, loss_train=5.16, x_0_train=0.242, x_1_train=0.242, rec_x_cf_train=0.191, z_1_train=5.43, ce_train=4.36, acc_train=0.139, f1_train=0.139, adv_ce_train=4.82, adv_acc_train=0.0937, adv_f1_train=0.0937]

Epoch 00036: loss_validation reached. Module best state updated.

Epoch 38/1000:   4%|▎         | 37/1000 [05:32<2:27:04,  9.16s/it, v_num=1, loss_validation=5.21, x_0_validation=0.241, x_1_validation=0.241, rec_x_cf_validation=0.19, z_1_validation=4.48, ce_validation=4.28, acc_validation=0.146, f1_validation=0.146, adv_ce_validation=4.8, adv_acc_validation=0.0935, adv_f1_validation=0.0935, loss_train=5.21, x_0_train=0.241, x_1_train=0.242, rec_x_cf_train=0.19, z_1_train=5.41, ce_train=4.29, acc_train=0.144, f1_train=0.144, adv_ce_train=4.81, adv_acc_train=0.0939, adv_f1_train=0.0939]

Epoch 00037: loss_validation reached. Module best state updated.

Epoch 40/1000:   4%|▍         | 39/1000 [05:48<2:17:31,  8.59s/it, v_num=1, loss_validation=5.21, x_0_validation=0.241, x_1_validation=0.241, rec_x_cf_validation=0.19, z_1_validation=4.49, ce_validation=4.28, acc_validation=0.144, f1_validation=0.144, adv_ce_validation=4.8, adv_acc_validation=0.0935, adv_f1_validation=0.0935, loss_train=5.21, x_0_train=0.241, x_1_train=0.242, rec_x_cf_train=0.19, z_1_train=5.41, ce_train=4.29, acc_train=0.143, f1_train=0.143, adv_ce_train=4.8, adv_acc_train=0.0938, adv_f1_train=0.0938]

Epoch 00039: loss_validation reached. Module best state updated.

Epoch 41/1000:   4%|▍         | 40/1000 [05:56<2:14:37,  8.41s/it, v_num=1, loss_validation=5.21, x_0_validation=0.241, x_1_validation=0.241, rec_x_cf_validation=0.19, z_1_validation=4.48, ce_validation=4.27, acc_validation=0.144, f1_validation=0.144, adv_ce_validation=4.8, adv_acc_validation=0.0942, adv_f1_validation=0.0942, loss_train=5.21, x_0_train=0.241, x_1_train=0.242, rec_x_cf_train=0.19, z_1_train=5.41, ce_train=4.29, acc_train=0.144, f1_train=0.144, adv_ce_train=4.8, adv_acc_train=0.0941, adv_f1_train=0.0941]

Epoch 00040: loss_validation reached. Module best state updated.

Epoch 42/1000:   4%|▍         | 41/1000 [06:08<2:33:14,  9.59s/it, v_num=1, loss_validation=5.19, x_0_validation=0.24, x_1_validation=0.24, rec_x_cf_validation=0.192, z_1_validation=5.6, ce_validation=4.28, acc_validation=0.144, f1_validation=0.144, adv_ce_validation=4.8, adv_acc_validation=0.0936, adv_f1_validation=0.0936, loss_train=5.13, x_0_train=0.241, x_1_train=0.241, rec_x_cf_train=0.191, z_1_train=5.42, ce_train=4.24, acc_train=0.148, f1_train=0.148, adv_ce_train=4.81, adv_acc_train=0.0939, adv_f1_train=0.0939]

Epoch 00041: loss_validation reached. Module best state updated.

Epoch 44/1000:   4%|▍         | 43/1000 [06:24<2:20:30,  8.81s/it, v_num=1, loss_validation=5.17, x_0_validation=0.24, x_1_validation=0.24, rec_x_cf_validation=0.191, z_1_validation=4.51, ce_validation=4.18, acc_validation=0.154, f1_validation=0.154, adv_ce_validation=4.79, adv_acc_validation=0.0945, adv_f1_validation=0.0945, loss_train=5.18, x_0_train=0.24, x_1_train=0.24, rec_x_cf_train=0.191, z_1_train=5.43, ce_train=4.19, acc_train=0.153, f1_train=0.153, adv_ce_train=4.8, adv_acc_train=0.094, adv_f1_train=0.094]

Epoch 00043: loss_validation reached. Module best state updated.

Epoch 45/1000:   4%|▍         | 44/1000 [06:32<2:17:13,  8.61s/it, v_num=1, loss_validation=5.17, x_0_validation=0.24, x_1_validation=0.24, rec_x_cf_validation=0.191, z_1_validation=4.5, ce_validation=4.17, acc_validation=0.153, f1_validation=0.153, adv_ce_validation=4.79, adv_acc_validation=0.0948, adv_f1_validation=0.0948, loss_train=5.18, x_0_train=0.24, x_1_train=0.24, rec_x_cf_train=0.191, z_1_train=5.44, ce_train=4.19, acc_train=0.153, f1_train=0.153, adv_ce_train=4.79, adv_acc_train=0.0947, adv_f1_train=0.0947]

Epoch 00044: loss_validation reached. Module best state updated.

Epoch 46/1000:   4%|▍         | 45/1000 [06:40<2:14:19,  8.44s/it, v_num=1, loss_validation=5.17, x_0_validation=0.24, x_1_validation=0.24, rec_x_cf_validation=0.191, z_1_validation=4.5, ce_validation=4.17, acc_validation=0.155, f1_validation=0.155, adv_ce_validation=4.78, adv_acc_validation=0.0945, adv_f1_validation=0.0945, loss_train=5.18, x_0_train=0.24, x_1_train=0.24, rec_x_cf_train=0.191, z_1_train=5.43, ce_train=4.19, acc_train=0.153, f1_train=0.153, adv_ce_train=4.79, adv_acc_train=0.0946, adv_f1_train=0.0946]

Epoch 00045: loss_validation reached. Module best state updated.

Epoch 47/1000:   5%|▍         | 46/1000 [06:54<2:37:59,  9.94s/it, v_num=1, loss_validation=5.15, x_0_validation=0.239, x_1_validation=0.239, rec_x_cf_validation=0.191, z_1_validation=4.68, ce_validation=4.12, acc_validation=0.166, f1_validation=0.166, adv_ce_validation=4.78, adv_acc_validation=0.0941, adv_f1_validation=0.0941, loss_train=5.1, x_0_train=0.239, x_1_train=0.24, rec_x_cf_train=0.191, z_1_train=5.45, ce_train=4.14, acc_train=0.158, f1_train=0.158, adv_ce_train=4.79, adv_acc_train=0.0941, adv_f1_train=0.0941]

Epoch 00046: loss_validation reached. Module best state updated.

Epoch 51/1000:   5%|▌         | 50/1000 [07:26<2:14:31,  8.50s/it, v_num=1, loss_validation=5.15, x_0_validation=0.239, x_1_validation=0.239, rec_x_cf_validation=0.191, z_1_validation=4.52, ce_validation=4.08, acc_validation=0.166, f1_validation=0.166, adv_ce_validation=4.77, adv_acc_validation=0.0953, adv_f1_validation=0.0953, loss_train=5.15, x_0_train=0.239, x_1_train=0.239, rec_x_cf_train=0.191, z_1_train=5.42, ce_train=4.09, acc_train=0.165, f1_train=0.165, adv_ce_train=4.77, adv_acc_train=0.0953, adv_f1_train=0.0953]

Epoch 00050: loss_validation reached. Module best state updated.

Epoch 52/1000:   5%|▌         | 51/1000 [07:38<2:32:19,  9.63s/it, v_num=1, loss_validation=5.13, x_0_validation=0.238, x_1_validation=0.238, rec_x_cf_validation=0.19, z_1_validation=4.67, ce_validation=4.08, acc_validation=0.176, f1_validation=0.176, adv_ce_validation=4.75, adv_acc_validation=0.0967, adv_f1_validation=0.0967, loss_train=5.08, x_0_train=0.238, x_1_train=0.239, rec_x_cf_train=0.19, z_1_train=5.49, ce_train=4.05, acc_train=0.168, f1_train=0.168, adv_ce_train=4.76, adv_acc_train=0.0953, adv_f1_train=0.0953]

Epoch 00051: loss_validation reached. Module best state updated.

Epoch 54/1000:   5%|▌         | 53/1000 [07:55<2:19:26,  8.83s/it, v_num=1, loss_validation=5.12, x_0_validation=0.238, x_1_validation=0.238, rec_x_cf_validation=0.19, z_1_validation=4.6, ce_validation=4, acc_validation=0.175, f1_validation=0.175, adv_ce_validation=4.74, adv_acc_validation=0.0963, adv_f1_validation=0.0963, loss_train=5.13, x_0_train=0.238, x_1_train=0.238, rec_x_cf_train=0.19, z_1_train=5.5, ce_train=4.01, acc_train=0.175, f1_train=0.175, adv_ce_train=4.75, adv_acc_train=0.0957, adv_f1_train=0.0957]

Epoch 00053: loss_validation reached. Module best state updated.

Epoch 55/1000:   5%|▌         | 54/1000 [08:03<2:15:45,  8.61s/it, v_num=1, loss_validation=5.12, x_0_validation=0.238, x_1_validation=0.238, rec_x_cf_validation=0.19, z_1_validation=4.6, ce_validation=4, acc_validation=0.175, f1_validation=0.175, adv_ce_validation=4.75, adv_acc_validation=0.0959, adv_f1_validation=0.0959, loss_train=5.13, x_0_train=0.238, x_1_train=0.238, rec_x_cf_train=0.19, z_1_train=5.51, ce_train=4.01, acc_train=0.174, f1_train=0.174, adv_ce_train=4.75, adv_acc_train=0.096, adv_f1_train=0.096]

Epoch 00054: loss_validation reached. Module best state updated.

Epoch 56/1000:   6%|▌         | 55/1000 [08:11<2:12:50,  8.43s/it, v_num=1, loss_validation=5.12, x_0_validation=0.238, x_1_validation=0.238, rec_x_cf_validation=0.19, z_1_validation=4.61, ce_validation=4, acc_validation=0.177, f1_validation=0.177, adv_ce_validation=4.74, adv_acc_validation=0.0966, adv_f1_validation=0.0966, loss_train=5.13, x_0_train=0.238, x_1_train=0.238, rec_x_cf_train=0.19, z_1_train=5.51, ce_train=4.01, acc_train=0.174, f1_train=0.174, adv_ce_train=4.75, adv_acc_train=0.0962, adv_f1_train=0.0962]

Epoch 00055: loss_validation reached. Module best state updated.

Epoch 57/1000:   6%|▌         | 56/1000 [08:23<2:30:46,  9.58s/it, v_num=1, loss_validation=5.1, x_0_validation=0.237, x_1_validation=0.237, rec_x_cf_validation=0.19, z_1_validation=4.75, ce_validation=3.96, acc_validation=0.188, f1_validation=0.188, adv_ce_validation=4.73, adv_acc_validation=0.0969, adv_f1_validation=0.0969, loss_train=5.05, x_0_train=0.237, x_1_train=0.238, rec_x_cf_train=0.19, z_1_train=5.56, ce_train=3.97, acc_train=0.179, f1_train=0.179, adv_ce_train=4.74, adv_acc_train=0.0958, adv_f1_train=0.0958]

Epoch 00056: loss_validation reached. Module best state updated.

Epoch 58/1000:   6%|▌         | 57/1000 [08:31<2:24:04,  9.17s/it, v_num=1, loss_validation=5.1, x_0_validation=0.237, x_1_validation=0.237, rec_x_cf_validation=0.19, z_1_validation=4.67, ce_validation=3.92, acc_validation=0.186, f1_validation=0.186, adv_ce_validation=4.73, adv_acc_validation=0.096, adv_f1_validation=0.096, loss_train=5.11, x_0_train=0.237, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.57, ce_train=3.92, acc_train=0.186, f1_train=0.186, adv_ce_train=4.74, adv_acc_train=0.0963, adv_f1_train=0.0963]

Epoch 00057: loss_validation reached. Module best state updated.

Epoch 59/1000:   6%|▌         | 58/1000 [08:39<2:18:06,  8.80s/it, v_num=1, loss_validation=5.1, x_0_validation=0.237, x_1_validation=0.237, rec_x_cf_validation=0.19, z_1_validation=4.68, ce_validation=3.92, acc_validation=0.188, f1_validation=0.188, adv_ce_validation=4.72, adv_acc_validation=0.0972, adv_f1_validation=0.0972, loss_train=5.11, x_0_train=0.237, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.58, ce_train=3.92, acc_train=0.186, f1_train=0.186, adv_ce_train=4.73, adv_acc_train=0.0964, adv_f1_train=0.0964]

Epoch 00058: loss_validation reached. Module best state updated.

Epoch 60/1000:   6%|▌         | 59/1000 [08:47<2:15:05,  8.61s/it, v_num=1, loss_validation=5.1, x_0_validation=0.237, x_1_validation=0.237, rec_x_cf_validation=0.19, z_1_validation=4.68, ce_validation=3.92, acc_validation=0.188, f1_validation=0.188, adv_ce_validation=4.72, adv_acc_validation=0.0973, adv_f1_validation=0.0973, loss_train=5.11, x_0_train=0.237, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.58, ce_train=3.92, acc_train=0.185, f1_train=0.185, adv_ce_train=4.73, adv_acc_train=0.0967, adv_f1_train=0.0967]

Epoch 00059: loss_validation reached. Module best state updated.

Epoch 61/1000:   6%|▌         | 60/1000 [08:55<2:12:04,  8.43s/it, v_num=1, loss_validation=5.1, x_0_validation=0.237, x_1_validation=0.237, rec_x_cf_validation=0.19, z_1_validation=4.67, ce_validation=3.91, acc_validation=0.192, f1_validation=0.192, adv_ce_validation=4.72, adv_acc_validation=0.0969, adv_f1_validation=0.0969, loss_train=5.11, x_0_train=0.237, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.58, ce_train=3.92, acc_train=0.186, f1_train=0.186, adv_ce_train=4.73, adv_acc_train=0.0964, adv_f1_train=0.0964]

Epoch 00060: loss_validation reached. Module best state updated.

Epoch 62/1000:   6%|▌         | 61/1000 [09:08<2:30:57,  9.65s/it, v_num=1, loss_validation=5.08, x_0_validation=0.236, x_1_validation=0.236, rec_x_cf_validation=0.189, z_1_validation=4.92, ce_validation=3.87, acc_validation=0.204, f1_validation=0.204, adv_ce_validation=4.71, adv_acc_validation=0.0981, adv_f1_validation=0.0981, loss_train=5.03, x_0_train=0.236, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.64, ce_train=3.89, acc_train=0.191, f1_train=0.191, adv_ce_train=4.72, adv_acc_train=0.0968, adv_f1_train=0.0968]

Epoch 00061: loss_validation reached. Module best state updated.

Epoch 63/1000:   6%|▌         | 62/1000 [09:16<2:23:30,  9.18s/it, v_num=1, loss_validation=5.08, x_0_validation=0.236, x_1_validation=0.236, rec_x_cf_validation=0.19, z_1_validation=4.79, ce_validation=3.83, acc_validation=0.203, f1_validation=0.203, adv_ce_validation=4.7, adv_acc_validation=0.0977, adv_f1_validation=0.0977, loss_train=5.09, x_0_train=0.236, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.68, ce_train=3.83, acc_train=0.199, f1_train=0.199, adv_ce_train=4.72, adv_acc_train=0.0972, adv_f1_train=0.0972]

Epoch 00062: loss_validation reached. Module best state updated.

Epoch 66/1000:   6%|▋         | 65/1000 [09:40<2:11:28,  8.44s/it, v_num=1, loss_validation=5.08, x_0_validation=0.236, x_1_validation=0.236, rec_x_cf_validation=0.19, z_1_validation=4.77, ce_validation=3.83, acc_validation=0.2, f1_validation=0.2, adv_ce_validation=4.7, adv_acc_validation=0.0971, adv_f1_validation=0.0971, loss_train=5.09, x_0_train=0.236, x_1_train=0.237, rec_x_cf_train=0.19, z_1_train=5.68, ce_train=3.83, acc_train=0.198, f1_train=0.198, adv_ce_train=4.71, adv_acc_train=0.097, adv_f1_train=0.097]

Epoch 00065: loss_validation reached. Module best state updated.

Epoch 67/1000:   7%|▋         | 66/1000 [09:52<2:29:15,  9.59s/it, v_num=1, loss_validation=5.06, x_0_validation=0.235, x_1_validation=0.236, rec_x_cf_validation=0.19, z_1_validation=5.23, ce_validation=3.73, acc_validation=0.219, f1_validation=0.219, adv_ce_validation=4.69, adv_acc_validation=0.0988, adv_f1_validation=0.0988, loss_train=5.01, x_0_train=0.235, x_1_train=0.236, rec_x_cf_train=0.19, z_1_train=5.75, ce_train=3.8, acc_train=0.204, f1_train=0.204, adv_ce_train=4.7, adv_acc_train=0.0972, adv_f1_train=0.0972]

Epoch 00066: loss_validation reached. Module best state updated.

Epoch 68/1000:   7%|▋         | 67/1000 [10:00<2:22:52,  9.19s/it, v_num=1, loss_validation=5.06, x_0_validation=0.235, x_1_validation=0.236, rec_x_cf_validation=0.19, z_1_validation=4.85, ce_validation=3.74, acc_validation=0.213, f1_validation=0.213, adv_ce_validation=4.69, adv_acc_validation=0.0995, adv_f1_validation=0.0995, loss_train=5.06, x_0_train=0.235, x_1_train=0.236, rec_x_cf_train=0.19, z_1_train=5.77, ce_train=3.74, acc_train=0.212, f1_train=0.212, adv_ce_train=4.7, adv_acc_train=0.0979, adv_f1_train=0.0979]

Epoch 00067: loss_validation reached. Module best state updated.

Epoch 71/1000:   7%|▋         | 70/1000 [10:25<2:10:57,  8.45s/it, v_num=1, loss_validation=5.06, x_0_validation=0.235, x_1_validation=0.236, rec_x_cf_validation=0.19, z_1_validation=4.86, ce_validation=3.74, acc_validation=0.213, f1_validation=0.213, adv_ce_validation=4.69, adv_acc_validation=0.0986, adv_f1_validation=0.0986, loss_train=5.06, x_0_train=0.235, x_1_train=0.236, rec_x_cf_train=0.19, z_1_train=5.77, ce_train=3.74, acc_train=0.211, f1_train=0.211, adv_ce_train=4.69, adv_acc_train=0.0974, adv_f1_train=0.0974]

Epoch 00070: loss_validation reached. Module best state updated.

Epoch 72/1000:   7%|▋         | 71/1000 [10:37<2:28:43,  9.61s/it, v_num=1, loss_validation=5.04, x_0_validation=0.234, x_1_validation=0.235, rec_x_cf_validation=0.19, z_1_validation=5.3, ce_validation=3.71, acc_validation=0.224, f1_validation=0.224, adv_ce_validation=4.67, adv_acc_validation=0.0989, adv_f1_validation=0.0989, loss_train=4.99, x_0_train=0.235, x_1_train=0.235, rec_x_cf_train=0.19, z_1_train=5.84, ce_train=3.71, acc_train=0.217, f1_train=0.217, adv_ce_train=4.69, adv_acc_train=0.0976, adv_f1_train=0.0976]

Epoch 00071: loss_validation reached. Module best state updated.

Epoch 73/1000:   7%|▋         | 72/1000 [10:46<2:23:00,  9.25s/it, v_num=1, loss_validation=5.04, x_0_validation=0.234, x_1_validation=0.235, rec_x_cf_validation=0.19, z_1_validation=5, ce_validation=3.66, acc_validation=0.227, f1_validation=0.227, adv_ce_validation=4.67, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=5.05, x_0_train=0.234, x_1_train=0.235, rec_x_cf_train=0.19, z_1_train=5.91, ce_train=3.65, acc_train=0.225, f1_train=0.225, adv_ce_train=4.68, adv_acc_train=0.0981, adv_f1_train=0.0981]

Epoch 00072: loss_validation reached. Module best state updated.

Epoch 76/1000:   8%|▊         | 75/1000 [11:10<2:11:07,  8.50s/it, v_num=1, loss_validation=5.04, x_0_validation=0.234, x_1_validation=0.235, rec_x_cf_validation=0.19, z_1_validation=4.99, ce_validation=3.65, acc_validation=0.227, f1_validation=0.227, adv_ce_validation=4.66, adv_acc_validation=0.0995, adv_f1_validation=0.0995, loss_train=5.05, x_0_train=0.234, x_1_train=0.235, rec_x_cf_train=0.19, z_1_train=5.9, ce_train=3.65, acc_train=0.223, f1_train=0.223, adv_ce_train=4.67, adv_acc_train=0.0982, adv_f1_train=0.0982]

Epoch 00075: loss_validation reached. Module best state updated.

Epoch 77/1000:   8%|▊         | 76/1000 [11:23<2:29:57,  9.74s/it, v_num=1, loss_validation=5.02, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.189, z_1_validation=5.1, ce_validation=3.59, acc_validation=0.24, f1_validation=0.24, adv_ce_validation=4.67, adv_acc_validation=0.0994, adv_f1_validation=0.0994, loss_train=4.97, x_0_train=0.234, x_1_train=0.235, rec_x_cf_train=0.19, z_1_train=5.95, ce_train=3.62, acc_train=0.23, f1_train=0.23, adv_ce_train=4.67, adv_acc_train=0.0985, adv_f1_train=0.0985]

Epoch 00076: loss_validation reached. Module best state updated.

Epoch 78/1000:   8%|▊         | 77/1000 [11:31<2:23:13,  9.31s/it, v_num=1, loss_validation=5.02, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.19, z_1_validation=5.04, ce_validation=3.57, acc_validation=0.242, f1_validation=0.242, adv_ce_validation=4.65, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=5.03, x_0_train=0.234, x_1_train=0.234, rec_x_cf_train=0.19, z_1_train=5.96, ce_train=3.57, acc_train=0.238, f1_train=0.238, adv_ce_train=4.67, adv_acc_train=0.0991, adv_f1_train=0.0991]

Epoch 00077: loss_validation reached. Module best state updated.

Epoch 80/1000:   8%|▊         | 79/1000 [11:49<2:20:33,  9.16s/it, v_num=1, loss_validation=5.02, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.19, z_1_validation=5.03, ce_validation=3.57, acc_validation=0.24, f1_validation=0.24, adv_ce_validation=4.65, adv_acc_validation=0.0998, adv_f1_validation=0.0998, loss_train=5.03, x_0_train=0.234, x_1_train=0.234, rec_x_cf_train=0.19, z_1_train=5.97, ce_train=3.57, acc_train=0.238, f1_train=0.238, adv_ce_train=4.66, adv_acc_train=0.0988, adv_f1_train=0.0988]

Epoch 00079: loss_validation reached. Module best state updated.

Epoch 81/1000:   8%|▊         | 80/1000 [11:57<2:15:27,  8.83s/it, v_num=1, loss_validation=5.02, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.19, z_1_validation=5.04, ce_validation=3.57, acc_validation=0.24, f1_validation=0.24, adv_ce_validation=4.65, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=5.03, x_0_train=0.234, x_1_train=0.234, rec_x_cf_train=0.19, z_1_train=5.96, ce_train=3.57, acc_train=0.238, f1_train=0.238, adv_ce_train=4.66, adv_acc_train=0.0991, adv_f1_train=0.0991]

Epoch 00080: loss_validation reached. Module best state updated.

Epoch 82/1000:   8%|▊         | 81/1000 [12:09<2:31:51,  9.91s/it, v_num=1, loss_validation=5.01, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.189, z_1_validation=5.3, ce_validation=3.49, acc_validation=0.25, f1_validation=0.25, adv_ce_validation=4.64, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.96, x_0_train=0.233, x_1_train=0.234, rec_x_cf_train=0.19, z_1_train=6.06, ce_train=3.53, acc_train=0.244, f1_train=0.244, adv_ce_train=4.66, adv_acc_train=0.0996, adv_f1_train=0.0996]

Epoch 00081: loss_validation reached. Module best state updated.

Epoch 84/1000:   8%|▊         | 83/1000 [12:26<2:19:36,  9.13s/it, v_num=1, loss_validation=5.01, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.19, z_1_validation=5.14, ce_validation=3.48, acc_validation=0.255, f1_validation=0.255, adv_ce_validation=4.64, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=5.01, x_0_train=0.233, x_1_train=0.234, rec_x_cf_train=0.189, z_1_train=6.08, ce_train=3.48, acc_train=0.25, f1_train=0.25, adv_ce_train=4.65, adv_acc_train=0.0994, adv_f1_train=0.0994]

Epoch 00083: loss_validation reached. Module best state updated.

Epoch 86/1000:   8%|▊         | 85/1000 [12:42<2:11:33,  8.63s/it, v_num=1, loss_validation=5.01, x_0_validation=0.233, x_1_validation=0.234, rec_x_cf_validation=0.19, z_1_validation=5.13, ce_validation=3.49, acc_validation=0.255, f1_validation=0.255, adv_ce_validation=4.64, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=5.01, x_0_train=0.233, x_1_train=0.234, rec_x_cf_train=0.189, z_1_train=6.07, ce_train=3.49, acc_train=0.249, f1_train=0.249, adv_ce_train=4.65, adv_acc_train=0.0997, adv_f1_train=0.0997]

Epoch 00085: loss_validation reached. Module best state updated.

Epoch 87/1000:   9%|▊         | 86/1000 [12:55<2:28:19,  9.74s/it, v_num=1, loss_validation=4.99, x_0_validation=0.232, x_1_validation=0.233, rec_x_cf_validation=0.189, z_1_validation=5.33, ce_validation=3.43, acc_validation=0.262, f1_validation=0.262, adv_ce_validation=4.63, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.94, x_0_train=0.233, x_1_train=0.234, rec_x_cf_train=0.19, z_1_train=6.16, ce_train=3.45, acc_train=0.254, f1_train=0.254, adv_ce_train=4.64, adv_acc_train=0.0999, adv_f1_train=0.0999]

Epoch 00086: loss_validation reached. Module best state updated.

Epoch 88/1000:   9%|▊         | 87/1000 [13:03<2:21:15,  9.28s/it, v_num=1, loss_validation=4.99, x_0_validation=0.232, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.24, ce_validation=3.41, acc_validation=0.263, f1_validation=0.263, adv_ce_validation=4.63, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=5, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.18, ce_train=3.41, acc_train=0.26, f1_train=0.26, adv_ce_train=4.64, adv_acc_train=0.0995, adv_f1_train=0.0995]

Epoch 00087: loss_validation reached. Module best state updated.

Epoch 89/1000:   9%|▉         | 88/1000 [13:11<2:16:28,  8.98s/it, v_num=1, loss_validation=4.99, x_0_validation=0.232, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.24, ce_validation=3.4, acc_validation=0.261, f1_validation=0.261, adv_ce_validation=4.63, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=5, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.19, ce_train=3.41, acc_train=0.26, f1_train=0.26, adv_ce_train=4.64, adv_acc_train=0.0997, adv_f1_train=0.0997]

Epoch 00088: loss_validation reached. Module best state updated.

Epoch 91/1000:   9%|▉         | 90/1000 [13:27<2:09:00,  8.51s/it, v_num=1, loss_validation=4.99, x_0_validation=0.232, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.26, ce_validation=3.41, acc_validation=0.261, f1_validation=0.261, adv_ce_validation=4.63, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=5, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.19, ce_train=3.41, acc_train=0.259, f1_train=0.259, adv_ce_train=4.64, adv_acc_train=0.099, adv_f1_train=0.099]

Epoch 00090: loss_validation reached. Module best state updated.

Epoch 92/1000:   9%|▉         | 91/1000 [13:40<2:26:06,  9.64s/it, v_num=1, loss_validation=4.98, x_0_validation=0.231, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.2, ce_validation=3.38, acc_validation=0.266, f1_validation=0.266, adv_ce_validation=4.62, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.93, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.26, ce_train=3.38, acc_train=0.265, f1_train=0.265, adv_ce_train=4.63, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00091: loss_validation reached. Module best state updated.

Epoch 93/1000:   9%|▉         | 92/1000 [13:48<2:20:10,  9.26s/it, v_num=1, loss_validation=4.98, x_0_validation=0.231, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.37, ce_validation=3.34, acc_validation=0.271, f1_validation=0.271, adv_ce_validation=4.61, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.98, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.3, ce_train=3.33, acc_train=0.27, f1_train=0.27, adv_ce_train=4.62, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00092: loss_validation reached. Module best state updated.

Epoch 96/1000:  10%|▉         | 95/1000 [14:12<2:07:50,  8.48s/it, v_num=1, loss_validation=4.98, x_0_validation=0.231, x_1_validation=0.233, rec_x_cf_validation=0.19, z_1_validation=5.35, ce_validation=3.34, acc_validation=0.272, f1_validation=0.272, adv_ce_validation=4.61, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.98, x_0_train=0.232, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.31, ce_train=3.33, acc_train=0.27, f1_train=0.27, adv_ce_train=4.62, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00095: loss_validation reached. Module best state updated.

Epoch 97/1000:  10%|▉         | 96/1000 [14:25<2:25:30,  9.66s/it, v_num=1, loss_validation=4.96, x_0_validation=0.231, x_1_validation=0.232, rec_x_cf_validation=0.189, z_1_validation=5.8, ce_validation=3.27, acc_validation=0.282, f1_validation=0.282, adv_ce_validation=4.61, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.91, x_0_train=0.231, x_1_train=0.233, rec_x_cf_train=0.19, z_1_train=6.36, ce_train=3.31, acc_train=0.272, f1_train=0.272, adv_ce_train=4.62, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00096: loss_validation reached. Module best state updated.

Epoch 99/1000:  10%|▉         | 98/1000 [14:41<2:14:49,  8.97s/it, v_num=1, loss_validation=4.96, x_0_validation=0.231, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.44, ce_validation=3.28, acc_validation=0.283, f1_validation=0.283, adv_ce_validation=4.61, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.97, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.189, z_1_train=6.38, ce_train=3.27, acc_train=0.279, f1_train=0.279, adv_ce_train=4.62, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00098: loss_validation reached. Module best state updated.

Epoch 101/1000:  10%|█         | 100/1000 [14:57<2:07:13,  8.48s/it, v_num=1, loss_validation=4.96, x_0_validation=0.231, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.42, ce_validation=3.27, acc_validation=0.281, f1_validation=0.281, adv_ce_validation=4.6, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.97, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.189, z_1_train=6.37, ce_train=3.27, acc_train=0.278, f1_train=0.278, adv_ce_train=4.61, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00100: loss_validation reached. Module best state updated.

Epoch 102/1000:  10%|█         | 101/1000 [15:10<2:23:58,  9.61s/it, v_num=1, loss_validation=4.96, x_0_validation=0.23, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.41, ce_validation=3.29, acc_validation=0.27, f1_validation=0.27, adv_ce_validation=4.6, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.9, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.189, z_1_train=6.45, ce_train=3.24, acc_train=0.283, f1_train=0.283, adv_ce_train=4.61, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00101: loss_validation reached. Module best state updated.

Epoch 103/1000:  10%|█         | 102/1000 [15:18<2:17:32,  9.19s/it, v_num=1, loss_validation=4.95, x_0_validation=0.23, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.51, ce_validation=3.21, acc_validation=0.29, f1_validation=0.29, adv_ce_validation=4.59, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.96, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.19, z_1_train=6.46, ce_train=3.2, acc_train=0.286, f1_train=0.286, adv_ce_train=4.6, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00102: loss_validation reached. Module best state updated.

Epoch 105/1000:  10%|█         | 104/1000 [15:34<2:09:00,  8.64s/it, v_num=1, loss_validation=4.95, x_0_validation=0.23, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.5, ce_validation=3.21, acc_validation=0.292, f1_validation=0.292, adv_ce_validation=4.59, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.96, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.19, z_1_train=6.47, ce_train=3.2, acc_train=0.286, f1_train=0.286, adv_ce_train=4.6, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00104: loss_validation reached. Module best state updated.

Epoch 106/1000:  10%|█         | 105/1000 [15:42<2:06:24,  8.47s/it, v_num=1, loss_validation=4.95, x_0_validation=0.23, x_1_validation=0.232, rec_x_cf_validation=0.19, z_1_validation=5.53, ce_validation=3.21, acc_validation=0.291, f1_validation=0.291, adv_ce_validation=4.59, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.96, x_0_train=0.231, x_1_train=0.232, rec_x_cf_train=0.19, z_1_train=6.47, ce_train=3.2, acc_train=0.286, f1_train=0.286, adv_ce_train=4.6, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00105: loss_validation reached. Module best state updated.

Epoch 107/1000:  11%|█         | 106/1000 [15:55<2:23:25,  9.63s/it, v_num=1, loss_validation=4.94, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.189, z_1_validation=5.6, ce_validation=3.22, acc_validation=0.28, f1_validation=0.28, adv_ce_validation=4.59, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.89, x_0_train=0.23, x_1_train=0.232, rec_x_cf_train=0.189, z_1_train=6.54, ce_train=3.18, acc_train=0.288, f1_train=0.288, adv_ce_train=4.6, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00106: loss_validation reached. Module best state updated.

Epoch 111/1000:  11%|█         | 110/1000 [16:27<2:05:58,  8.49s/it, v_num=1, loss_validation=4.94, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.19, z_1_validation=5.62, ce_validation=3.15, acc_validation=0.295, f1_validation=0.295, adv_ce_validation=4.58, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.94, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.19, z_1_train=6.56, ce_train=3.14, acc_train=0.295, f1_train=0.295, adv_ce_train=4.59, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00110: loss_validation reached. Module best state updated.

Epoch 112/1000:  11%|█         | 111/1000 [16:40<2:23:27,  9.68s/it, v_num=1, loss_validation=4.94, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.19, z_1_validation=5.71, ce_validation=3.18, acc_validation=0.292, f1_validation=0.292, adv_ce_validation=4.57, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.88, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.189, z_1_train=6.65, ce_train=3.12, acc_train=0.297, f1_train=0.297, adv_ce_train=4.59, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00111: loss_validation reached. Module best state updated.

Epoch 113/1000:  11%|█         | 112/1000 [16:48<2:17:03,  9.26s/it, v_num=1, loss_validation=4.93, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.19, z_1_validation=5.74, ce_validation=3.1, acc_validation=0.302, f1_validation=0.302, adv_ce_validation=4.57, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.94, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.19, z_1_train=6.69, ce_train=3.08, acc_train=0.302, f1_train=0.302, adv_ce_train=4.59, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00112: loss_validation reached. Module best state updated.

Epoch 115/1000:  11%|█▏        | 114/1000 [17:05<2:11:30,  8.91s/it, v_num=1, loss_validation=4.93, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.19, z_1_validation=5.73, ce_validation=3.11, acc_validation=0.304, f1_validation=0.304, adv_ce_validation=4.57, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.94, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.19, z_1_train=6.68, ce_train=3.08, acc_train=0.3, f1_train=0.3, adv_ce_train=4.58, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00114: loss_validation reached. Module best state updated.

Epoch 116/1000:  12%|█▏        | 115/1000 [17:13<2:07:20,  8.63s/it, v_num=1, loss_validation=4.93, x_0_validation=0.23, x_1_validation=0.231, rec_x_cf_validation=0.19, z_1_validation=5.74, ce_validation=3.1, acc_validation=0.306, f1_validation=0.306, adv_ce_validation=4.57, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.94, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.19, z_1_train=6.68, ce_train=3.08, acc_train=0.301, f1_train=0.301, adv_ce_train=4.58, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00115: loss_validation reached. Module best state updated.

Epoch 117/1000:  12%|█▏        | 116/1000 [17:26<2:23:20,  9.73s/it, v_num=1, loss_validation=4.92, x_0_validation=0.229, x_1_validation=0.231, rec_x_cf_validation=0.189, z_1_validation=5.86, ce_validation=3.08, acc_validation=0.306, f1_validation=0.306, adv_ce_validation=4.57, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.87, x_0_train=0.23, x_1_train=0.231, rec_x_cf_train=0.189, z_1_train=6.74, ce_train=3.07, acc_train=0.303, f1_train=0.303, adv_ce_train=4.58, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00116: loss_validation reached. Module best state updated.

Epoch 119/1000:  12%|█▏        | 118/1000 [17:42<2:12:19,  9.00s/it, v_num=1, loss_validation=4.92, x_0_validation=0.229, x_1_validation=0.23, rec_x_cf_validation=0.189, z_1_validation=5.8, ce_validation=3.05, acc_validation=0.309, f1_validation=0.309, adv_ce_validation=4.56, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.92, x_0_train=0.229, x_1_train=0.231, rec_x_cf_train=0.189, z_1_train=6.75, ce_train=3.03, acc_train=0.309, f1_train=0.309, adv_ce_train=4.58, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00118: loss_validation reached. Module best state updated.

Epoch 121/1000:  12%|█▏        | 120/1000 [17:58<2:04:28,  8.49s/it, v_num=1, loss_validation=4.92, x_0_validation=0.229, x_1_validation=0.23, rec_x_cf_validation=0.189, z_1_validation=5.81, ce_validation=3.05, acc_validation=0.309, f1_validation=0.309, adv_ce_validation=4.56, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.92, x_0_train=0.229, x_1_train=0.231, rec_x_cf_train=0.189, z_1_train=6.75, ce_train=3.02, acc_train=0.309, f1_train=0.309, adv_ce_train=4.57, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00120: loss_validation reached. Module best state updated.

Epoch 122/1000:  12%|█▏        | 121/1000 [18:11<2:21:46,  9.68s/it, v_num=1, loss_validation=4.91, x_0_validation=0.229, x_1_validation=0.23, rec_x_cf_validation=0.189, z_1_validation=6.09, ce_validation=3.05, acc_validation=0.311, f1_validation=0.311, adv_ce_validation=4.55, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.86, x_0_train=0.229, x_1_train=0.23, rec_x_cf_train=0.189, z_1_train=6.83, ce_train=3.01, acc_train=0.312, f1_train=0.312, adv_ce_train=4.57, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00121: loss_validation reached. Module best state updated.

Epoch 124/1000:  12%|█▏        | 123/1000 [18:27<2:11:07,  8.97s/it, v_num=1, loss_validation=4.91, x_0_validation=0.229, x_1_validation=0.23, rec_x_cf_validation=0.19, z_1_validation=5.88, ce_validation=3, acc_validation=0.316, f1_validation=0.316, adv_ce_validation=4.55, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.91, x_0_train=0.229, x_1_train=0.23, rec_x_cf_train=0.19, z_1_train=6.84, ce_train=2.98, acc_train=0.317, f1_train=0.317, adv_ce_train=4.57, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00123: loss_validation reached. Module best state updated.

Epoch 126/1000:  12%|█▎        | 125/1000 [18:43<2:03:57,  8.50s/it, v_num=1, loss_validation=4.91, x_0_validation=0.229, x_1_validation=0.23, rec_x_cf_validation=0.19, z_1_validation=5.9, ce_validation=3, acc_validation=0.315, f1_validation=0.315, adv_ce_validation=4.55, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.91, x_0_train=0.229, x_1_train=0.23, rec_x_cf_train=0.19, z_1_train=6.83, ce_train=2.97, acc_train=0.317, f1_train=0.317, adv_ce_train=4.56, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00125: loss_validation reached. Module best state updated.

Epoch 127/1000:  13%|█▎        | 126/1000 [18:56<2:20:23,  9.64s/it, v_num=1, loss_validation=4.9, x_0_validation=0.228, x_1_validation=0.23, rec_x_cf_validation=0.189, z_1_validation=6.07, ce_validation=3.02, acc_validation=0.309, f1_validation=0.309, adv_ce_validation=4.53, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.85, x_0_train=0.229, x_1_train=0.23, rec_x_cf_train=0.189, z_1_train=6.95, ce_train=2.96, acc_train=0.318, f1_train=0.318, adv_ce_train=4.56, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00126: loss_validation reached. Module best state updated.

Epoch 131/1000:  13%|█▎        | 130/1000 [19:28<2:02:47,  8.47s/it, v_num=1, loss_validation=4.9, x_0_validation=0.228, x_1_validation=0.23, rec_x_cf_validation=0.19, z_1_validation=6.01, ce_validation=2.96, acc_validation=0.324, f1_validation=0.324, adv_ce_validation=4.53, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.9, x_0_train=0.229, x_1_train=0.23, rec_x_cf_train=0.19, z_1_train=6.94, ce_train=2.92, acc_train=0.324, f1_train=0.324, adv_ce_train=4.55, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00130: loss_validation reached. Module best state updated.

Epoch 132/1000:  13%|█▎        | 131/1000 [19:41<2:19:20,  9.62s/it, v_num=1, loss_validation=4.89, x_0_validation=0.228, x_1_validation=0.23, rec_x_cf_validation=0.189, z_1_validation=6.15, ce_validation=2.95, acc_validation=0.32, f1_validation=0.32, adv_ce_validation=4.53, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.84, x_0_train=0.228, x_1_train=0.23, rec_x_cf_train=0.189, z_1_train=7.03, ce_train=2.91, acc_train=0.327, f1_train=0.327, adv_ce_train=4.55, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00131: loss_validation reached. Module best state updated.

Epoch 136/1000:  14%|█▎        | 135/1000 [20:13<2:02:20,  8.49s/it, v_num=1, loss_validation=4.89, x_0_validation=0.228, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.12, ce_validation=2.91, acc_validation=0.331, f1_validation=0.331, adv_ce_validation=4.52, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.89, x_0_train=0.228, x_1_train=0.23, rec_x_cf_train=0.189, z_1_train=7.02, ce_train=2.87, acc_train=0.332, f1_train=0.332, adv_ce_train=4.54, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00135: loss_validation reached. Module best state updated.

Epoch 137/1000:  14%|█▎        | 136/1000 [20:26<2:20:41,  9.77s/it, v_num=1, loss_validation=4.88, x_0_validation=0.228, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.37, ce_validation=2.9, acc_validation=0.336, f1_validation=0.336, adv_ce_validation=4.52, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.83, x_0_train=0.228, x_1_train=0.23, rec_x_cf_train=0.189, z_1_train=7.14, ce_train=2.86, acc_train=0.333, f1_train=0.333, adv_ce_train=4.54, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00136: loss_validation reached. Module best state updated.

Epoch 141/1000:  14%|█▍        | 140/1000 [20:59<2:02:16,  8.53s/it, v_num=1, loss_validation=4.88, x_0_validation=0.228, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.22, ce_validation=2.87, acc_validation=0.337, f1_validation=0.337, adv_ce_validation=4.51, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.89, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.13, ce_train=2.82, acc_train=0.339, f1_train=0.339, adv_ce_train=4.53, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00140: loss_validation reached. Module best state updated.

Epoch 142/1000:  14%|█▍        | 141/1000 [21:11<2:18:17,  9.66s/it, v_num=1, loss_validation=4.88, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.49, ce_validation=2.86, acc_validation=0.34, f1_validation=0.34, adv_ce_validation=4.51, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.82, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.21, ce_train=2.82, acc_train=0.338, f1_train=0.338, adv_ce_train=4.53, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00141: loss_validation reached. Module best state updated.

Epoch 143/1000:  14%|█▍        | 142/1000 [21:19<2:12:20,  9.25s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.26, ce_validation=2.82, acc_validation=0.346, f1_validation=0.346, adv_ce_validation=4.51, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.88, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.15, ce_train=2.77, acc_train=0.348, f1_train=0.348, adv_ce_train=4.53, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00142: loss_validation reached. Module best state updated.

Epoch 144/1000:  14%|█▍        | 143/1000 [21:27<2:07:50,  8.95s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.24, ce_validation=2.82, acc_validation=0.347, f1_validation=0.347, adv_ce_validation=4.51, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.88, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.16, ce_train=2.77, acc_train=0.348, f1_train=0.348, adv_ce_train=4.52, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00143: loss_validation reached. Module best state updated.

Epoch 145/1000:  14%|█▍        | 144/1000 [21:35<2:04:08,  8.70s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.24, ce_validation=2.82, acc_validation=0.346, f1_validation=0.346, adv_ce_validation=4.5, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.88, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.16, ce_train=2.78, acc_train=0.347, f1_train=0.347, adv_ce_train=4.52, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00144: loss_validation reached. Module best state updated.

Epoch 146/1000:  14%|█▍        | 145/1000 [21:43<2:01:03,  8.50s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.27, ce_validation=2.82, acc_validation=0.347, f1_validation=0.347, adv_ce_validation=4.5, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.88, x_0_train=0.228, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.15, ce_train=2.78, acc_train=0.348, f1_train=0.348, adv_ce_train=4.52, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00145: loss_validation reached. Module best state updated.

Epoch 147/1000:  15%|█▍        | 146/1000 [21:57<2:22:04,  9.98s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.19, z_1_validation=6.97, ce_validation=2.85, acc_validation=0.336, f1_validation=0.336, adv_ce_validation=4.51, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.81, x_0_train=0.227, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.3, ce_train=2.77, acc_train=0.348, f1_train=0.348, adv_ce_train=4.52, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00146: loss_validation reached. Module best state updated.

Epoch 148/1000:  15%|█▍        | 147/1000 [22:05<2:14:28,  9.46s/it, v_num=1, loss_validation=4.87, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.189, z_1_validation=6.37, ce_validation=2.78, acc_validation=0.35, f1_validation=0.35, adv_ce_validation=4.5, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.87, x_0_train=0.227, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.29, ce_train=2.72, acc_train=0.355, f1_train=0.355, adv_ce_train=4.52, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00147: loss_validation reached. Module best state updated.

Epoch 151/1000:  15%|█▌        | 150/1000 [22:30<2:01:30,  8.58s/it, v_num=1, loss_validation=4.86, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.19, z_1_validation=6.39, ce_validation=2.77, acc_validation=0.353, f1_validation=0.353, adv_ce_validation=4.5, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.87, x_0_train=0.227, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.29, ce_train=2.72, acc_train=0.355, f1_train=0.355, adv_ce_train=4.52, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00150: loss_validation reached. Module best state updated.

Epoch 152/1000:  15%|█▌        | 151/1000 [22:42<2:17:27,  9.71s/it, v_num=1, loss_validation=4.86, x_0_validation=0.227, x_1_validation=0.229, rec_x_cf_validation=0.19, z_1_validation=6.49, ce_validation=2.8, acc_validation=0.347, f1_validation=0.347, adv_ce_validation=4.49, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.8, x_0_train=0.227, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.38, ce_train=2.72, acc_train=0.356, f1_train=0.356, adv_ce_train=4.51, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00151: loss_validation reached. Module best state updated.

Epoch 153/1000:  15%|█▌        | 152/1000 [22:51<2:11:36,  9.31s/it, v_num=1, loss_validation=4.86, x_0_validation=0.227, x_1_validation=0.228, rec_x_cf_validation=0.19, z_1_validation=6.47, ce_validation=2.73, acc_validation=0.359, f1_validation=0.359, adv_ce_validation=4.48, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.86, x_0_train=0.227, x_1_train=0.229, rec_x_cf_train=0.189, z_1_train=7.38, ce_train=2.68, acc_train=0.362, f1_train=0.362, adv_ce_train=4.51, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00152: loss_validation reached. Module best state updated.

Epoch 157/1000:  16%|█▌        | 156/1000 [23:27<2:15:53,  9.66s/it, v_num=1, loss_validation=4.86, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.63, ce_validation=2.8, acc_validation=0.35, f1_validation=0.35, adv_ce_validation=4.49, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.8, x_0_train=0.227, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.47, ce_train=2.67, acc_train=0.363, f1_train=0.363, adv_ce_train=4.51, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00156: loss_validation reached. Module best state updated.

Epoch 158/1000:  16%|█▌        | 157/1000 [23:36<2:09:45,  9.24s/it, v_num=1, loss_validation=4.85, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.55, ce_validation=2.69, acc_validation=0.366, f1_validation=0.366, adv_ce_validation=4.49, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.86, x_0_train=0.227, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.47, ce_train=2.64, acc_train=0.37, f1_train=0.37, adv_ce_train=4.51, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00157: loss_validation reached. Module best state updated.

Epoch 159/1000:  16%|█▌        | 158/1000 [23:44<2:05:48,  8.96s/it, v_num=1, loss_validation=4.85, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.54, ce_validation=2.69, acc_validation=0.367, f1_validation=0.367, adv_ce_validation=4.49, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.86, x_0_train=0.227, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.47, ce_train=2.63, acc_train=0.371, f1_train=0.371, adv_ce_train=4.51, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00158: loss_validation reached. Module best state updated.

Epoch 162/1000:  16%|█▌        | 161/1000 [24:12<2:14:51,  9.64s/it, v_num=1, loss_validation=4.85, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.88, ce_validation=2.79, acc_validation=0.342, f1_validation=0.342, adv_ce_validation=4.48, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.79, x_0_train=0.227, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.54, ce_train=2.62, acc_train=0.373, f1_train=0.373, adv_ce_train=4.5, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00161: loss_validation reached. Module best state updated.

Epoch 163/1000:  16%|█▌        | 162/1000 [24:21<2:08:52,  9.23s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.66, ce_validation=2.64, acc_validation=0.376, f1_validation=0.376, adv_ce_validation=4.47, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.85, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.53, ce_train=2.58, acc_train=0.377, f1_train=0.377, adv_ce_train=4.5, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00162: loss_validation reached. Module best state updated.

Epoch 166/1000:  16%|█▋        | 165/1000 [24:45<1:58:14,  8.50s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.19, z_1_validation=6.64, ce_validation=2.64, acc_validation=0.375, f1_validation=0.375, adv_ce_validation=4.47, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.85, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.54, ce_train=2.58, acc_train=0.378, f1_train=0.378, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00165: loss_validation reached. Module best state updated.

Epoch 167/1000:  17%|█▋        | 166/1000 [24:57<2:14:00,  9.64s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.44, ce_validation=2.68, acc_validation=0.366, f1_validation=0.366, adv_ce_validation=4.48, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.78, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.6, ce_train=2.57, acc_train=0.381, f1_train=0.381, adv_ce_train=4.5, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00166: loss_validation reached. Module best state updated.

Epoch 168/1000:  17%|█▋        | 167/1000 [25:06<2:08:41,  9.27s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.64, ce_validation=2.59, acc_validation=0.384, f1_validation=0.384, adv_ce_validation=4.47, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.84, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.55, ce_train=2.53, acc_train=0.389, f1_train=0.389, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00167: loss_validation reached. Module best state updated.

Epoch 171/1000:  17%|█▋        | 170/1000 [25:30<1:57:34,  8.50s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.63, ce_validation=2.6, acc_validation=0.382, f1_validation=0.382, adv_ce_validation=4.47, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.84, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.56, ce_train=2.53, acc_train=0.389, f1_train=0.389, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00170: loss_validation reached. Module best state updated.

Epoch 172/1000:  17%|█▋        | 171/1000 [25:43<2:14:27,  9.73s/it, v_num=1, loss_validation=4.84, x_0_validation=0.226, x_1_validation=0.228, rec_x_cf_validation=0.189, z_1_validation=6.93, ce_validation=2.63, acc_validation=0.377, f1_validation=0.377, adv_ce_validation=4.48, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.78, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.66, ce_train=2.52, acc_train=0.388, f1_train=0.388, adv_ce_train=4.49, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00171: loss_validation reached. Module best state updated.

Epoch 177/1000:  18%|█▊        | 176/1000 [26:28<2:14:01,  9.76s/it, v_num=1, loss_validation=4.83, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.19, z_1_validation=6.66, ce_validation=2.59, acc_validation=0.381, f1_validation=0.381, adv_ce_validation=4.47, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.77, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.71, ce_train=2.47, acc_train=0.397, f1_train=0.397, adv_ce_train=4.49, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00176: loss_validation reached. Module best state updated.

Epoch 178/1000:  18%|█▊        | 177/1000 [26:37<2:09:20,  9.43s/it, v_num=1, loss_validation=4.82, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.19, z_1_validation=6.76, ce_validation=2.49, acc_validation=0.402, f1_validation=0.402, adv_ce_validation=4.46, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.83, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.69, ce_train=2.42, acc_train=0.406, f1_train=0.406, adv_ce_train=4.49, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00177: loss_validation reached. Module best state updated.

Epoch 182/1000:  18%|█▊        | 181/1000 [27:16<2:17:05, 10.04s/it, v_num=1, loss_validation=4.84, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=7.58, ce_validation=2.79, acc_validation=0.335, f1_validation=0.335, adv_ce_validation=4.47, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.76, x_0_train=0.226, x_1_train=0.228, rec_x_cf_train=0.189, z_1_train=7.76, ce_train=2.41, acc_train=0.408, f1_train=0.408, adv_ce_train=4.49, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00181: loss_validation reached. Module best state updated.

Epoch 186/1000:  18%|█▊        | 185/1000 [27:49<1:58:05,  8.69s/it, v_num=1, loss_validation=4.82, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.79, ce_validation=2.44, acc_validation=0.411, f1_validation=0.411, adv_ce_validation=4.46, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.82, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.74, ce_train=2.38, acc_train=0.414, f1_train=0.414, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00185: loss_validation reached. Module best state updated.

Epoch 187/1000:  19%|█▊        | 186/1000 [28:02<2:13:44,  9.86s/it, v_num=1, loss_validation=4.82, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.188, z_1_validation=6.63, ce_validation=2.44, acc_validation=0.417, f1_validation=0.417, adv_ce_validation=4.47, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.76, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.81, ce_train=2.36, acc_train=0.417, f1_train=0.417, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00186: loss_validation reached. Module best state updated.

Epoch 188/1000:  19%|█▊        | 187/1000 [28:10<2:07:37,  9.42s/it, v_num=1, loss_validation=4.81, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.188, z_1_validation=6.8, ce_validation=2.37, acc_validation=0.423, f1_validation=0.423, adv_ce_validation=4.46, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.82, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.188, z_1_train=7.77, ce_train=2.31, acc_train=0.426, f1_train=0.426, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00187: loss_validation reached. Module best state updated.

Epoch 190/1000:  19%|█▉        | 189/1000 [28:26<1:59:24,  8.83s/it, v_num=1, loss_validation=4.81, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.188, z_1_validation=6.81, ce_validation=2.38, acc_validation=0.421, f1_validation=0.421, adv_ce_validation=4.46, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.82, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.188, z_1_train=7.78, ce_train=2.31, acc_train=0.428, f1_train=0.428, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00189: loss_validation reached. Module best state updated.

Epoch 192/1000:  19%|█▉        | 191/1000 [28:47<2:11:38,  9.76s/it, v_num=1, loss_validation=4.82, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=7.25, ce_validation=2.51, acc_validation=0.394, f1_validation=0.394, adv_ce_validation=4.48, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.75, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.85, ce_train=2.31, acc_train=0.428, f1_train=0.428, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00191: loss_validation reached. Module best state updated.

Epoch 194/1000:  19%|█▉        | 193/1000 [29:04<2:02:36,  9.12s/it, v_num=1, loss_validation=4.8, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.83, ce_validation=2.32, acc_validation=0.432, f1_validation=0.432, adv_ce_validation=4.47, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.81, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.81, ce_train=2.26, acc_train=0.436, f1_train=0.436, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00193: loss_validation reached. Module best state updated.

Epoch 195/1000:  19%|█▉        | 194/1000 [29:12<1:58:50,  8.85s/it, v_num=1, loss_validation=4.8, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.83, ce_validation=2.33, acc_validation=0.431, f1_validation=0.431, adv_ce_validation=4.46, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.81, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.81, ce_train=2.26, acc_train=0.436, f1_train=0.436, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00194: loss_validation reached. Module best state updated.

Epoch 197/1000:  20%|█▉        | 196/1000 [29:33<2:10:55,  9.77s/it, v_num=1, loss_validation=4.8, x_0_validation=0.225, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.54, ce_validation=2.39, acc_validation=0.42, f1_validation=0.42, adv_ce_validation=4.48, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.74, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.87, ce_train=2.25, acc_train=0.436, f1_train=0.436, adv_ce_train=4.49, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00196: loss_validation reached. Module best state updated.

Epoch 198/1000:  20%|█▉        | 197/1000 [29:42<2:06:29,  9.45s/it, v_num=1, loss_validation=4.8, x_0_validation=0.224, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.86, ce_validation=2.26, acc_validation=0.446, f1_validation=0.446, adv_ce_validation=4.47, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.8, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.86, ce_train=2.2, acc_train=0.449, f1_train=0.449, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00197: loss_validation reached. Module best state updated.

Epoch 199/1000:  20%|█▉        | 198/1000 [29:50<2:02:29,  9.16s/it, v_num=1, loss_validation=4.8, x_0_validation=0.224, x_1_validation=0.227, rec_x_cf_validation=0.189, z_1_validation=6.86, ce_validation=2.27, acc_validation=0.445, f1_validation=0.445, adv_ce_validation=4.47, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.8, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.86, ce_train=2.21, acc_train=0.446, f1_train=0.446, adv_ce_train=4.5, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00198: loss_validation reached. Module best state updated.

Epoch 202/1000:  20%|██        | 201/1000 [30:20<2:12:08,  9.92s/it, v_num=1, loss_validation=4.8, x_0_validation=0.224, x_1_validation=0.227, rec_x_cf_validation=0.188, z_1_validation=6.66, ce_validation=2.32, acc_validation=0.435, f1_validation=0.435, adv_ce_validation=4.48, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.74, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.92, ce_train=2.2, acc_train=0.445, f1_train=0.445, adv_ce_train=4.5, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00201: loss_validation reached. Module best state updated.

Epoch 207/1000:  21%|██        | 206/1000 [31:06<2:11:32,  9.94s/it, v_num=1, loss_validation=4.8, x_0_validation=0.224, x_1_validation=0.227, rec_x_cf_validation=0.19, z_1_validation=7.13, ce_validation=2.29, acc_validation=0.435, f1_validation=0.435, adv_ce_validation=4.49, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.73, x_0_train=0.225, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.94, ce_train=2.14, acc_train=0.458, f1_train=0.458, adv_ce_train=4.51, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00206: loss_validation reached. Module best state updated.

Epoch 208/1000:  21%|██        | 207/1000 [31:15<2:06:21,  9.56s/it, v_num=1, loss_validation=4.79, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.19, z_1_validation=6.88, ce_validation=2.15, acc_validation=0.463, f1_validation=0.463, adv_ce_validation=4.49, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.79, x_0_train=0.224, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.92, ce_train=2.1, acc_train=0.469, f1_train=0.469, adv_ce_train=4.52, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00207: loss_validation reached. Module best state updated.

Epoch 212/1000:  21%|██        | 211/1000 [31:52<2:09:28,  9.85s/it, v_num=1, loss_validation=4.79, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=7.02, ce_validation=2.18, acc_validation=0.459, f1_validation=0.459, adv_ce_validation=4.52, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.73, x_0_train=0.224, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=7.95, ce_train=2.08, acc_train=0.47, f1_train=0.47, adv_ce_train=4.52, adv_acc_train=0.108, adv_f1_train=0.108]

Epoch 00211: loss_validation reached. Module best state updated.

Epoch 217/1000:  22%|██▏       | 216/1000 [32:39<2:11:13, 10.04s/it, v_num=1, loss_validation=4.79, x_0_validation=0.224, x_1_validation=0.227, rec_x_cf_validation=0.19, z_1_validation=7.14, ce_validation=2.17, acc_validation=0.471, f1_validation=0.471, adv_ce_validation=4.52, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.72, x_0_train=0.224, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=8, ce_train=2.03, acc_train=0.481, f1_train=0.481, adv_ce_train=4.53, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00216: loss_validation reached. Module best state updated.

Epoch 222/1000:  22%|██▏       | 221/1000 [33:25<2:07:48,  9.84s/it, v_num=1, loss_validation=4.78, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.46, ce_validation=2.18, acc_validation=0.459, f1_validation=0.459, adv_ce_validation=4.53, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.72, x_0_train=0.224, x_1_train=0.227, rec_x_cf_train=0.189, z_1_train=8.03, ce_train=1.98, acc_train=0.493, f1_train=0.493, adv_ce_train=4.54, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00221: loss_validation reached. Module best state updated.

Epoch 223/1000:  22%|██▏       | 222/1000 [33:34<2:02:20,  9.43s/it, v_num=1, loss_validation=4.77, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.9, ce_validation=1.97, acc_validation=0.504, f1_validation=0.504, adv_ce_validation=4.52, adv_acc_validation=0.111, adv_f1_validation=0.111, loss_train=4.78, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.02, ce_train=1.93, acc_train=0.504, f1_train=0.504, adv_ce_train=4.55, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00222: loss_validation reached. Module best state updated.

Epoch 227/1000:  23%|██▎       | 226/1000 [34:11<2:06:43,  9.82s/it, v_num=1, loss_validation=4.77, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.55, ce_validation=2.05, acc_validation=0.491, f1_validation=0.491, adv_ce_validation=4.53, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.71, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.189, z_1_train=8.05, ce_train=1.93, acc_train=0.505, f1_train=0.505, adv_ce_train=4.55, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00226: loss_validation reached. Module best state updated.

Epoch 232/1000:  23%|██▎       | 231/1000 [34:57<2:06:56,  9.90s/it, v_num=1, loss_validation=4.77, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.84, ce_validation=2.01, acc_validation=0.494, f1_validation=0.494, adv_ce_validation=4.55, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.71, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.06, ce_train=1.87, acc_train=0.516, f1_train=0.516, adv_ce_train=4.56, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00231: loss_validation reached. Module best state updated.

Epoch 237/1000:  24%|██▎       | 236/1000 [35:43<2:04:28,  9.78s/it, v_num=1, loss_validation=4.77, x_0_validation=0.224, x_1_validation=0.226, rec_x_cf_validation=0.187, z_1_validation=7.3, ce_validation=1.98, acc_validation=0.498, f1_validation=0.498, adv_ce_validation=4.57, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.7, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.1, ce_train=1.82, acc_train=0.531, f1_train=0.531, adv_ce_train=4.57, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00236: loss_validation reached. Module best state updated.

Epoch 238/1000:  24%|██▎       | 237/1000 [35:52<1:58:57,  9.35s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.85, ce_validation=1.81, acc_validation=0.544, f1_validation=0.544, adv_ce_validation=4.54, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.76, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.06, ce_train=1.77, acc_train=0.541, f1_train=0.541, adv_ce_train=4.57, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00237: loss_validation reached. Module best state updated.

Epoch 240/1000:  24%|██▍       | 239/1000 [36:08<1:50:54,  8.74s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.87, ce_validation=1.8, acc_validation=0.545, f1_validation=0.545, adv_ce_validation=4.53, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.76, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.05, ce_train=1.77, acc_train=0.542, f1_train=0.542, adv_ce_train=4.56, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00239: loss_validation reached. Module best state updated.

Epoch 242/1000:  24%|██▍       | 241/1000 [36:28<2:02:26,  9.68s/it, v_num=1, loss_validation=4.76, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=7.08, ce_validation=1.91, acc_validation=0.529, f1_validation=0.529, adv_ce_validation=4.57, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.7, x_0_train=0.224, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.13, ce_train=1.77, acc_train=0.541, f1_train=0.541, adv_ce_train=4.59, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00241: loss_validation reached. Module best state updated.

Epoch 243/1000:  24%|██▍       | 242/1000 [36:37<1:56:58,  9.26s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.87, ce_validation=1.75, acc_validation=0.559, f1_validation=0.559, adv_ce_validation=4.54, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.76, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.11, ce_train=1.73, acc_train=0.554, f1_train=0.554, adv_ce_train=4.58, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00242: loss_validation reached. Module best state updated.

Epoch 245/1000:  24%|██▍       | 244/1000 [36:53<1:49:29,  8.69s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.9, ce_validation=1.75, acc_validation=0.56, f1_validation=0.56, adv_ce_validation=4.52, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.76, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.1, ce_train=1.73, acc_train=0.554, f1_train=0.554, adv_ce_train=4.56, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00244: loss_validation reached. Module best state updated.

Epoch 247/1000:  25%|██▍       | 246/1000 [37:13<2:01:10,  9.64s/it, v_num=1, loss_validation=4.77, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=8.27, ce_validation=2.07, acc_validation=0.459, f1_validation=0.459, adv_ce_validation=4.58, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.69, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.16, ce_train=1.72, acc_train=0.554, f1_train=0.554, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00246: loss_validation reached. Module best state updated.

Epoch 248/1000:  25%|██▍       | 247/1000 [37:22<1:56:17,  9.27s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.92, ce_validation=1.7, acc_validation=0.574, f1_validation=0.574, adv_ce_validation=4.54, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.75, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.19, ce_train=1.68, acc_train=0.566, f1_train=0.566, adv_ce_train=4.58, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00247: loss_validation reached. Module best state updated.

Epoch 249/1000:  25%|██▍       | 248/1000 [37:31<1:56:09,  9.27s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.94, ce_validation=1.7, acc_validation=0.575, f1_validation=0.575, adv_ce_validation=4.52, adv_acc_validation=0.111, adv_f1_validation=0.111, loss_train=4.75, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.18, ce_train=1.68, acc_train=0.566, f1_train=0.566, adv_ce_train=4.56, adv_acc_train=0.107, adv_f1_train=0.107]

Epoch 00248: loss_validation reached. Module best state updated.

Epoch 252/1000:  25%|██▌       | 251/1000 [38:00<2:01:35,  9.74s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.58, ce_validation=1.77, acc_validation=0.554, f1_validation=0.554, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.69, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.16, ce_train=1.67, acc_train=0.566, f1_train=0.566, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00251: loss_validation reached. Module best state updated.

Epoch 253/1000:  25%|██▌       | 252/1000 [38:08<1:56:13,  9.32s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.84, ce_validation=1.64, acc_validation=0.591, f1_validation=0.591, adv_ce_validation=4.55, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.75, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.12, ce_train=1.63, acc_train=0.574, f1_train=0.574, adv_ce_train=4.59, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00252: loss_validation reached. Module best state updated.

Epoch 254/1000:  25%|██▌       | 253/1000 [38:16<1:52:22,  9.03s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.85, ce_validation=1.64, acc_validation=0.591, f1_validation=0.591, adv_ce_validation=4.54, adv_acc_validation=0.11, adv_f1_validation=0.11, loss_train=4.75, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.13, ce_train=1.63, acc_train=0.577, f1_train=0.577, adv_ce_train=4.58, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00253: loss_validation reached. Module best state updated.

Epoch 257/1000:  26%|██▌       | 256/1000 [38:45<1:59:49,  9.66s/it, v_num=1, loss_validation=4.75, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.96, ce_validation=1.78, acc_validation=0.551, f1_validation=0.551, adv_ce_validation=4.62, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.68, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.23, ce_train=1.62, acc_train=0.579, f1_train=0.579, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00256: loss_validation reached. Module best state updated.

Epoch 260/1000:  26%|██▌       | 259/1000 [39:09<1:47:37,  8.72s/it, v_num=1, loss_validation=4.73, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=6.88, ce_validation=1.58, acc_validation=0.603, f1_validation=0.603, adv_ce_validation=4.57, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.74, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.21, ce_train=1.58, acc_train=0.59, f1_train=0.59, adv_ce_train=4.6, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00259: loss_validation reached. Module best state updated.

Epoch 262/1000:  26%|██▌       | 261/1000 [39:30<1:58:50,  9.65s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=7.37, ce_validation=1.71, acc_validation=0.555, f1_validation=0.555, adv_ce_validation=4.61, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.68, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.23, ce_train=1.57, acc_train=0.593, f1_train=0.593, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00261: loss_validation reached. Module best state updated.

Epoch 263/1000:  26%|██▌       | 262/1000 [39:38<1:53:45,  9.25s/it, v_num=1, loss_validation=4.73, x_0_validation=0.223, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.87, ce_validation=1.54, acc_validation=0.615, f1_validation=0.615, adv_ce_validation=4.59, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.74, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.22, ce_train=1.54, acc_train=0.602, f1_train=0.602, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00262: loss_validation reached. Module best state updated.

Epoch 264/1000:  26%|██▋       | 263/1000 [39:46<1:50:16,  8.98s/it, v_num=1, loss_validation=4.73, x_0_validation=0.223, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.85, ce_validation=1.54, acc_validation=0.618, f1_validation=0.618, adv_ce_validation=4.57, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.74, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.21, ce_train=1.53, acc_train=0.604, f1_train=0.604, adv_ce_train=4.61, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00263: loss_validation reached. Module best state updated.

Epoch 265/1000:  26%|██▋       | 264/1000 [39:54<1:46:26,  8.68s/it, v_num=1, loss_validation=4.73, x_0_validation=0.223, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.88, ce_validation=1.54, acc_validation=0.619, f1_validation=0.619, adv_ce_validation=4.57, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.74, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.22, ce_train=1.54, acc_train=0.6, f1_train=0.6, adv_ce_train=4.6, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00264: loss_validation reached. Module best state updated.

Epoch 267/1000:  27%|██▋       | 266/1000 [40:15<1:58:04,  9.65s/it, v_num=1, loss_validation=4.74, x_0_validation=0.223, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=7.62, ce_validation=1.67, acc_validation=0.571, f1_validation=0.571, adv_ce_validation=4.62, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.67, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.26, ce_train=1.53, acc_train=0.605, f1_train=0.605, adv_ce_train=4.64, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00266: loss_validation reached. Module best state updated.

Epoch 268/1000:  27%|██▋       | 267/1000 [40:23<1:53:03,  9.25s/it, v_num=1, loss_validation=4.72, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.88, ce_validation=1.48, acc_validation=0.628, f1_validation=0.628, adv_ce_validation=4.58, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.74, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.21, ce_train=1.49, acc_train=0.614, f1_train=0.614, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00267: loss_validation reached. Module best state updated.

Epoch 272/1000:  27%|██▋       | 271/1000 [41:00<1:56:55,  9.62s/it, v_num=1, loss_validation=4.73, x_0_validation=0.222, x_1_validation=0.226, rec_x_cf_validation=0.188, z_1_validation=7, ce_validation=1.64, acc_validation=0.587, f1_validation=0.587, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.67, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.29, ce_train=1.48, acc_train=0.618, f1_train=0.618, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00271: loss_validation reached. Module best state updated.

Epoch 273/1000:  27%|██▋       | 272/1000 [41:08<1:52:20,  9.26s/it, v_num=1, loss_validation=4.72, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.88, ce_validation=1.43, acc_validation=0.644, f1_validation=0.644, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.73, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.27, ce_train=1.45, acc_train=0.626, f1_train=0.626, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00272: loss_validation reached. Module best state updated.

Epoch 277/1000:  28%|██▊       | 276/1000 [41:45<1:56:25,  9.65s/it, v_num=1, loss_validation=4.73, x_0_validation=0.222, x_1_validation=0.226, rec_x_cf_validation=0.189, z_1_validation=6.79, ce_validation=1.55, acc_validation=0.626, f1_validation=0.626, adv_ce_validation=4.63, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.67, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.31, ce_train=1.44, acc_train=0.627, f1_train=0.627, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00276: loss_validation reached. Module best state updated.

Epoch 282/1000:  28%|██▊       | 281/1000 [42:31<1:59:22,  9.96s/it, v_num=1, loss_validation=4.72, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.76, ce_validation=1.55, acc_validation=0.602, f1_validation=0.602, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.66, x_0_train=0.223, x_1_train=0.226, rec_x_cf_train=0.188, z_1_train=8.33, ce_train=1.4, acc_train=0.639, f1_train=0.639, adv_ce_train=4.67, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00281: loss_validation reached. Module best state updated.

Epoch 283/1000:  28%|██▊       | 282/1000 [42:39<1:53:24,  9.48s/it, v_num=1, loss_validation=4.71, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.86, ce_validation=1.34, acc_validation=0.671, f1_validation=0.671, adv_ce_validation=4.57, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.72, x_0_train=0.223, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.29, ce_train=1.36, acc_train=0.649, f1_train=0.649, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00282: loss_validation reached. Module best state updated.

Epoch 284/1000:  28%|██▊       | 283/1000 [42:47<1:48:38,  9.09s/it, v_num=1, loss_validation=4.71, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.89, ce_validation=1.34, acc_validation=0.673, f1_validation=0.673, adv_ce_validation=4.54, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.72, x_0_train=0.223, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.31, ce_train=1.36, acc_train=0.65, f1_train=0.65, adv_ce_train=4.58, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00283: loss_validation reached. Module best state updated.

Epoch 287/1000:  29%|██▊       | 286/1000 [43:16<1:55:16,  9.69s/it, v_num=1, loss_validation=4.72, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.42, ce_validation=1.53, acc_validation=0.615, f1_validation=0.615, adv_ce_validation=4.63, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.66, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.36, ce_train=1.36, acc_train=0.651, f1_train=0.651, adv_ce_train=4.68, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00286: loss_validation reached. Module best state updated.

Epoch 292/1000:  29%|██▉       | 291/1000 [44:01<1:53:45,  9.63s/it, v_num=1, loss_validation=4.72, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=7.12, ce_validation=1.46, acc_validation=0.638, f1_validation=0.638, adv_ce_validation=4.66, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.65, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.38, ce_train=1.31, acc_train=0.663, f1_train=0.663, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00291: loss_validation reached. Module best state updated.

Epoch 293/1000:  29%|██▉       | 292/1000 [44:09<1:48:49,  9.22s/it, v_num=1, loss_validation=4.7, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=6.84, ce_validation=1.25, acc_validation=0.7, f1_validation=0.7, adv_ce_validation=4.61, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.72, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.36, ce_train=1.28, acc_train=0.673, f1_train=0.673, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00292: loss_validation reached. Module best state updated.

Epoch 297/1000:  30%|██▉       | 296/1000 [44:46<1:53:13,  9.65s/it, v_num=1, loss_validation=4.71, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.72, ce_validation=1.38, acc_validation=0.658, f1_validation=0.658, adv_ce_validation=4.63, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.65, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.42, ce_train=1.28, acc_train=0.672, f1_train=0.672, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00296: loss_validation reached. Module best state updated.

Epoch 298/1000:  30%|██▉       | 297/1000 [44:54<1:48:35,  9.27s/it, v_num=1, loss_validation=4.7, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.91, ce_validation=1.21, acc_validation=0.713, f1_validation=0.713, adv_ce_validation=4.6, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.71, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.39, ce_train=1.24, acc_train=0.686, f1_train=0.686, adv_ce_train=4.64, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00297: loss_validation reached. Module best state updated.

Epoch 302/1000:  30%|███       | 301/1000 [45:31<1:52:33,  9.66s/it, v_num=1, loss_validation=4.71, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.95, ce_validation=1.33, acc_validation=0.666, f1_validation=0.666, adv_ce_validation=4.64, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.65, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.45, ce_train=1.24, acc_train=0.684, f1_train=0.684, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00301: loss_validation reached. Module best state updated.

Epoch 303/1000:  30%|███       | 302/1000 [45:39<1:47:39,  9.25s/it, v_num=1, loss_validation=4.69, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.87, ce_validation=1.16, acc_validation=0.727, f1_validation=0.727, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.71, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.4, ce_train=1.21, acc_train=0.695, f1_train=0.695, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00302: loss_validation reached. Module best state updated.

Epoch 307/1000:  31%|███       | 306/1000 [46:16<1:51:14,  9.62s/it, v_num=1, loss_validation=4.71, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.2, ce_validation=1.37, acc_validation=0.645, f1_validation=0.645, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.64, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.45, ce_train=1.2, acc_train=0.695, f1_train=0.695, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00306: loss_validation reached. Module best state updated.

Epoch 312/1000:  31%|███       | 311/1000 [47:01<1:50:34,  9.63s/it, v_num=1, loss_validation=4.7, x_0_validation=0.222, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=7.07, ce_validation=1.31, acc_validation=0.667, f1_validation=0.667, adv_ce_validation=4.67, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.64, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.49, ce_train=1.16, acc_train=0.706, f1_train=0.706, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00311: loss_validation reached. Module best state updated.

Epoch 314/1000:  31%|███▏      | 313/1000 [47:17<1:42:20,  8.94s/it, v_num=1, loss_validation=4.69, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.91, ce_validation=1.08, acc_validation=0.753, f1_validation=0.753, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.7, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.46, ce_train=1.13, acc_train=0.718, f1_train=0.718, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00313: loss_validation reached. Module best state updated.

Epoch 317/1000:  32%|███▏      | 316/1000 [47:47<1:52:21,  9.86s/it, v_num=1, loss_validation=4.7, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=7.66, ce_validation=1.28, acc_validation=0.683, f1_validation=0.683, adv_ce_validation=4.64, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.64, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.51, ce_train=1.13, acc_train=0.715, f1_train=0.715, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00316: loss_validation reached. Module best state updated.

Epoch 318/1000:  32%|███▏      | 317/1000 [47:55<1:47:03,  9.40s/it, v_num=1, loss_validation=4.69, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.94, ce_validation=1.05, acc_validation=0.762, f1_validation=0.762, adv_ce_validation=4.6, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.7, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.51, ce_train=1.1, acc_train=0.728, f1_train=0.728, adv_ce_train=4.64, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00317: loss_validation reached. Module best state updated.

Epoch 322/1000:  32%|███▏      | 321/1000 [48:32<1:49:21,  9.66s/it, v_num=1, loss_validation=4.69, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.17, ce_validation=1.21, acc_validation=0.695, f1_validation=0.695, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.63, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.51, ce_train=1.1, acc_train=0.725, f1_train=0.725, adv_ce_train=4.68, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00321: loss_validation reached. Module best state updated.

Epoch 323/1000:  32%|███▏      | 322/1000 [48:40<1:44:27,  9.24s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.93, ce_validation=1.01, acc_validation=0.773, f1_validation=0.773, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.7, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.53, ce_train=1.07, acc_train=0.735, f1_train=0.735, adv_ce_train=4.64, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00322: loss_validation reached. Module best state updated.

Epoch 324/1000:  32%|███▏      | 323/1000 [48:48<1:41:16,  8.98s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.94, ce_validation=1.01, acc_validation=0.772, f1_validation=0.772, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.7, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.52, ce_train=1.06, acc_train=0.736, f1_train=0.736, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00323: loss_validation reached. Module best state updated.

Epoch 325/1000:  32%|███▏      | 324/1000 [48:56<1:37:50,  8.68s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=6.95, ce_validation=1.01, acc_validation=0.775, f1_validation=0.775, adv_ce_validation=4.59, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.7, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.52, ce_train=1.06, acc_train=0.736, f1_train=0.736, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00324: loss_validation reached. Module best state updated.

Epoch 327/1000:  33%|███▎      | 326/1000 [49:17<1:48:17,  9.64s/it, v_num=1, loss_validation=4.69, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.14, ce_validation=1.13, acc_validation=0.716, f1_validation=0.716, adv_ce_validation=4.63, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.63, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.54, ce_train=1.06, acc_train=0.734, f1_train=0.734, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00326: loss_validation reached. Module best state updated.

Epoch 328/1000:  33%|███▎      | 327/1000 [49:25<1:43:38,  9.24s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.9, ce_validation=0.976, acc_validation=0.785, f1_validation=0.785, adv_ce_validation=4.62, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.69, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.52, ce_train=1.03, acc_train=0.746, f1_train=0.746, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00327: loss_validation reached. Module best state updated.

Epoch 329/1000:  33%|███▎      | 328/1000 [49:33<1:40:24,  8.97s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.91, ce_validation=0.972, acc_validation=0.783, f1_validation=0.783, adv_ce_validation=4.61, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.69, x_0_train=0.222, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.52, ce_train=1.03, acc_train=0.745, f1_train=0.745, adv_ce_train=4.64, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00328: loss_validation reached. Module best state updated.

Epoch 332/1000:  33%|███▎      | 331/1000 [50:02<1:47:18,  9.62s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=6.98, ce_validation=1.08, acc_validation=0.748, f1_validation=0.748, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.63, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.56, ce_train=1.03, acc_train=0.746, f1_train=0.746, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00331: loss_validation reached. Module best state updated.

Epoch 335/1000:  33%|███▎      | 334/1000 [50:26<1:36:43,  8.71s/it, v_num=1, loss_validation=4.67, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=6.86, ce_validation=0.943, acc_validation=0.792, f1_validation=0.792, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.69, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.51, ce_train=1, acc_train=0.753, f1_train=0.753, adv_ce_train=4.63, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00334: loss_validation reached. Module best state updated.

Epoch 337/1000:  34%|███▎      | 336/1000 [50:47<1:47:08,  9.68s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.82, ce_validation=1.09, acc_validation=0.73, f1_validation=0.73, adv_ce_validation=4.63, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.62, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.56, ce_train=1, acc_train=0.753, f1_train=0.753, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00336: loss_validation reached. Module best state updated.

Epoch 338/1000:  34%|███▎      | 337/1000 [50:55<1:42:17,  9.26s/it, v_num=1, loss_validation=4.67, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.85, ce_validation=0.909, acc_validation=0.806, f1_validation=0.806, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.69, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.5, ce_train=0.974, acc_train=0.766, f1_train=0.766, adv_ce_train=4.65, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00337: loss_validation reached. Module best state updated.

Epoch 339/1000:  34%|███▍      | 338/1000 [51:03<1:38:51,  8.96s/it, v_num=1, loss_validation=4.67, x_0_validation=0.221, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.85, ce_validation=0.905, acc_validation=0.805, f1_validation=0.805, adv_ce_validation=4.6, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.69, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.5, ce_train=0.973, acc_train=0.765, f1_train=0.765, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00338: loss_validation reached. Module best state updated.

Epoch 342/1000:  34%|███▍      | 341/1000 [51:32<1:45:42,  9.62s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.189, z_1_validation=7.36, ce_validation=1.1, acc_validation=0.731, f1_validation=0.731, adv_ce_validation=4.64, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.62, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.57, ce_train=0.969, acc_train=0.767, f1_train=0.767, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00341: loss_validation reached. Module best state updated.

Epoch 343/1000:  34%|███▍      | 342/1000 [51:40<1:41:24,  9.25s/it, v_num=1, loss_validation=4.67, x_0_validation=0.221, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.88, ce_validation=0.87, acc_validation=0.812, f1_validation=0.812, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.68, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.56, ce_train=0.944, acc_train=0.772, f1_train=0.772, adv_ce_train=4.65, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00342: loss_validation reached. Module best state updated.

Epoch 347/1000:  35%|███▍      | 346/1000 [52:17<1:44:47,  9.61s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=7.17, ce_validation=1.01, acc_validation=0.755, f1_validation=0.755, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.62, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.59, ce_train=0.941, acc_train=0.768, f1_train=0.768, adv_ce_train=4.65, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00346: loss_validation reached. Module best state updated.

Epoch 352/1000:  35%|███▌      | 351/1000 [53:03<1:45:50,  9.79s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=7.4, ce_validation=1.04, acc_validation=0.742, f1_validation=0.742, adv_ce_validation=4.64, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.62, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.62, ce_train=0.913, acc_train=0.781, f1_train=0.781, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00351: loss_validation reached. Module best state updated.

Epoch 353/1000:  35%|███▌      | 352/1000 [53:11<1:40:49,  9.34s/it, v_num=1, loss_validation=4.66, x_0_validation=0.221, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.92, ce_validation=0.816, acc_validation=0.829, f1_validation=0.829, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.68, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.6, ce_train=0.887, acc_train=0.79, f1_train=0.79, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00352: loss_validation reached. Module best state updated.

Epoch 357/1000:  36%|███▌      | 356/1000 [53:48<1:43:30,  9.64s/it, v_num=1, loss_validation=4.68, x_0_validation=0.221, x_1_validation=0.225, rec_x_cf_validation=0.187, z_1_validation=7.03, ce_validation=1.03, acc_validation=0.75, f1_validation=0.75, adv_ce_validation=4.64, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.61, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.63, ce_train=0.884, acc_train=0.789, f1_train=0.789, adv_ce_train=4.66, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00356: loss_validation reached. Module best state updated.

Epoch 362/1000:  36%|███▌      | 361/1000 [54:33<1:42:52,  9.66s/it, v_num=1, loss_validation=4.67, x_0_validation=0.221, x_1_validation=0.224, rec_x_cf_validation=0.189, z_1_validation=7.52, ce_validation=0.973, acc_validation=0.754, f1_validation=0.754, adv_ce_validation=4.64, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.61, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.65, ce_train=0.856, acc_train=0.797, f1_train=0.797, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00361: loss_validation reached. Module best state updated.

Epoch 364/1000:  36%|███▋      | 363/1000 [54:49<1:35:23,  8.98s/it, v_num=1, loss_validation=4.66, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.92, ce_validation=0.756, acc_validation=0.845, f1_validation=0.845, adv_ce_validation=4.6, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.67, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.62, ce_train=0.832, acc_train=0.807, f1_train=0.807, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00363: loss_validation reached. Module best state updated.

Epoch 367/1000:  37%|███▋      | 366/1000 [55:18<1:41:50,  9.64s/it, v_num=1, loss_validation=4.67, x_0_validation=0.22, x_1_validation=0.225, rec_x_cf_validation=0.188, z_1_validation=6.97, ce_validation=0.948, acc_validation=0.782, f1_validation=0.782, adv_ce_validation=4.65, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.61, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.65, ce_train=0.837, acc_train=0.802, f1_train=0.802, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00366: loss_validation reached. Module best state updated.

Epoch 368/1000:  37%|███▋      | 367/1000 [55:26<1:37:48,  9.27s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.9, ce_validation=0.732, acc_validation=0.852, f1_validation=0.852, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.67, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.61, ce_train=0.813, acc_train=0.813, f1_train=0.813, adv_ce_train=4.64, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00367: loss_validation reached. Module best state updated.

Epoch 369/1000:  37%|███▋      | 368/1000 [55:34<1:34:11,  8.94s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.9, ce_validation=0.731, acc_validation=0.856, f1_validation=0.856, adv_ce_validation=4.57, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.67, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.188, z_1_train=8.62, ce_train=0.816, acc_train=0.811, f1_train=0.811, adv_ce_train=4.61, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00368: loss_validation reached. Module best state updated.

Epoch 372/1000:  37%|███▋      | 371/1000 [56:03<1:40:47,  9.61s/it, v_num=1, loss_validation=4.67, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.46, ce_validation=0.961, acc_validation=0.757, f1_validation=0.757, adv_ce_validation=4.65, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.6, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.69, ce_train=0.808, acc_train=0.81, f1_train=0.81, adv_ce_train=4.68, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00371: loss_validation reached. Module best state updated.

Epoch 374/1000:  37%|███▋      | 373/1000 [56:19<1:33:27,  8.94s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.97, ce_validation=0.705, acc_validation=0.86, f1_validation=0.86, adv_ce_validation=4.58, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.67, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.73, ce_train=0.789, acc_train=0.817, f1_train=0.817, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00373: loss_validation reached. Module best state updated.

Epoch 377/1000:  38%|███▊      | 376/1000 [56:48<1:40:18,  9.65s/it, v_num=1, loss_validation=4.67, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=8.1, ce_validation=0.939, acc_validation=0.769, f1_validation=0.769, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.6, x_0_train=0.221, x_1_train=0.225, rec_x_cf_train=0.187, z_1_train=8.7, ce_train=0.789, acc_train=0.814, f1_train=0.814, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00376: loss_validation reached. Module best state updated.

Epoch 382/1000:  38%|███▊      | 381/1000 [57:33<1:39:15,  9.62s/it, v_num=1, loss_validation=4.66, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.28, ce_validation=0.83, acc_validation=0.818, f1_validation=0.818, adv_ce_validation=4.66, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.6, x_0_train=0.221, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.72, ce_train=0.76, acc_train=0.825, f1_train=0.825, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00381: loss_validation reached. Module best state updated.

Epoch 387/1000:  39%|███▊      | 386/1000 [58:19<1:39:56,  9.77s/it, v_num=1, loss_validation=4.66, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.45, ce_validation=0.812, acc_validation=0.817, f1_validation=0.817, adv_ce_validation=4.64, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.6, x_0_train=0.221, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.72, ce_train=0.742, acc_train=0.83, f1_train=0.83, adv_ce_train=4.67, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00386: loss_validation reached. Module best state updated.

Epoch 392/1000:  39%|███▉      | 391/1000 [59:04<1:38:22,  9.69s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.13, ce_validation=0.75, acc_validation=0.849, f1_validation=0.849, adv_ce_validation=4.64, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.6, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.77, ce_train=0.722, acc_train=0.834, f1_train=0.834, adv_ce_train=4.68, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00391: loss_validation reached. Module best state updated.

Epoch 394/1000:  39%|███▉      | 393/1000 [59:20<1:31:07,  9.01s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.98, ce_validation=0.608, acc_validation=0.885, f1_validation=0.885, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.66, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.77, ce_train=0.698, acc_train=0.843, f1_train=0.843, adv_ce_train=4.63, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00393: loss_validation reached. Module best state updated.

Epoch 397/1000:  40%|███▉      | 396/1000 [59:49<1:37:31,  9.69s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.48, ce_validation=0.765, acc_validation=0.838, f1_validation=0.838, adv_ce_validation=4.67, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.59, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.78, ce_train=0.702, acc_train=0.841, f1_train=0.841, adv_ce_train=4.68, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00396: loss_validation reached. Module best state updated.

Epoch 400/1000:  40%|███▉      | 399/1000 [1:00:14<1:27:14,  8.71s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=6.92, ce_validation=0.589, acc_validation=0.89, f1_validation=0.89, adv_ce_validation=4.59, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.66, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.73, ce_train=0.685, acc_train=0.844, f1_train=0.844, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00399: loss_validation reached. Module best state updated.

Epoch 402/1000:  40%|████      | 401/1000 [1:00:34<1:36:29,  9.66s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.43, ce_validation=0.774, acc_validation=0.828, f1_validation=0.828, adv_ce_validation=4.67, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.59, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.79, ce_train=0.679, acc_train=0.848, f1_train=0.848, adv_ce_train=4.69, adv_acc_train=0.0999, adv_f1_train=0.0999]

Epoch 00401: loss_validation reached. Module best state updated.

Epoch 403/1000:  40%|████      | 402/1000 [1:00:43<1:32:29,  9.28s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.98, ce_validation=0.562, acc_validation=0.897, f1_validation=0.897, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.8, ce_train=0.659, acc_train=0.853, f1_train=0.853, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00402: loss_validation reached. Module best state updated.

Epoch 404/1000:  40%|████      | 403/1000 [1:00:51<1:29:14,  8.97s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.99, ce_validation=0.566, acc_validation=0.898, f1_validation=0.898, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.79, ce_train=0.658, acc_train=0.857, f1_train=0.857, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00403: loss_validation reached. Module best state updated.

Epoch 405/1000:  40%|████      | 404/1000 [1:00:59<1:26:33,  8.71s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=6.99, ce_validation=0.562, acc_validation=0.898, f1_validation=0.898, adv_ce_validation=4.57, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.79, ce_train=0.66, acc_train=0.854, f1_train=0.854, adv_ce_train=4.61, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00404: loss_validation reached. Module best state updated.

Epoch 407/1000:  41%|████      | 406/1000 [1:01:20<1:35:32,  9.65s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.1, ce_validation=0.711, acc_validation=0.852, f1_validation=0.852, adv_ce_validation=4.69, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.59, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.83, ce_train=0.666, acc_train=0.852, f1_train=0.852, adv_ce_train=4.7, adv_acc_train=0.0993, adv_f1_train=0.0993]

Epoch 00406: loss_validation reached. Module best state updated.

Epoch 408/1000:  41%|████      | 407/1000 [1:01:28<1:31:50,  9.29s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.03, ce_validation=0.545, acc_validation=0.903, f1_validation=0.903, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.84, ce_train=0.641, acc_train=0.86, f1_train=0.86, adv_ce_train=4.66, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00407: loss_validation reached. Module best state updated.

Epoch 409/1000:  41%|████      | 408/1000 [1:01:36<1:28:42,  8.99s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.01, ce_validation=0.545, acc_validation=0.902, f1_validation=0.902, adv_ce_validation=4.59, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.82, ce_train=0.641, acc_train=0.86, f1_train=0.86, adv_ce_train=4.63, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00408: loss_validation reached. Module best state updated.

Epoch 412/1000:  41%|████      | 411/1000 [1:02:05<1:35:02,  9.68s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.189, z_1_validation=8.1, ce_validation=0.815, acc_validation=0.794, f1_validation=0.794, adv_ce_validation=4.67, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.59, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.85, ce_train=0.645, acc_train=0.856, f1_train=0.856, adv_ce_train=4.71, adv_acc_train=0.0986, adv_f1_train=0.0986]

Epoch 00411: loss_validation reached. Module best state updated.

Epoch 413/1000:  41%|████      | 412/1000 [1:02:13<1:30:45,  9.26s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.03, ce_validation=0.535, acc_validation=0.902, f1_validation=0.902, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.188, z_1_train=8.83, ce_train=0.632, acc_train=0.862, f1_train=0.862, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00412: loss_validation reached. Module best state updated.

Epoch 417/1000:  42%|████▏     | 416/1000 [1:02:51<1:37:19, 10.00s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.15, ce_validation=0.631, acc_validation=0.879, f1_validation=0.879, adv_ce_validation=4.68, adv_acc_validation=0.0996, adv_f1_validation=0.0996, loss_train=4.58, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.85, ce_train=0.627, acc_train=0.863, f1_train=0.863, adv_ce_train=4.72, adv_acc_train=0.0984, adv_f1_train=0.0984]

Epoch 00416: loss_validation reached. Module best state updated.

Epoch 418/1000:  42%|████▏     | 417/1000 [1:02:59<1:32:08,  9.48s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7, ce_validation=0.514, acc_validation=0.909, f1_validation=0.909, adv_ce_validation=4.62, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.84, ce_train=0.61, acc_train=0.866, f1_train=0.866, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00417: loss_validation reached. Module best state updated.

Epoch 419/1000:  42%|████▏     | 418/1000 [1:03:07<1:28:19,  9.11s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.03, ce_validation=0.511, acc_validation=0.913, f1_validation=0.913, adv_ce_validation=4.59, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.84, ce_train=0.614, acc_train=0.866, f1_train=0.866, adv_ce_train=4.63, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00418: loss_validation reached. Module best state updated.

Epoch 422/1000:  42%|████▏     | 421/1000 [1:03:36<1:33:51,  9.73s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=8.27, ce_validation=0.867, acc_validation=0.783, f1_validation=0.783, adv_ce_validation=4.69, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.58, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.88, ce_train=0.616, acc_train=0.865, f1_train=0.865, adv_ce_train=4.71, adv_acc_train=0.0987, adv_f1_train=0.0987]

Epoch 00421: loss_validation reached. Module best state updated.

Epoch 424/1000:  42%|████▏     | 423/1000 [1:03:52<1:26:27,  8.99s/it, v_num=1, loss_validation=4.63, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.06, ce_validation=0.495, acc_validation=0.915, f1_validation=0.915, adv_ce_validation=4.56, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.65, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.89, ce_train=0.597, acc_train=0.872, f1_train=0.872, adv_ce_train=4.61, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00423: loss_validation reached. Module best state updated.

Epoch 427/1000:  43%|████▎     | 426/1000 [1:04:21<1:32:19,  9.65s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.4, ce_validation=0.732, acc_validation=0.826, f1_validation=0.826, adv_ce_validation=4.68, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.58, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.88, ce_train=0.593, acc_train=0.873, f1_train=0.873, adv_ce_train=4.74, adv_acc_train=0.0968, adv_f1_train=0.0968]

Epoch 00426: loss_validation reached. Module best state updated.

Epoch 432/1000:  43%|████▎     | 431/1000 [1:05:06<1:31:46,  9.68s/it, v_num=1, loss_validation=4.65, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=8.03, ce_validation=0.887, acc_validation=0.774, f1_validation=0.774, adv_ce_validation=4.69, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.58, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.91, ce_train=0.578, acc_train=0.876, f1_train=0.876, adv_ce_train=4.75, adv_acc_train=0.0965, adv_f1_train=0.0965]

Epoch 00431: loss_validation reached. Module best state updated.

Epoch 433/1000:  43%|████▎     | 432/1000 [1:05:15<1:27:26,  9.24s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=7.04, ce_validation=0.464, acc_validation=0.922, f1_validation=0.922, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.64, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.88, ce_train=0.565, acc_train=0.881, f1_train=0.881, adv_ce_train=4.65, adv_acc_train=0.102, adv_f1_train=0.102]

Epoch 00432: loss_validation reached. Module best state updated.

Epoch 434/1000:  43%|████▎     | 433/1000 [1:05:23<1:24:57,  8.99s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.05, ce_validation=0.468, acc_validation=0.921, f1_validation=0.921, adv_ce_validation=4.56, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.64, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.88, ce_train=0.567, acc_train=0.88, f1_train=0.88, adv_ce_train=4.6, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00433: loss_validation reached. Module best state updated.

Epoch 437/1000:  44%|████▎     | 436/1000 [1:05:51<1:30:50,  9.66s/it, v_num=1, loss_validation=4.65, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.188, z_1_validation=8.02, ce_validation=0.888, acc_validation=0.773, f1_validation=0.773, adv_ce_validation=4.67, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.58, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.9, ce_train=0.562, acc_train=0.88, f1_train=0.88, adv_ce_train=4.73, adv_acc_train=0.0977, adv_f1_train=0.0977]

Epoch 00436: loss_validation reached. Module best state updated.

Epoch 439/1000:  44%|████▍     | 438/1000 [1:06:08<1:23:57,  8.96s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.03, ce_validation=0.453, acc_validation=0.923, f1_validation=0.923, adv_ce_validation=4.56, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.64, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.88, ce_train=0.552, acc_train=0.885, f1_train=0.885, adv_ce_train=4.61, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00438: loss_validation reached. Module best state updated.

Epoch 442/1000:  44%|████▍     | 441/1000 [1:06:37<1:29:49,  9.64s/it, v_num=1, loss_validation=4.64, x_0_validation=0.22, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.66, ce_validation=0.668, acc_validation=0.842, f1_validation=0.842, adv_ce_validation=4.7, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.57, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.92, ce_train=0.549, acc_train=0.885, f1_train=0.885, adv_ce_train=4.72, adv_acc_train=0.0981, adv_f1_train=0.0981]

Epoch 00441: loss_validation reached. Module best state updated.

Epoch 443/1000:  44%|████▍     | 442/1000 [1:06:45<1:26:14,  9.27s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.188, z_1_validation=7.08, ce_validation=0.435, acc_validation=0.929, f1_validation=0.929, adv_ce_validation=4.62, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.64, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.91, ce_train=0.535, acc_train=0.888, f1_train=0.888, adv_ce_train=4.66, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00442: loss_validation reached. Module best state updated.

Epoch 444/1000:  44%|████▍     | 443/1000 [1:06:53<1:23:24,  8.98s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.08, ce_validation=0.436, acc_validation=0.925, f1_validation=0.925, adv_ce_validation=4.59, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.64, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.9, ce_train=0.534, acc_train=0.888, f1_train=0.888, adv_ce_train=4.63, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00443: loss_validation reached. Module best state updated.

Epoch 447/1000:  45%|████▍     | 446/1000 [1:07:22<1:29:41,  9.71s/it, v_num=1, loss_validation=4.63, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.35, ce_validation=0.598, acc_validation=0.884, f1_validation=0.884, adv_ce_validation=4.68, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.57, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.93, ce_train=0.54, acc_train=0.885, f1_train=0.885, adv_ce_train=4.71, adv_acc_train=0.0991, adv_f1_train=0.0991]

Epoch 00446: loss_validation reached. Module best state updated.

Epoch 452/1000:  45%|████▌     | 451/1000 [1:08:08<1:29:49,  9.82s/it, v_num=1, loss_validation=4.63, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.56, ce_validation=0.54, acc_validation=0.901, f1_validation=0.901, adv_ce_validation=4.68, adv_acc_validation=0.0995, adv_f1_validation=0.0995, loss_train=4.57, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.96, ce_train=0.525, acc_train=0.89, f1_train=0.89, adv_ce_train=4.74, adv_acc_train=0.0978, adv_f1_train=0.0978]

Epoch 00451: loss_validation reached. Module best state updated.

Epoch 457/1000:  46%|████▌     | 456/1000 [1:08:53<1:27:37,  9.67s/it, v_num=1, loss_validation=4.64, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=8.02, ce_validation=0.744, acc_validation=0.812, f1_validation=0.812, adv_ce_validation=4.68, adv_acc_validation=0.0996, adv_f1_validation=0.0996, loss_train=4.57, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.96, ce_train=0.508, acc_train=0.895, f1_train=0.895, adv_ce_train=4.72, adv_acc_train=0.0988, adv_f1_train=0.0988]

Epoch 00456: loss_validation reached. Module best state updated.

Epoch 458/1000:  46%|████▌     | 457/1000 [1:09:01<1:23:43,  9.25s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.08, ce_validation=0.392, acc_validation=0.938, f1_validation=0.938, adv_ce_validation=4.6, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.63, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.94, ce_train=0.494, acc_train=0.898, f1_train=0.898, adv_ce_train=4.65, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00457: loss_validation reached. Module best state updated.

Epoch 462/1000:  46%|████▌     | 461/1000 [1:09:38<1:26:38,  9.65s/it, v_num=1, loss_validation=4.64, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.76, ce_validation=0.71, acc_validation=0.836, f1_validation=0.836, adv_ce_validation=4.67, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.57, x_0_train=0.22, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.95, ce_train=0.497, acc_train=0.898, f1_train=0.898, adv_ce_train=4.73, adv_acc_train=0.0992, adv_f1_train=0.0992]

Epoch 00461: loss_validation reached. Module best state updated.

Epoch 463/1000:  46%|████▌     | 462/1000 [1:09:46<1:23:06,  9.27s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.12, ce_validation=0.38, acc_validation=0.941, f1_validation=0.941, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.98, ce_train=0.483, acc_train=0.903, f1_train=0.903, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00462: loss_validation reached. Module best state updated.

Epoch 464/1000:  46%|████▋     | 463/1000 [1:09:54<1:20:11,  8.96s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.188, z_1_validation=7.11, ce_validation=0.379, acc_validation=0.942, f1_validation=0.942, adv_ce_validation=4.6, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.98, ce_train=0.481, acc_train=0.904, f1_train=0.904, adv_ce_train=4.64, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00463: loss_validation reached. Module best state updated.

Epoch 465/1000:  46%|████▋     | 464/1000 [1:10:03<1:17:49,  8.71s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.1, ce_validation=0.38, acc_validation=0.941, f1_validation=0.941, adv_ce_validation=4.59, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.99, ce_train=0.484, acc_train=0.903, f1_train=0.903, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00464: loss_validation reached. Module best state updated.

Epoch 467/1000:  47%|████▋     | 466/1000 [1:10:23<1:26:04,  9.67s/it, v_num=1, loss_validation=4.63, x_0_validation=0.219, x_1_validation=0.224, rec_x_cf_validation=0.187, z_1_validation=7.69, ce_validation=0.637, acc_validation=0.85, f1_validation=0.85, adv_ce_validation=4.68, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.57, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.97, ce_train=0.483, acc_train=0.902, f1_train=0.902, adv_ce_train=4.71, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00466: loss_validation reached. Module best state updated.

Epoch 468/1000:  47%|████▋     | 467/1000 [1:10:32<1:22:18,  9.27s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.11, ce_validation=0.371, acc_validation=0.943, f1_validation=0.943, adv_ce_validation=4.62, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.96, ce_train=0.476, acc_train=0.904, f1_train=0.904, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00467: loss_validation reached. Module best state updated.

Epoch 472/1000:  47%|████▋     | 471/1000 [1:11:08<1:25:07,  9.66s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.74, ce_validation=0.48, acc_validation=0.911, f1_validation=0.911, adv_ce_validation=4.69, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=4.56, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.97, ce_train=0.474, acc_train=0.905, f1_train=0.905, adv_ce_train=4.71, adv_acc_train=0.099, adv_f1_train=0.099]

Epoch 00471: loss_validation reached. Module best state updated.

Epoch 477/1000:  48%|████▊     | 476/1000 [1:11:53<1:24:10,  9.64s/it, v_num=1, loss_validation=4.63, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.188, z_1_validation=8.22, ce_validation=0.646, acc_validation=0.838, f1_validation=0.838, adv_ce_validation=4.7, adv_acc_validation=0.0988, adv_f1_validation=0.0988, loss_train=4.56, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.467, acc_train=0.908, f1_train=0.908, adv_ce_train=4.73, adv_acc_train=0.0981, adv_f1_train=0.0981]

Epoch 00476: loss_validation reached. Module best state updated.

Epoch 480/1000:  48%|████▊     | 479/1000 [1:12:18<1:15:35,  8.70s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.35, acc_validation=0.948, f1_validation=0.948, adv_ce_validation=4.55, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.453, acc_train=0.912, f1_train=0.912, adv_ce_train=4.6, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00479: loss_validation reached. Module best state updated.

Epoch 482/1000:  48%|████▊     | 481/1000 [1:12:39<1:23:38,  9.67s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.41, ce_validation=0.566, acc_validation=0.884, f1_validation=0.884, adv_ce_validation=4.7, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.56, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=8.99, ce_train=0.45, acc_train=0.911, f1_train=0.911, adv_ce_train=4.74, adv_acc_train=0.0984, adv_f1_train=0.0984]

Epoch 00481: loss_validation reached. Module best state updated.

Epoch 483/1000:  48%|████▊     | 482/1000 [1:12:48<1:22:59,  9.61s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.17, ce_validation=0.339, acc_validation=0.95, f1_validation=0.95, adv_ce_validation=4.61, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9.01, ce_train=0.444, acc_train=0.913, f1_train=0.913, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00482: loss_validation reached. Module best state updated.

Epoch 484/1000:  48%|████▊     | 483/1000 [1:12:56<1:19:30,  9.23s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.339, acc_validation=0.95, f1_validation=0.95, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.444, acc_train=0.913, f1_train=0.913, adv_ce_train=4.62, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00483: loss_validation reached. Module best state updated.

Epoch 487/1000:  49%|████▊     | 486/1000 [1:13:25<1:23:12,  9.71s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.35, ce_validation=0.443, acc_validation=0.922, f1_validation=0.922, adv_ce_validation=4.69, adv_acc_validation=0.0998, adv_f1_validation=0.0998, loss_train=4.56, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.44, acc_train=0.914, f1_train=0.914, adv_ce_train=4.73, adv_acc_train=0.0975, adv_f1_train=0.0975]

Epoch 00486: loss_validation reached. Module best state updated.

Epoch 488/1000:  49%|████▊     | 487/1000 [1:13:33<1:19:45,  9.33s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.328, acc_validation=0.953, f1_validation=0.953, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.63, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.433, acc_train=0.915, f1_train=0.915, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00487: loss_validation reached. Module best state updated.

Epoch 492/1000:  49%|████▉     | 491/1000 [1:14:10<1:22:06,  9.68s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.188, z_1_validation=7.42, ce_validation=0.455, acc_validation=0.92, f1_validation=0.92, adv_ce_validation=4.69, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.56, x_0_train=0.219, x_1_train=0.224, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.433, acc_train=0.916, f1_train=0.916, adv_ce_train=4.72, adv_acc_train=0.099, adv_f1_train=0.099]

Epoch 00491: loss_validation reached. Module best state updated.

Epoch 497/1000:  50%|████▉     | 496/1000 [1:14:55<1:21:18,  9.68s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.44, ce_validation=0.525, acc_validation=0.896, f1_validation=0.896, adv_ce_validation=4.69, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.56, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.422, acc_train=0.919, f1_train=0.919, adv_ce_train=4.72, adv_acc_train=0.0984, adv_f1_train=0.0984]

Epoch 00496: loss_validation reached. Module best state updated.

Epoch 500/1000:  50%|████▉     | 499/1000 [1:15:19<1:12:54,  8.73s/it, v_num=1, loss_validation=4.6, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.11, ce_validation=0.31, acc_validation=0.955, f1_validation=0.955, adv_ce_validation=4.58, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=8.98, ce_train=0.413, acc_train=0.921, f1_train=0.921, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00499: loss_validation reached. Module best state updated.

Epoch 502/1000:  50%|█████     | 501/1000 [1:15:40<1:20:15,  9.65s/it, v_num=1, loss_validation=4.63, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=8.24, ce_validation=0.685, acc_validation=0.832, f1_validation=0.832, adv_ce_validation=4.7, adv_acc_validation=0.101, adv_f1_validation=0.101, loss_train=4.56, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.01, ce_train=0.413, acc_train=0.921, f1_train=0.921, adv_ce_train=4.73, adv_acc_train=0.0987, adv_f1_train=0.0987]

Epoch 00501: loss_validation reached. Module best state updated.

Epoch 504/1000:  50%|█████     | 503/1000 [1:15:56<1:14:15,  8.96s/it, v_num=1, loss_validation=4.6, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.16, ce_validation=0.303, acc_validation=0.957, f1_validation=0.957, adv_ce_validation=4.59, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.405, acc_train=0.923, f1_train=0.923, adv_ce_train=4.63, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00503: loss_validation reached. Module best state updated.

Epoch 505/1000:  50%|█████     | 504/1000 [1:16:04<1:11:48,  8.69s/it, v_num=1, loss_validation=4.6, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.3, acc_validation=0.96, f1_validation=0.96, adv_ce_validation=4.58, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.406, acc_train=0.923, f1_train=0.923, adv_ce_train=4.62, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00504: loss_validation reached. Module best state updated.

Epoch 507/1000:  51%|█████     | 506/1000 [1:16:25<1:19:33,  9.66s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.68, ce_validation=0.487, acc_validation=0.897, f1_validation=0.897, adv_ce_validation=4.7, adv_acc_validation=0.0996, adv_f1_validation=0.0996, loss_train=4.56, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.405, acc_train=0.922, f1_train=0.922, adv_ce_train=4.73, adv_acc_train=0.0979, adv_f1_train=0.0979]

Epoch 00506: loss_validation reached. Module best state updated.

Epoch 508/1000:  51%|█████     | 507/1000 [1:16:33<1:15:51,  9.23s/it, v_num=1, loss_validation=4.6, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.17, ce_validation=0.294, acc_validation=0.959, f1_validation=0.959, adv_ce_validation=4.62, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.01, ce_train=0.395, acc_train=0.926, f1_train=0.926, adv_ce_train=4.67, adv_acc_train=0.1, adv_f1_train=0.1]

Epoch 00507: loss_validation reached. Module best state updated.

Epoch 509/1000:  51%|█████     | 508/1000 [1:16:41<1:13:30,  8.97s/it, v_num=1, loss_validation=4.6, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.289, acc_validation=0.963, f1_validation=0.963, adv_ce_validation=4.58, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.01, ce_train=0.394, acc_train=0.928, f1_train=0.928, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00508: loss_validation reached. Module best state updated.

Epoch 512/1000:  51%|█████     | 511/1000 [1:17:10<1:18:39,  9.65s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.21, ce_validation=0.399, acc_validation=0.93, f1_validation=0.93, adv_ce_validation=4.68, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.03, ce_train=0.395, acc_train=0.926, f1_train=0.926, adv_ce_train=4.74, adv_acc_train=0.0971, adv_f1_train=0.0971]

Epoch 00511: loss_validation reached. Module best state updated.

Epoch 514/1000:  51%|█████▏    | 513/1000 [1:17:27<1:12:55,  8.98s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.14, ce_validation=0.284, acc_validation=0.965, f1_validation=0.965, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=8.99, ce_train=0.387, acc_train=0.928, f1_train=0.928, adv_ce_train=4.62, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00513: loss_validation reached. Module best state updated.

Epoch 515/1000:  51%|█████▏    | 514/1000 [1:17:35<1:10:53,  8.75s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.283, acc_validation=0.962, f1_validation=0.962, adv_ce_validation=4.57, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=8.99, ce_train=0.385, acc_train=0.929, f1_train=0.929, adv_ce_train=4.61, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00514: loss_validation reached. Module best state updated.

Epoch 517/1000:  52%|█████▏    | 516/1000 [1:17:57<1:20:56, 10.03s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.59, ce_validation=0.441, acc_validation=0.917, f1_validation=0.917, adv_ce_validation=4.7, adv_acc_validation=0.0991, adv_f1_validation=0.0991, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.39, acc_train=0.927, f1_train=0.927, adv_ce_train=4.74, adv_acc_train=0.0983, adv_f1_train=0.0983]

Epoch 00516: loss_validation reached. Module best state updated.

Epoch 518/1000:  52%|█████▏    | 517/1000 [1:18:05<1:16:39,  9.52s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.274, acc_validation=0.967, f1_validation=0.967, adv_ce_validation=4.61, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.38, acc_train=0.931, f1_train=0.931, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00517: loss_validation reached. Module best state updated.

Epoch 519/1000:  52%|█████▏    | 518/1000 [1:18:13<1:13:41,  9.17s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.15, ce_validation=0.274, acc_validation=0.967, f1_validation=0.967, adv_ce_validation=4.58, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=8.99, ce_train=0.377, acc_train=0.931, f1_train=0.931, adv_ce_train=4.62, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00518: loss_validation reached. Module best state updated.

Epoch 522/1000:  52%|█████▏    | 521/1000 [1:18:42<1:17:28,  9.70s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=8.2, ce_validation=0.652, acc_validation=0.84, f1_validation=0.84, adv_ce_validation=4.69, adv_acc_validation=0.0996, adv_f1_validation=0.0996, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.03, ce_train=0.38, acc_train=0.929, f1_train=0.929, adv_ce_train=4.76, adv_acc_train=0.0974, adv_f1_train=0.0974]

Epoch 00521: loss_validation reached. Module best state updated.

Epoch 525/1000:  52%|█████▏    | 524/1000 [1:19:06<1:09:07,  8.71s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.21, ce_validation=0.27, acc_validation=0.964, f1_validation=0.964, adv_ce_validation=4.55, adv_acc_validation=0.109, adv_f1_validation=0.109, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.07, ce_train=0.375, acc_train=0.931, f1_train=0.931, adv_ce_train=4.59, adv_acc_train=0.106, adv_f1_train=0.106]

Epoch 00524: loss_validation reached. Module best state updated.

Epoch 527/1000:  53%|█████▎    | 526/1000 [1:19:27<1:16:39,  9.70s/it, v_num=1, loss_validation=4.61, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.34, ce_validation=0.359, acc_validation=0.945, f1_validation=0.945, adv_ce_validation=4.71, adv_acc_validation=0.1, adv_f1_validation=0.1, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.06, ce_train=0.375, acc_train=0.93, f1_train=0.93, adv_ce_train=4.77, adv_acc_train=0.0968, adv_f1_train=0.0968]

Epoch 00526: loss_validation reached. Module best state updated.

Epoch 528/1000:  53%|█████▎    | 527/1000 [1:19:35<1:13:10,  9.28s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.17, ce_validation=0.262, acc_validation=0.966, f1_validation=0.966, adv_ce_validation=4.62, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.62, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.365, acc_train=0.935, f1_train=0.935, adv_ce_train=4.67, adv_acc_train=0.0998, adv_f1_train=0.0998]

Epoch 00527: loss_validation reached. Module best state updated.

Epoch 532/1000:  53%|█████▎    | 531/1000 [1:20:12<1:15:36,  9.67s/it, v_num=1, loss_validation=4.62, x_0_validation=0.219, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.88, ce_validation=0.587, acc_validation=0.86, f1_validation=0.86, adv_ce_validation=4.69, adv_acc_validation=0.0995, adv_f1_validation=0.0995, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.03, ce_train=0.366, acc_train=0.933, f1_train=0.933, adv_ce_train=4.75, adv_acc_train=0.0977, adv_f1_train=0.0977]

Epoch 00531: loss_validation reached. Module best state updated.

Epoch 533/1000:  53%|█████▎    | 532/1000 [1:20:20<1:12:23,  9.28s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.2, ce_validation=0.254, acc_validation=0.969, f1_validation=0.969, adv_ce_validation=4.62, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.03, ce_train=0.355, acc_train=0.936, f1_train=0.936, adv_ce_train=4.67, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00532: loss_validation reached. Module best state updated.

Epoch 537/1000:  54%|█████▎    | 536/1000 [1:20:57<1:14:47,  9.67s/it, v_num=1, loss_validation=4.61, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.188, z_1_validation=7.97, ce_validation=0.48, acc_validation=0.9, f1_validation=0.9, adv_ce_validation=4.7, adv_acc_validation=0.0997, adv_f1_validation=0.0997, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.359, acc_train=0.936, f1_train=0.936, adv_ce_train=4.74, adv_acc_train=0.0979, adv_f1_train=0.0979]

Epoch 00536: loss_validation reached. Module best state updated.

Epoch 539/1000:  54%|█████▍    | 538/1000 [1:21:14<1:09:24,  9.01s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.18, ce_validation=0.252, acc_validation=0.969, f1_validation=0.969, adv_ce_validation=4.6, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.351, acc_train=0.937, f1_train=0.937, adv_ce_train=4.64, adv_acc_train=0.103, adv_f1_train=0.103]

Epoch 00538: loss_validation reached. Module best state updated.

Epoch 542/1000:  54%|█████▍    | 541/1000 [1:21:43<1:13:59,  9.67s/it, v_num=1, loss_validation=4.61, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.55, ce_validation=0.416, acc_validation=0.924, f1_validation=0.924, adv_ce_validation=4.7, adv_acc_validation=0.0992, adv_f1_validation=0.0992, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.355, acc_train=0.935, f1_train=0.935, adv_ce_train=4.75, adv_acc_train=0.0975, adv_f1_train=0.0975]

Epoch 00541: loss_validation reached. Module best state updated.

Epoch 543/1000:  54%|█████▍    | 542/1000 [1:21:51<1:10:50,  9.28s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.21, ce_validation=0.241, acc_validation=0.972, f1_validation=0.972, adv_ce_validation=4.62, adv_acc_validation=0.102, adv_f1_validation=0.102, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.03, ce_train=0.343, acc_train=0.941, f1_train=0.941, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00542: loss_validation reached. Module best state updated.

Epoch 547/1000:  55%|█████▍    | 546/1000 [1:22:28<1:13:05,  9.66s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.43, ce_validation=0.369, acc_validation=0.938, f1_validation=0.938, adv_ce_validation=4.71, adv_acc_validation=0.0996, adv_f1_validation=0.0996, loss_train=4.55, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.06, ce_train=0.347, acc_train=0.937, f1_train=0.937, adv_ce_train=4.77, adv_acc_train=0.0961, adv_f1_train=0.0961]

Epoch 00546: loss_validation reached. Module best state updated.

Epoch 548/1000:  55%|█████▍    | 547/1000 [1:22:36<1:09:58,  9.27s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.22, ce_validation=0.237, acc_validation=0.973, f1_validation=0.973, adv_ce_validation=4.61, adv_acc_validation=0.103, adv_f1_validation=0.103, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.05, ce_train=0.342, acc_train=0.939, f1_train=0.939, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00547: loss_validation reached. Module best state updated.

Epoch 549/1000:  55%|█████▍    | 548/1000 [1:22:44<1:07:27,  8.96s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.23, ce_validation=0.234, acc_validation=0.974, f1_validation=0.974, adv_ce_validation=4.57, adv_acc_validation=0.108, adv_f1_validation=0.108, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.06, ce_train=0.342, acc_train=0.938, f1_train=0.938, adv_ce_train=4.62, adv_acc_train=0.104, adv_f1_train=0.104]

Epoch 00548: loss_validation reached. Module best state updated.

Epoch 552/1000:  55%|█████▌    | 551/1000 [1:23:14<1:13:57,  9.88s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.68, ce_validation=0.382, acc_validation=0.932, f1_validation=0.932, adv_ce_validation=4.72, adv_acc_validation=0.0986, adv_f1_validation=0.0986, loss_train=4.54, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.07, ce_train=0.344, acc_train=0.937, f1_train=0.937, adv_ce_train=4.78, adv_acc_train=0.0951, adv_f1_train=0.0951]

Epoch 00551: loss_validation reached. Module best state updated.

Epoch 553/1000:  55%|█████▌    | 552/1000 [1:23:22<1:10:19,  9.42s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.22, ce_validation=0.232, acc_validation=0.973, f1_validation=0.973, adv_ce_validation=4.6, adv_acc_validation=0.106, adv_f1_validation=0.106, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.07, ce_train=0.336, acc_train=0.94, f1_train=0.94, adv_ce_train=4.68, adv_acc_train=0.101, adv_f1_train=0.101]

Epoch 00552: loss_validation reached. Module best state updated.

Epoch 554/1000:  55%|█████▌    | 553/1000 [1:23:30<1:07:43,  9.09s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.21, ce_validation=0.231, acc_validation=0.973, f1_validation=0.973, adv_ce_validation=4.54, adv_acc_validation=0.111, adv_f1_validation=0.111, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.06, ce_train=0.335, acc_train=0.941, f1_train=0.941, adv_ce_train=4.6, adv_acc_train=0.105, adv_f1_train=0.105]

Epoch 00553: loss_validation reached. Module best state updated.

Epoch 557/1000:  56%|█████▌    | 556/1000 [1:23:59<1:11:39,  9.68s/it, v_num=1, loss_validation=4.6, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.51, ce_validation=0.327, acc_validation=0.953, f1_validation=0.953, adv_ce_validation=4.72, adv_acc_validation=0.0987, adv_f1_validation=0.0987, loss_train=4.54, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.05, ce_train=0.338, acc_train=0.939, f1_train=0.939, adv_ce_train=4.8, adv_acc_train=0.095, adv_f1_train=0.095]

Epoch 00556: loss_validation reached. Module best state updated.

Epoch 558/1000:  56%|█████▌    | 557/1000 [1:24:07<1:08:40,  9.30s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.14, ce_validation=0.225, acc_validation=0.974, f1_validation=0.974, adv_ce_validation=4.6, adv_acc_validation=0.105, adv_f1_validation=0.105, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9, ce_train=0.332, acc_train=0.943, f1_train=0.943, adv_ce_train=4.68, adv_acc_train=0.0998, adv_f1_train=0.0998]

Epoch 00557: loss_validation reached. Module best state updated.

Epoch 562/1000:  56%|█████▌    | 561/1000 [1:24:44<1:10:38,  9.66s/it, v_num=1, loss_validation=4.61, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.187, z_1_validation=7.93, ce_validation=0.486, acc_validation=0.893, f1_validation=0.893, adv_ce_validation=4.71, adv_acc_validation=0.0989, adv_f1_validation=0.0989, loss_train=4.54, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.187, z_1_train=9.04, ce_train=0.329, acc_train=0.943, f1_train=0.943, adv_ce_train=4.78, adv_acc_train=0.0952, adv_f1_train=0.0952]

Epoch 00561: loss_validation reached. Module best state updated.

Epoch 568/1000:  57%|█████▋    | 567/1000 [1:25:38<1:06:48,  9.26s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.2, ce_validation=0.217, acc_validation=0.976, f1_validation=0.976, adv_ce_validation=4.62, adv_acc_validation=0.104, adv_f1_validation=0.104, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.186, z_1_train=9.01, ce_train=0.317, acc_train=0.945, f1_train=0.945, adv_ce_train=4.68, adv_acc_train=0.1, adv_f1_train=0.1]         Epoch 00568: reducing learning rate of group 0 to 1.5000e-03.
Epoch 568/1000:  57%|█████▋    | 568/1000 [1:25:46<1:05:14,  9.06s/it, v_num=1, loss_validation=4.59, x_0_validation=0.218, x_1_validation=0.223, rec_x_cf_validation=0.186, z_1_validation=7.18, ce_validation=0.217, acc_validation=0.977, f1_validation=0.977, adv_ce_validation=4.58, adv_acc_validation=0.107, adv_f1_validation=0.107, loss_train=4.61, x_0_train=0.219, x_1_train=0.223, rec_x_cf_train=0.186, z_1_train=9.03, ce_train=0.318, acc_train=0.945, f1_train=0.945, adv_ce_train=4.63, adv_acc_train=0.104, adv_f1_train=0.104]
Monitored metric loss_validation did not improve in the last 6 records. Best score: 4.587. Signaling Trainer to stop.

model.save(f"norman_celldisect/", overwrite=True)
print("norman_celldisect/")

norman_celldisect/

2.4. 3. Predicting a Single Seen Perturbation

First, let’s predict a perturbation that the model has seen during training.

seen_pert = train_single[0]
print(f"Predicting seen single-gene perturbation: '{seen_pert}'")

x_ctrl, x_true, x_pred = model.predict_perturbation(
    adata_eval,
    perturbation=seen_pert,
    source_perturbation=control_label,
    cats=cats,
    perturbation_key=perturbation_key,
    n_samples_from_source=500,
)

print(f"Control shape:   {x_ctrl.shape}")
print(f"True shape:      {x_true.shape}")
print(f"Predicted shape: {x_pred.shape}")

Predicting seen single-gene perturbation: 'TSC22D1'
Control shape:   torch.Size([500, 5045])
True shape:      torch.Size([376, 5045])
Predicted shape: torch.Size([500, 5045])

metrics_seen_single = perturbation_metrics(
    x_pred.numpy(), x_true.numpy(), x_ctrl.numpy(), top_n_de=20
)
print(f"Metrics for seen perturbation '{seen_pert}':")
for k, v in metrics_seen_single.items():
    print(f"  {k}: {v:.4f}")

Metrics for seen perturbation 'TSC22D1':
  pearson_mean: 0.9927
  pearson_delta: 0.0228
  mse: 0.0038
  top20_de_pearson: 0.9298
  top20_de_cosine: 0.3240

2.5. 4. Predicting a Single Unseen Perturbation

Now we predict one of the held-out perturbations that was not in the training data. We pass its GenePT embedding via new_embeddings.

unseen_pert = holdout_single[0]
print(f"Predicting unseen single-gene perturbation: '{unseen_pert}'")

unseen_embs = {g: gene_embeddings[g] for g in unseen_pert.split(DELIMITER)}

x_ctrl, x_true, x_pred = model.predict_perturbation(
    adata_eval,
    perturbation=unseen_pert,
    source_perturbation=control_label,
    cats=cats,
    perturbation_key=perturbation_key,
    new_embeddings=unseen_embs,
    n_samples_from_source=500,
)

if x_true is not None:
    metrics_unseen_single = perturbation_metrics(
        x_pred.numpy(), x_true.numpy(), x_ctrl.numpy(), top_n_de=20
    )
    print(f"Metrics for unseen perturbation '{unseen_pert}':")
    for k, v in metrics_unseen_single.items():
        print(f"  {k}: {v:.4f}")
else:
    print(f"No ground-truth cells for '{unseen_pert}' in evaluation data.")
    print(f"Predicted shape: {x_pred.shape}")

Predicting unseen single-gene perturbation: 'FOXO4'
Metrics for unseen perturbation 'FOXO4':
  pearson_mean: 0.9841
  pearson_delta: -0.1067
  mse: 0.0100
  top20_de_pearson: 0.9567
  top20_de_cosine: 0.3998

2.6. 5. Predicting an Unseen Combinatorial Perturbation

CellDISECT handles combinatorial perturbations (e.g. GeneA+GeneB) by summing the atomic component embeddings. Here we predict a held-out combo.

unseen_combo = holdout_combo[0]
print(f"Predicting unseen combinatorial perturbation: '{unseen_combo}'")
print(f"  Components: {unseen_combo.split(DELIMITER)}")

combo_embs = {g: gene_embeddings[g] for g in unseen_combo.split(DELIMITER)}

x_ctrl, x_true, x_pred = model.predict_perturbation(
    adata_eval,
    perturbation=unseen_combo,
    source_perturbation=control_label,
    cats=cats,
    perturbation_key=perturbation_key,
    new_embeddings=combo_embs,
    n_samples_from_source=500,
)

if x_true is not None:
    metrics_unseen_combo = perturbation_metrics(
        x_pred.numpy(), x_true.numpy(), x_ctrl.numpy(), top_n_de=20
    )
    print(f"Metrics for unseen combo '{unseen_combo}':")
    for k, v in metrics_unseen_combo.items():
        print(f"  {k}: {v:.4f}")
else:
    print(f"No ground-truth cells for '{unseen_combo}'.")
    print(f"Predicted shape: {x_pred.shape}")

Predicting unseen combinatorial perturbation: 'MAP2K6+IKZF3'
  Components: ['MAP2K6', 'IKZF3']
Metrics for unseen combo 'MAP2K6+IKZF3':
  pearson_mean: 0.9864
  pearson_delta: 0.6255
  mse: 0.0067
  top20_de_pearson: 0.9028
  top20_de_cosine: 0.9578

2.7. 6. Batch Evaluation with predict_perturbations

For systematic evaluation, we use predict_perturbations (plural) which processes multiple perturbations efficiently by sharing source cell encoding.

We evaluate:

1. All held-out (unseen) perturbations — both single-gene and combinatorial

2. A random subset of seen perturbations — to assess reconstruction quality

np.random.seed(42)

N_SEEN_EVAL = min(20, len(train_perts))
seen_eval_perts = list(np.random.choice(train_perts, size=N_SEEN_EVAL, replace=False))

all_eval_perts = holdout_perts + seen_eval_perts

n_eval_single = sum(1 for p in all_eval_perts if DELIMITER not in p)
n_eval_combo = sum(1 for p in all_eval_perts if DELIMITER in p)
print(f"Evaluating {len(holdout_perts)} unseen + {len(seen_eval_perts)} seen = {len(all_eval_perts)} total")
print(f"  ({n_eval_single} single-gene, {n_eval_combo} combinatorial)")

Evaluating 10 unseen + 20 seen = 30 total
  (13 single-gene, 17 combinatorial)

holdout_perts

['FOXO4',
 'FOXL2',
 'ARRDC3',
 'C19orf26',
 'PTPN12',
 'MAP2K6+IKZF3',
 'FEV+ISL2',
 'FOXA3+FOXL2',
 'LHX1+ELMSAN1',
 'FOXA1+FOXL2']

import gc
gc.collect()

14460

# Collect atomic embeddings for all unseen perturbation components
new_embs = {}
for p in holdout_perts:
    for g in p.split(DELIMITER):
        if g not in new_embs:
            new_embs[g] = gene_embeddings[g]

print(f"Providing {len(new_embs)} atomic embeddings for unseen perturbations")

results = model.predict_perturbations(
    adata_eval,
    perturbations=all_eval_perts,
    source_perturbation=control_label,
    cats=cats,
    perturbation_key=perturbation_key,
    new_embeddings=new_embs,
    n_samples_from_source=500,
    batch_size=256,
)

print(f"Predictions returned for {len(results)} perturbations")

Providing 13 atomic embeddings for unseen perturbations
Predictions returned for 30 perturbations

2.7.1. 6.1 Compute metrics for all evaluated perturbations

records = []

for pert, (x_ctrl_i, x_true_i, x_pred_i) in results.items():
    if x_true_i is None:
        continue
    m = perturbation_metrics(
        x_pred_i.numpy(), x_true_i.numpy(), x_ctrl_i.numpy(), top_n_de=20
    )
    m['perturbation'] = pert
    m['split'] = 'unseen' if pert in holdout_perts else 'seen'
    m['type'] = 'combo' if DELIMITER in pert else 'single'
    records.append(m)

metrics_df = pd.DataFrame(records)
metrics_df = metrics_df.set_index('perturbation')

print(f"Computed metrics for {len(metrics_df)} perturbations")
metrics_df.head(10)

Computed metrics for 30 perturbations

	pearson_mean	pearson_delta	mse	top20_de_pearson	top20_de_cosine	split	type
perturbation
FOXO4	0.984066	-0.108509	0.009984	0.956673	0.395618	unseen	single
FOXL2	0.988258	-0.029363	0.008701	0.956343	0.260015	unseen	single
ARRDC3	0.991241	-0.181686	0.005321	0.996426	-0.137059	unseen	single
C19orf26	0.992569	0.168080	0.003984	0.972179	0.712447	unseen	single
PTPN12	0.991953	0.432851	0.004374	0.984046	0.895203	unseen	single
MAP2K6+IKZF3	0.986456	0.627291	0.006720	0.903662	0.957571	unseen	combo
FEV+ISL2	0.978671	0.266620	0.016061	0.905176	0.822309	unseen	combo
FOXA3+FOXL2	0.973870	0.179636	0.019634	0.978840	0.831653	unseen	combo
LHX1+ELMSAN1	0.984850	-0.008092	0.008423	0.716356	0.480285	unseen	combo
FOXA1+FOXL2	0.984429	0.174049	0.012851	0.992558	0.878325	unseen	combo

print("=" * 60)
print("AGGREGATE METRICS")
print("=" * 60)

numeric_cols = [c for c in metrics_df.columns if c not in ('split', 'type')]

for split in ['seen', 'unseen']:
    sub = metrics_df[metrics_df['split'] == split][numeric_cols]
    if len(sub) == 0:
        continue
    print(f"\n--- {split.upper()} perturbations (n={len(sub)}) ---")
    print(sub.describe().loc[['mean', 'std', 'min', 'max']].round(4).to_string())

print("\n" + "=" * 60)
print("BREAKDOWN BY TYPE")
print("=" * 60)

for (split, ptype), sub in metrics_df.groupby(['split', 'type']):
    sub_num = sub[numeric_cols]
    print(f"\n--- {split.upper()} / {ptype.upper()} (n={len(sub_num)}) ---")
    print(sub_num.mean().round(4).to_string())

============================================================
AGGREGATE METRICS
============================================================

--- SEEN perturbations (n=20) ---
      pearson_mean  pearson_delta     mse  top20_de_pearson  top20_de_cosine
mean        0.9869         0.3944  0.0083            0.9436           0.7186
std         0.0070         0.2689  0.0056            0.0629           0.4167
min         0.9649        -0.2056  0.0023            0.7382          -0.6895
max         0.9946         0.7890  0.0248            0.9968           0.9941

--- UNSEEN perturbations (n=10) ---
      pearson_mean  pearson_delta     mse  top20_de_pearson  top20_de_cosine
mean        0.9856         0.1521  0.0096            0.9362           0.6096
std         0.0059         0.2488  0.0052            0.0839           0.3531
min         0.9739        -0.1817  0.0040            0.7164          -0.1371
max         0.9926         0.6273  0.0196            0.9964           0.9576

============================================================
BREAKDOWN BY TYPE
============================================================

--- SEEN / COMBO (n=12) ---
pearson_mean        0.9839
pearson_delta       0.4859
mse                 0.0107
top20_de_pearson    0.9476
top20_de_cosine     0.8531

--- SEEN / SINGLE (n=8) ---
pearson_mean        0.9913
pearson_delta       0.2572
mse                 0.0046
top20_de_pearson    0.9377
top20_de_cosine     0.5169

--- UNSEEN / COMBO (n=5) ---
pearson_mean        0.9817
pearson_delta       0.2479
mse                 0.0127
top20_de_pearson    0.8993
top20_de_cosine     0.7940

--- UNSEEN / SINGLE (n=5) ---
pearson_mean        0.9896
pearson_delta       0.0563
mse                 0.0065
top20_de_pearson    0.9731
top20_de_cosine     0.4252

2.8. 7. Visualization

def plot_prediction_scatter(x_pred, x_true, x_ctrl, title='', top_n_de=20):
    """Scatter plot of predicted vs true mean expression."""
    pred_mean = x_pred.numpy().mean(0) if hasattr(x_pred, 'numpy') else np.asarray(x_pred).mean(0)
    true_mean = x_true.numpy().mean(0) if hasattr(x_true, 'numpy') else np.asarray(x_true).mean(0)
    ctrl_mean = x_ctrl.numpy().mean(0) if hasattr(x_ctrl, 'numpy') else np.asarray(x_ctrl).mean(0)

    delta_true = true_mean - ctrl_mean
    de_idx = np.argsort(-np.abs(delta_true))[:top_n_de]

    fig, axes = plt.subplots(1, 2, figsize=(12, 5))

    r_all, _ = pearsonr(pred_mean, true_mean)
    axes[0].scatter(true_mean, pred_mean, s=1, alpha=0.3)
    axes[0].set_xlabel('True mean expression')
    axes[0].set_ylabel('Predicted mean expression')
    axes[0].set_title(f'{title} — All genes (r={r_all:.3f})')
    lims = [min(axes[0].get_xlim()[0], axes[0].get_ylim()[0]),
            max(axes[0].get_xlim()[1], axes[0].get_ylim()[1])]
    axes[0].plot(lims, lims, 'r--', alpha=0.5)

    r_de, _ = pearsonr(pred_mean[de_idx], true_mean[de_idx])
    axes[1].scatter(true_mean[de_idx], pred_mean[de_idx], s=20, alpha=0.7, c='coral')
    axes[1].set_xlabel('True mean expression')
    axes[1].set_ylabel('Predicted mean expression')
    axes[1].set_title(f'{title} — Top {top_n_de} DE genes (r={r_de:.3f})')
    lims = [min(axes[1].get_xlim()[0], axes[1].get_ylim()[0]),
            max(axes[1].get_xlim()[1], axes[1].get_ylim()[1])]
    axes[1].plot(lims, lims, 'r--', alpha=0.5)

    plt.tight_layout()
    plt.show()

2.8.1. 7.1 Scatter plots for example perturbations

# Seen single-gene perturbation
seen_singles_eval = [p for p in seen_eval_perts if DELIMITER not in p]
if seen_singles_eval:
    pert = seen_singles_eval[0]
    x_c, x_t, x_p = results[pert]
    if x_t is not None:
        plot_prediction_scatter(x_p, x_t, x_c, title=f'Seen single: {pert}')

# Seen combinatorial perturbation
seen_combos_eval = [p for p in seen_eval_perts if DELIMITER in p]
if seen_combos_eval:
    pert = seen_combos_eval[0]
    x_c, x_t, x_p = results[pert]
    if x_t is not None:
        plot_prediction_scatter(x_p, x_t, x_c, title=f'Seen combo: {pert}')

# Unseen single-gene perturbation
if holdout_single:
    pert = holdout_single[0]
    x_c, x_t, x_p = results[pert]
    if x_t is not None:
        plot_prediction_scatter(x_p, x_t, x_c, title=f'Unseen single: {pert}')

# Unseen combinatorial perturbation
if holdout_combo:
    pert = holdout_combo[0]
    x_c, x_t, x_p = results[pert]
    if x_t is not None:
        plot_prediction_scatter(x_p, x_t, x_c, title=f'Unseen combo: {pert}')

2.8.2. 7.2 Compare seen vs unseen metric distributions

plot_metrics = ['pearson_delta', 'top20_de_pearson', 'top20_de_cosine', 'mse']
available_metrics = [m for m in plot_metrics if m in metrics_df.columns]

fig, axes = plt.subplots(1, len(available_metrics), figsize=(5 * len(available_metrics), 4))
if len(available_metrics) == 1:
    axes = [axes]

colors = {'seen': '#4C72B0', 'unseen': '#DD8452'}

for ax, metric in zip(axes, available_metrics):
    for split in ['seen', 'unseen']:
        sub = metrics_df[metrics_df['split'] == split]
        if len(sub) == 0:
            continue
        vals = sub[metric].dropna()
        ax.hist(vals, bins=15, alpha=0.6, label=split, color=colors[split], edgecolor='white')
    ax.set_xlabel(metric)
    ax.set_ylabel('Count')
    ax.legend()
    ax.set_title(metric)

plt.suptitle('Seen vs Unseen Perturbation Metrics', y=1.02, fontsize=14)
plt.tight_layout()
plt.show()

2.8.3. 7.3 Compare single vs combinatorial perturbation metrics

fig, axes = plt.subplots(1, len(available_metrics), figsize=(5 * len(available_metrics), 4))
if len(available_metrics) == 1:
    axes = [axes]

type_colors = {'single': '#55A868', 'combo': '#C44E52'}

for ax, metric in zip(axes, available_metrics):
    for ptype in ['single', 'combo']:
        sub = metrics_df[metrics_df['type'] == ptype]
        if len(sub) == 0:
            continue
        vals = sub[metric].dropna()
        ax.hist(vals, bins=15, alpha=0.6, label=ptype, color=type_colors[ptype], edgecolor='white')
    ax.set_xlabel(metric)
    ax.set_ylabel('Count')
    ax.legend()
    ax.set_title(metric)

plt.suptitle('Single vs Combinatorial Perturbation Metrics', y=1.02, fontsize=14)
plt.tight_layout()
plt.show()

2.8.4. 7.4 Per-perturbation metric bar plot

metric_to_plot = 'pearson_delta'
if metric_to_plot in metrics_df.columns:
    df_sorted = metrics_df.sort_values(metric_to_plot, ascending=False)

    bar_colors = []
    for _, row in df_sorted.iterrows():
        if row['split'] == 'unseen' and row['type'] == 'combo':
            bar_colors.append('#E24A33')  # red — unseen combo
        elif row['split'] == 'unseen':
            bar_colors.append('#DD8452')  # orange — unseen single
        elif row['type'] == 'combo':
            bar_colors.append('#8172B2')  # purple — seen combo
        else:
            bar_colors.append('#4C72B0')  # blue — seen single

    fig, ax = plt.subplots(figsize=(max(10, len(df_sorted) * 0.4), 5))
    ax.bar(range(len(df_sorted)), df_sorted[metric_to_plot], color=bar_colors)
    ax.set_xticks(range(len(df_sorted)))
    ax.set_xticklabels(df_sorted.index, rotation=90, fontsize=7)
    ax.set_ylabel(metric_to_plot)
    ax.set_title(f'{metric_to_plot} per perturbation\n'
                 f'blue=seen/single, purple=seen/combo, orange=unseen/single, red=unseen/combo')
    plt.tight_layout()
    plt.show()

2.8.5. 7.5 Inspect learned perturbation embeddings

names, emb_matrix = model.get_perturbation_embeddings()
print(f"Perturbation embeddings: {len(names)} perturbations, dim={emb_matrix.shape[1]}")
print(f"First 10: {names[:10]}")

Perturbation embeddings: 223 perturbations, dim=1536
First 10: ['AHR', 'AHR+FEV', 'AHR+KLF1', 'ARID1A', 'ATL1', 'BAK1', 'BCL2L11', 'BCL2L11+BAK1', 'BCL2L11+TGFBR2', 'BCORL1']

2.9. 8. Full metrics table

display_cols = [c for c in metrics_df.columns if c not in ('split', 'type')]

print("\n--- UNSEEN SINGLE perturbations ---")
mask = (metrics_df['split'] == 'unseen') & (metrics_df['type'] == 'single')
display(metrics_df[mask][display_cols].round(4))

print("\n--- UNSEEN COMBO perturbations ---")
mask = (metrics_df['split'] == 'unseen') & (metrics_df['type'] == 'combo')
display(metrics_df[mask][display_cols].round(4))

print("\n--- SEEN perturbations (random subset) ---")
mask = metrics_df['split'] == 'seen'
display(metrics_df[mask][display_cols].round(4))

--- UNSEEN SINGLE perturbations ---

	pearson_mean	pearson_delta	mse	top20_de_pearson	top20_de_cosine
perturbation
FOXO4	0.9841	-0.1085	0.0100	0.9567	0.3956
FOXL2	0.9883	-0.0294	0.0087	0.9563	0.2600
ARRDC3	0.9912	-0.1817	0.0053	0.9964	-0.1371
C19orf26	0.9926	0.1681	0.0040	0.9722	0.7124
PTPN12	0.9920	0.4329	0.0044	0.9840	0.8952

--- UNSEEN COMBO perturbations ---

	pearson_mean	pearson_delta	mse	top20_de_pearson	top20_de_cosine
perturbation
MAP2K6+IKZF3	0.9865	0.6273	0.0067	0.9037	0.9576
FEV+ISL2	0.9787	0.2666	0.0161	0.9052	0.8223
FOXA3+FOXL2	0.9739	0.1796	0.0196	0.9788	0.8317
LHX1+ELMSAN1	0.9848	-0.0081	0.0084	0.7164	0.4803
FOXA1+FOXL2	0.9844	0.1740	0.0129	0.9926	0.8783

--- SEEN perturbations (random subset) ---

	pearson_mean	pearson_delta	mse	top20_de_pearson	top20_de_cosine
perturbation
STIL	0.9917	-0.2056	0.0061	0.9934	-0.6895
PLK4+STIL	0.9870	0.1037	0.0094	0.9894	0.7696
BCORL1	0.9917	-0.1271	0.0046	0.9615	-0.0530
CEBPE+SPI1	0.9649	0.4972	0.0248	0.8512	0.8028
CEBPB+OSR2	0.9829	0.5306	0.0108	0.9314	0.8297
TGFBR2+IGDCC3	0.9903	0.4528	0.0064	0.9805	0.8447
FOXF1	0.9923	-0.0397	0.0045	0.9949	0.2522
TBX3	0.9880	0.3738	0.0055	0.7382	0.9405
MAP2K3	0.9937	0.4546	0.0028	0.9809	0.8584
TBX2	0.9886	0.3252	0.0055	0.8577	0.9242
SAMD1+ZBTB1	0.9842	0.5339	0.0101	0.9445	0.8085
DUSP9+KLF1	0.9898	0.7890	0.0053	0.9671	0.9663
CBL+UBASH3B	0.9854	0.6265	0.0099	0.9429	0.9174
FOSB+CEBPB	0.9729	0.4638	0.0213	0.9698	0.7062
DUSP9+ETS2	0.9892	0.4333	0.0080	0.9738	0.8880
MAP2K6+SPI1	0.9897	0.3568	0.0048	0.9262	0.8505
PRTG	0.9902	0.4973	0.0055	0.9782	0.9079
PTPN12+UBASH3A	0.9860	0.5225	0.0096	0.9525	0.9115
KLF1	0.9946	0.7791	0.0023	0.9968	0.9941
SGK1+TBX2	0.9845	0.5202	0.0083	0.9416	0.9422