4. COVID-19 analysis

In this tutorial, we demonstrate how to use publicly available paired scRNA-seq and scATAC-seq data to predict scATAC profiles for unpaired samples that only have scRNA data, and to calculate and analyze transcription factor (TF) motif activity across different sample conditions in the dataset.

We used a public paired scRNA/ATAC-seq dataset from healthy donors (PBMC10k, 10x Multiome) to train an XChrom model, and then predicted the epigenomic features of COVID-19 patients based on their scRNA-seq data,it has been annotated cell types and batch information. We first performed batch correction on COVID-19 and PBMC10k using the Harmony, resulting in batch-corrected cell embeddings stored in RNA.obsm['X_pca_harmony']. The processed COVID-19 scRNA data and the paired PBMC10k scRNA and scATAC data (filtered using a 1% threshold for PBMC10k) have been uploaded to https://doi.org/10.5281/zenodo.16959682. For detailed procedures, please refer to https://github.com/Miaoyuanyuan777/XChrom_analysis.

Data Preprocessing

In this tutorial, we use the paired scRNA/ATAC-seq PBMC10k data as the training set, then predict scATAC profiles for the COVID-19 data. For the training scATAC-seq data, we split it by cells and peaks to generate training/validation data for model input, following the same procedure as in the 1_within_sample analysis tutorial. For the scRNA-seq data, we directly use the processed batch-corrected cell embeddings (RNA.obsm['X_pca_harmony']) as input for model training and prediction.
Model Training

During training, the model accepts two types of inputs: ① DNA sequences (one-hot encoded, 1 × 1344bp) and ② cell embeddings (cell number × 32). The model is trained to predict chromatin accessibility probabilities for each genomic region across all cells. Importantly, the cell embeddings used here are derived from batch-corrected scRNA-seq data from both samples.
Model Prediction

After training, we use the COVID-19 RNA.obsm['X_pca_harmony'] as model input for prediction. Note: Since the COVID-19 data lacks paired scATAC measurements, we can only predict the accessibility of the training set sequences in each COVID-19 cell.
Interpretability analysis

We calculated the TF motif activity at the single-cell level, defined by the difference predicted by XChrom when the motif sequence was inserted into the background sequence. Then we checked if XChrom could identify well-established cell type-specific TF activities.

1. Download Data (PBMC10k, COVID-19)

The original PBMC10k data is available at:

https://cf.10xgenomics.com/samples/cell-arc/2.0.0/pbmc_granulocyte_sorted_10k/pbmc_granulocyte_sorted_10k_filtered_feature_bc_matrix.h5

The original COVID-19 data is available at:

https://nubes.helmholtz-berlin.de/s/wqg6tmX4fW7pci5/download

We have preprocessed this data, including filtering the paired PBMC10k data and extracting only the scRNA data from mild and severe samples in the COVID-19 dataset for analysis. Batch correction was also applied. The preprocessed data can be downloaded from the https://doi.org/10.5281/zenodo.16959682.
Download the PBMC10k data and save it as:

'./data/4_pred_newCondition/pbmc10k_atac.h5ad'

'./data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad'

(These files will be used for model training)
Download the COVID-19 data and save it as:

'./data/4_pred_newCondition/covid_rna_harmony.h5ad'

(This file provides the model input for inferring TF activity)
Download the motif database file from:

https://meme-suite.org/meme/meme-software/Databases/motifs/motif_databases.12.27.tgz

After decompression, select the file motif_databases/CIS-BP_2.00/Homo_sapiens.meme and save it to:

'./data/4_pred_newCondition/Homo_sapiens.meme'
Download the human genome file from:

https://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz

and decompress it.
The raw batch-corrected cell embeddings are stored in RNA.obsm['X_pca_harmony'], and cell type labels are available in RNA.obs['celltypeL0'].

[1]:

import scanpy as sc
import xchrom as xc

[2]:

# import os
# os.environ["CUDA_VISIBLE_DEVICES"]="3,2,1,0"

2. Training/test data prepare

[3]:

## Generate data for model training
train_folder = './data/4_pred_newCondition/train_data/'
input_fasta = '/picb/bigdata/project/miaoyuanyuan/hg38.fa'
train_atac = sc.read_h5ad('./data/4_pred_newCondition/pbmc10k_atac.h5ad')
dict = xc.pp.process_train_test_single(
    ad_atac=train_atac, ## can be a str, Path, or anndata.AnnData object
    input_fasta=input_fasta,
    output_path=train_folder
)

train/test data is saved in:  data/4_pred_newCondition/train_data
successful writing bed file.
successful writing train/test split file.
successful writing train/test anndata file.
successful writing sparse m.
Successfully saving all sequence h5 file...
Successfully saving trainval sequence h5 file...
Successfully saving test sequence h5 file...

We performed preprocessing on the filtered PBMC10k scATAC:

Following the same procedure as in the 1_Within_sample_analysis tutorial, we partitioned the data using 90% of cells and 90% of peaks to generate training/validation sets. This produced:

ad_trainval.h5ad: containing training cells and training peaks
m_trainval.npz: corresponding count matrix
trainval_seqs.h5: base sequence file for training peaks

All files were saved in './data/4_pred_newCondition/train_data/'.

Note: The input_fasta parameter should be replaced with the path to the genome file corresponding to the species used in your specific dataset.

3. Train the model

We use the preprocessed data from the PBMC10k training set obtained above as sequence inputs for the model. The input_folder should contain all files generated during preprocessing. The batch-corrected X_pca_harmony embeddings derived from scRNA data are used as raw cell embeddings and served as cell identity inputs to the model. If using dimensionality reduction results from other methods, they must be stored in cell_embedding_ad.obsm under the key cellembed_raw for extraction.

If you want to compute NS(k=100) and LS(k=100) for monitoring the XChrom training process, you need to set trackscore = True and specify the celltype in either the RNA or ATAC H5AD file.
The model is set to train for 1000 epochs by default, but an early stopping mechanism will be triggered if the increase in training auROC remains below 1e-6 for 50 consecutive epochs.
The save_freq parameter determines the frequency of saving model parameters, with a default value of 1000 (meaning intermediate model parameters are not saved during training).

[4]:

history = xc.tr.train_XChrom(
    input_folder='./data/4_pred_newCondition/train_data/',
    cell_embedding_ad='./data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad',
    cellembed_raw='X_pca_harmony',
    out_path='./data/4_pred_newCondition/train_out/',
    epochs = 1000,
    verbose = 1
)

=== Start training XChrom model ===
Input folder: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_data
Cell embedding file: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad
Raw cell embedding key: X_pca_harmony
Output path: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out
Model parameters: bottleneck=32, batch_size=128, lr=0.01
1. Load raw cell embedding and make z-score normalization...
Raw cell embedding saved to: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad.obsm['X_pca_harmony']
Initial cell embedding saved to: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad.obsm['zscore32_perpc']
Initial cell embedding shape: (11898, 32)
2. Load training data...
3. Prepare train/val data split...
Training peak number: 81963, Validation peak number: 9107
4. Create TensorFlow dataset...

2025-08-18 15:11:33.141411: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2025-08-18 15:11:34.846821: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 21971 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:b1:00.0, compute capability: 8.6
2025-08-18 15:11:34.847782: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 21971 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:98:00.0, compute capability: 8.6
2025-08-18 15:11:34.848213: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 21971 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:4b:00.0, compute capability: 8.6
2025-08-18 15:11:34.848573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 1246 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 3090, pci bus id: 0000:31:00.0, compute capability: 8.6

5. Build and compile model...
Model: "model"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to
==================================================================================================
sequence (InputLayer)           [(None, 1344, 4)]    0
__________________________________________________________________________________________________
stochastic_reverse_complement ( ((None, 1344, 4), () 0           sequence[0][0]
__________________________________________________________________________________________________
stochastic_shift (StochasticShi (None, 1344, 4)      0           stochastic_reverse_complement[0][
__________________________________________________________________________________________________
gelu (GELU)                     (None, 1344, 4)      0           stochastic_shift[0][0]
__________________________________________________________________________________________________
conv1d (Conv1D)                 (None, 1344, 288)    19584       gelu[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 1344, 288)    1152        conv1d[0][0]
__________________________________________________________________________________________________
max_pooling1d (MaxPooling1D)    (None, 448, 288)     0           batch_normalization[0][0]
__________________________________________________________________________________________________
gelu_1 (GELU)                   (None, 448, 288)     0           max_pooling1d[0][0]
__________________________________________________________________________________________________
conv1d_1 (Conv1D)               (None, 448, 288)     414720      gelu_1[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 448, 288)     1152        conv1d_1[0][0]
__________________________________________________________________________________________________
max_pooling1d_1 (MaxPooling1D)  (None, 224, 288)     0           batch_normalization_1[0][0]
__________________________________________________________________________________________________
gelu_2 (GELU)                   (None, 224, 288)     0           max_pooling1d_1[0][0]
__________________________________________________________________________________________________
conv1d_2 (Conv1D)               (None, 224, 323)     465120      gelu_2[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 224, 323)     1292        conv1d_2[0][0]
__________________________________________________________________________________________________
max_pooling1d_2 (MaxPooling1D)  (None, 112, 323)     0           batch_normalization_2[0][0]
__________________________________________________________________________________________________
gelu_3 (GELU)                   (None, 112, 323)     0           max_pooling1d_2[0][0]
__________________________________________________________________________________________________
conv1d_3 (Conv1D)               (None, 112, 363)     586245      gelu_3[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 112, 363)     1452        conv1d_3[0][0]
__________________________________________________________________________________________________
max_pooling1d_3 (MaxPooling1D)  (None, 56, 363)      0           batch_normalization_3[0][0]
__________________________________________________________________________________________________
gelu_4 (GELU)                   (None, 56, 363)      0           max_pooling1d_3[0][0]
__________________________________________________________________________________________________
conv1d_4 (Conv1D)               (None, 56, 407)      738705      gelu_4[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 56, 407)      1628        conv1d_4[0][0]
__________________________________________________________________________________________________
max_pooling1d_4 (MaxPooling1D)  (None, 28, 407)      0           batch_normalization_4[0][0]
__________________________________________________________________________________________________
gelu_5 (GELU)                   (None, 28, 407)      0           max_pooling1d_4[0][0]
__________________________________________________________________________________________________
conv1d_5 (Conv1D)               (None, 28, 456)      927960      gelu_5[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 28, 456)      1824        conv1d_5[0][0]
__________________________________________________________________________________________________
max_pooling1d_5 (MaxPooling1D)  (None, 14, 456)      0           batch_normalization_5[0][0]
__________________________________________________________________________________________________
gelu_6 (GELU)                   (None, 14, 456)      0           max_pooling1d_5[0][0]
__________________________________________________________________________________________________
conv1d_6 (Conv1D)               (None, 14, 512)      1167360     gelu_6[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 14, 512)      2048        conv1d_6[0][0]
__________________________________________________________________________________________________
max_pooling1d_6 (MaxPooling1D)  (None, 7, 512)       0           batch_normalization_6[0][0]
__________________________________________________________________________________________________
gelu_7 (GELU)                   (None, 7, 512)       0           max_pooling1d_6[0][0]
__________________________________________________________________________________________________
conv1d_7 (Conv1D)               (None, 7, 256)       131072      gelu_7[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 7, 256)       1024        conv1d_7[0][0]
__________________________________________________________________________________________________
gelu_8 (GELU)                   (None, 7, 256)       0           batch_normalization_7[0][0]
__________________________________________________________________________________________________
reshape (Reshape)               (None, 1, 1792)      0           gelu_8[0][0]
__________________________________________________________________________________________________
dense (Dense)                   (None, 1, 32)        57344       reshape[0][0]
__________________________________________________________________________________________________
cell_embed (InputLayer)         [(None, 10709, 32)]  0
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 1, 32)        128         dense[0][0]
__________________________________________________________________________________________________
lambda (Lambda)                 (None, 10709, 32)    0           cell_embed[0][0]
__________________________________________________________________________________________________
dropout (Dropout)               (None, 1, 32)        0           batch_normalization_8[0][0]
__________________________________________________________________________________________________
layer_normalization (LayerNorma (None, 10709, 32)    64          lambda[0][0]
__________________________________________________________________________________________________
gelu_9 (GELU)                   (None, 1, 32)        0           dropout[0][0]
__________________________________________________________________________________________________
dense_1 (Dense)                 (None, 10709, 64)    2112        layer_normalization[0][0]
__________________________________________________________________________________________________
tf.compat.v1.squeeze (TFOpLambd (None, 32)           0           gelu_9[0][0]
__________________________________________________________________________________________________
sequencing_depth (InputLayer)   [(None, 10709)]      0
__________________________________________________________________________________________________
final_cellembed (Dense)         (None, 10709, 32)    2080        dense_1[0][0]
__________________________________________________________________________________________________
tf.expand_dims (TFOpLambda)     (None, 32, 1)        0           tf.compat.v1.squeeze[0][0]
__________________________________________________________________________________________________
tf.expand_dims_1 (TFOpLambda)   (None, 10709, 1)     0           sequencing_depth[0][0]
__________________________________________________________________________________________________
tf.linalg.matmul (TFOpLambda)   (None, 10709, 1)     0           final_cellembed[0][0]
                                                                 tf.expand_dims[0][0]
__________________________________________________________________________________________________
dense_2 (Dense)                 (None, 10709, 1)     2           tf.expand_dims_1[0][0]
__________________________________________________________________________________________________
tf.compat.v1.squeeze_2 (TFOpLam (None, 10709)        0           tf.linalg.matmul[0][0]
__________________________________________________________________________________________________
tf.compat.v1.squeeze_1 (TFOpLam (None, 10709)        0           dense_2[0][0]
__________________________________________________________________________________________________
tf.__operators__.add (TFOpLambd (None, 10709)        0           tf.compat.v1.squeeze_2[0][0]
                                                                 tf.compat.v1.squeeze_1[0][0]
__________________________________________________________________________________________________
tf.math.sigmoid (TFOpLambda)    (None, 10709)        0           tf.__operators__.add[0][0]
==================================================================================================
Total params: 4,524,068
Trainable params: 4,518,218
Non-trainable params: 5,850
__________________________________________________________________________________________________
6. Set training callbacks...
7. Start training...
Model will be saved to: data/4_pred_newCondition/train_out/E1000best_model.h5
Epoch 1/1000

2025-08-18 15:11:40.845523: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)
2025-08-18 15:11:46.107242: I tensorflow/stream_executor/cuda/cuda_dnn.cc:369] Loaded cuDNN version 8800
2025-08-18 15:11:46.221853: I tensorflow/stream_executor/cuda/cuda_blas.cc:1760] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.

641/641 [==============================] - 229s 340ms/step - loss: 0.2488 - binary_accuracy: 0.9157 - auc: 0.7736 - pr: 0.2814 - val_loss: 0.2395 - val_binary_accuracy: 0.9172 - val_auc: 0.7982 - val_pr: 0.3480
Epoch 2/1000
641/641 [==============================] - 215s 327ms/step - loss: 0.2334 - binary_accuracy: 0.9187 - auc: 0.7965 - pr: 0.3500 - val_loss: 0.2456 - val_binary_accuracy: 0.9172 - val_auc: 0.7948 - val_pr: 0.3396
Epoch 3/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.2316 - binary_accuracy: 0.9194 - auc: 0.8008 - pr: 0.3593 - val_loss: 0.2433 - val_binary_accuracy: 0.9177 - val_auc: 0.8000 - val_pr: 0.3625
Epoch 4/1000
641/641 [==============================] - 227s 345ms/step - loss: 0.2298 - binary_accuracy: 0.9203 - auc: 0.8046 - pr: 0.3688 - val_loss: 0.2444 - val_binary_accuracy: 0.9173 - val_auc: 0.8035 - val_pr: 0.3603
Epoch 5/1000
641/641 [==============================] - 221s 337ms/step - loss: 0.2287 - binary_accuracy: 0.9205 - auc: 0.8084 - pr: 0.3717 - val_loss: 0.2291 - val_binary_accuracy: 0.9201 - val_auc: 0.8108 - val_pr: 0.3749
Epoch 6/1000
641/641 [==============================] - 228s 351ms/step - loss: 0.2275 - binary_accuracy: 0.9207 - auc: 0.8118 - pr: 0.3761 - val_loss: 0.2298 - val_binary_accuracy: 0.9200 - val_auc: 0.8105 - val_pr: 0.3724
Epoch 7/1000
641/641 [==============================] - 225s 346ms/step - loss: 0.2263 - binary_accuracy: 0.9210 - auc: 0.8157 - pr: 0.3807 - val_loss: 0.2337 - val_binary_accuracy: 0.9187 - val_auc: 0.8171 - val_pr: 0.3780
Epoch 8/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.2251 - binary_accuracy: 0.9210 - auc: 0.8198 - pr: 0.3834 - val_loss: 0.2250 - val_binary_accuracy: 0.9219 - val_auc: 0.8199 - val_pr: 0.3898
Epoch 9/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.2237 - binary_accuracy: 0.9213 - auc: 0.8232 - pr: 0.3887 - val_loss: 0.2275 - val_binary_accuracy: 0.9211 - val_auc: 0.8241 - val_pr: 0.3873
Epoch 10/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.2226 - binary_accuracy: 0.9215 - auc: 0.8263 - pr: 0.3928 - val_loss: 0.2309 - val_binary_accuracy: 0.9193 - val_auc: 0.8240 - val_pr: 0.3879
Epoch 11/1000
641/641 [==============================] - 206s 315ms/step - loss: 0.2214 - binary_accuracy: 0.9218 - auc: 0.8292 - pr: 0.3971 - val_loss: 0.2311 - val_binary_accuracy: 0.9197 - val_auc: 0.8232 - val_pr: 0.3875
Epoch 12/1000
641/641 [==============================] - 222s 339ms/step - loss: 0.2203 - binary_accuracy: 0.9220 - auc: 0.8315 - pr: 0.4021 - val_loss: 0.2216 - val_binary_accuracy: 0.9221 - val_auc: 0.8284 - val_pr: 0.3972
Epoch 13/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.2194 - binary_accuracy: 0.9223 - auc: 0.8335 - pr: 0.4055 - val_loss: 0.2214 - val_binary_accuracy: 0.9222 - val_auc: 0.8280 - val_pr: 0.3966
Epoch 14/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.2186 - binary_accuracy: 0.9226 - auc: 0.8352 - pr: 0.4095 - val_loss: 0.2225 - val_binary_accuracy: 0.9222 - val_auc: 0.8298 - val_pr: 0.4008
Epoch 15/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.2179 - binary_accuracy: 0.9227 - auc: 0.8366 - pr: 0.4127 - val_loss: 0.2197 - val_binary_accuracy: 0.9227 - val_auc: 0.8315 - val_pr: 0.4048
Epoch 16/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.2170 - binary_accuracy: 0.9229 - auc: 0.8383 - pr: 0.4161 - val_loss: 0.2224 - val_binary_accuracy: 0.9224 - val_auc: 0.8313 - val_pr: 0.4010
Epoch 17/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.2162 - binary_accuracy: 0.9232 - auc: 0.8402 - pr: 0.4202 - val_loss: 0.2229 - val_binary_accuracy: 0.9217 - val_auc: 0.8311 - val_pr: 0.4000
Epoch 18/1000
641/641 [==============================] - 213s 324ms/step - loss: 0.2155 - binary_accuracy: 0.9233 - auc: 0.8415 - pr: 0.4230 - val_loss: 0.2256 - val_binary_accuracy: 0.9213 - val_auc: 0.8305 - val_pr: 0.3983
Epoch 19/1000
641/641 [==============================] - 205s 315ms/step - loss: 0.2146 - binary_accuracy: 0.9235 - auc: 0.8431 - pr: 0.4270 - val_loss: 0.2232 - val_binary_accuracy: 0.9215 - val_auc: 0.8315 - val_pr: 0.3966
Epoch 20/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.2139 - binary_accuracy: 0.9236 - auc: 0.8445 - pr: 0.4292 - val_loss: 0.2235 - val_binary_accuracy: 0.9215 - val_auc: 0.8289 - val_pr: 0.3879
Epoch 21/1000
641/641 [==============================] - 230s 353ms/step - loss: 0.2132 - binary_accuracy: 0.9239 - auc: 0.8461 - pr: 0.4322 - val_loss: 0.2200 - val_binary_accuracy: 0.9226 - val_auc: 0.8341 - val_pr: 0.4044
Epoch 22/1000
641/641 [==============================] - 217s 334ms/step - loss: 0.2129 - binary_accuracy: 0.9238 - auc: 0.8465 - pr: 0.4328 - val_loss: 0.2203 - val_binary_accuracy: 0.9204 - val_auc: 0.8347 - val_pr: 0.4072
Epoch 23/1000
641/641 [==============================] - 209s 318ms/step - loss: 0.2118 - binary_accuracy: 0.9242 - auc: 0.8484 - pr: 0.4380 - val_loss: 0.2191 - val_binary_accuracy: 0.9230 - val_auc: 0.8353 - val_pr: 0.4110
Epoch 24/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.2111 - binary_accuracy: 0.9242 - auc: 0.8501 - pr: 0.4402 - val_loss: 0.2220 - val_binary_accuracy: 0.9224 - val_auc: 0.8335 - val_pr: 0.4009
Epoch 25/1000
641/641 [==============================] - 226s 347ms/step - loss: 0.2107 - binary_accuracy: 0.9242 - auc: 0.8510 - pr: 0.4414 - val_loss: 0.2213 - val_binary_accuracy: 0.9224 - val_auc: 0.8310 - val_pr: 0.3961
Epoch 26/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.2099 - binary_accuracy: 0.9245 - auc: 0.8523 - pr: 0.4452 - val_loss: 0.2222 - val_binary_accuracy: 0.9225 - val_auc: 0.8349 - val_pr: 0.4049
Epoch 27/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.2094 - binary_accuracy: 0.9245 - auc: 0.8533 - pr: 0.4466 - val_loss: 0.2188 - val_binary_accuracy: 0.9231 - val_auc: 0.8359 - val_pr: 0.4095
Epoch 28/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.2086 - binary_accuracy: 0.9248 - auc: 0.8550 - pr: 0.4504 - val_loss: 0.2184 - val_binary_accuracy: 0.9229 - val_auc: 0.8362 - val_pr: 0.4083
Epoch 29/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.2082 - binary_accuracy: 0.9248 - auc: 0.8559 - pr: 0.4514 - val_loss: 0.2197 - val_binary_accuracy: 0.9229 - val_auc: 0.8355 - val_pr: 0.4077
Epoch 30/1000
641/641 [==============================] - 210s 320ms/step - loss: 0.2076 - binary_accuracy: 0.9249 - auc: 0.8572 - pr: 0.4534 - val_loss: 0.2198 - val_binary_accuracy: 0.9226 - val_auc: 0.8359 - val_pr: 0.4078
Epoch 31/1000
641/641 [==============================] - 221s 339ms/step - loss: 0.2070 - binary_accuracy: 0.9250 - auc: 0.8582 - pr: 0.4557 - val_loss: 0.2182 - val_binary_accuracy: 0.9227 - val_auc: 0.8378 - val_pr: 0.4111
Epoch 32/1000
641/641 [==============================] - 224s 344ms/step - loss: 0.2067 - binary_accuracy: 0.9250 - auc: 0.8591 - pr: 0.4567 - val_loss: 0.2187 - val_binary_accuracy: 0.9226 - val_auc: 0.8368 - val_pr: 0.4065
Epoch 33/1000
641/641 [==============================] - 223s 339ms/step - loss: 0.2060 - binary_accuracy: 0.9252 - auc: 0.8602 - pr: 0.4594 - val_loss: 0.2178 - val_binary_accuracy: 0.9229 - val_auc: 0.8376 - val_pr: 0.4093
Epoch 34/1000
641/641 [==============================] - 224s 343ms/step - loss: 0.2056 - binary_accuracy: 0.9253 - auc: 0.8610 - pr: 0.4608 - val_loss: 0.2176 - val_binary_accuracy: 0.9227 - val_auc: 0.8381 - val_pr: 0.4101
Epoch 35/1000
641/641 [==============================] - 222s 343ms/step - loss: 0.2053 - binary_accuracy: 0.9253 - auc: 0.8618 - pr: 0.4615 - val_loss: 0.2178 - val_binary_accuracy: 0.9225 - val_auc: 0.8381 - val_pr: 0.4092
Epoch 36/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.2048 - binary_accuracy: 0.9254 - auc: 0.8627 - pr: 0.4634 - val_loss: 0.2196 - val_binary_accuracy: 0.9227 - val_auc: 0.8364 - val_pr: 0.4069
Epoch 37/1000
641/641 [==============================] - 207s 318ms/step - loss: 0.2043 - binary_accuracy: 0.9255 - auc: 0.8637 - pr: 0.4650 - val_loss: 0.2205 - val_binary_accuracy: 0.9225 - val_auc: 0.8372 - val_pr: 0.4072
Epoch 38/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.2041 - binary_accuracy: 0.9254 - auc: 0.8644 - pr: 0.4656 - val_loss: 0.2177 - val_binary_accuracy: 0.9232 - val_auc: 0.8384 - val_pr: 0.4118
Epoch 39/1000
641/641 [==============================] - 219s 333ms/step - loss: 0.2039 - binary_accuracy: 0.9255 - auc: 0.8646 - pr: 0.4664 - val_loss: 0.2194 - val_binary_accuracy: 0.9222 - val_auc: 0.8366 - val_pr: 0.4031
Epoch 40/1000
641/641 [==============================] - 221s 342ms/step - loss: 0.2036 - binary_accuracy: 0.9256 - auc: 0.8651 - pr: 0.4676 - val_loss: 0.2190 - val_binary_accuracy: 0.9226 - val_auc: 0.8377 - val_pr: 0.4059
Epoch 41/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.2031 - binary_accuracy: 0.9257 - auc: 0.8661 - pr: 0.4693 - val_loss: 0.2186 - val_binary_accuracy: 0.9228 - val_auc: 0.8379 - val_pr: 0.4097
Epoch 42/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.2027 - binary_accuracy: 0.9258 - auc: 0.8670 - pr: 0.4715 - val_loss: 0.2199 - val_binary_accuracy: 0.9224 - val_auc: 0.8372 - val_pr: 0.4049
Epoch 43/1000
641/641 [==============================] - 226s 346ms/step - loss: 0.2025 - binary_accuracy: 0.9258 - auc: 0.8675 - pr: 0.4716 - val_loss: 0.2185 - val_binary_accuracy: 0.9230 - val_auc: 0.8388 - val_pr: 0.4125
Epoch 44/1000
641/641 [==============================] - 222s 344ms/step - loss: 0.2021 - binary_accuracy: 0.9260 - auc: 0.8681 - pr: 0.4733 - val_loss: 0.2201 - val_binary_accuracy: 0.9229 - val_auc: 0.8377 - val_pr: 0.4093
Epoch 45/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.2020 - binary_accuracy: 0.9259 - auc: 0.8683 - pr: 0.4732 - val_loss: 0.2187 - val_binary_accuracy: 0.9230 - val_auc: 0.8371 - val_pr: 0.4082
Epoch 46/1000
641/641 [==============================] - 224s 341ms/step - loss: 0.2016 - binary_accuracy: 0.9260 - auc: 0.8691 - pr: 0.4748 - val_loss: 0.2190 - val_binary_accuracy: 0.9230 - val_auc: 0.8377 - val_pr: 0.4105
Epoch 47/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.2014 - binary_accuracy: 0.9260 - auc: 0.8696 - pr: 0.4758 - val_loss: 0.2194 - val_binary_accuracy: 0.9230 - val_auc: 0.8383 - val_pr: 0.4106
Epoch 48/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.2009 - binary_accuracy: 0.9262 - auc: 0.8705 - pr: 0.4774 - val_loss: 0.2175 - val_binary_accuracy: 0.9231 - val_auc: 0.8388 - val_pr: 0.4128
Epoch 49/1000
641/641 [==============================] - 221s 340ms/step - loss: 0.2010 - binary_accuracy: 0.9261 - auc: 0.8705 - pr: 0.4768 - val_loss: 0.2212 - val_binary_accuracy: 0.9224 - val_auc: 0.8369 - val_pr: 0.4044
Epoch 50/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.2007 - binary_accuracy: 0.9261 - auc: 0.8712 - pr: 0.4773 - val_loss: 0.2187 - val_binary_accuracy: 0.9228 - val_auc: 0.8370 - val_pr: 0.4070
Epoch 51/1000
641/641 [==============================] - 227s 351ms/step - loss: 0.2004 - binary_accuracy: 0.9261 - auc: 0.8716 - pr: 0.4784 - val_loss: 0.2207 - val_binary_accuracy: 0.9227 - val_auc: 0.8370 - val_pr: 0.4064
Epoch 52/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.2003 - binary_accuracy: 0.9262 - auc: 0.8720 - pr: 0.4789 - val_loss: 0.2183 - val_binary_accuracy: 0.9229 - val_auc: 0.8379 - val_pr: 0.4126
Epoch 53/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1998 - binary_accuracy: 0.9263 - auc: 0.8728 - pr: 0.4807 - val_loss: 0.2192 - val_binary_accuracy: 0.9230 - val_auc: 0.8381 - val_pr: 0.4100
Epoch 54/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1999 - binary_accuracy: 0.9262 - auc: 0.8729 - pr: 0.4800 - val_loss: 0.2185 - val_binary_accuracy: 0.9231 - val_auc: 0.8384 - val_pr: 0.4102
Epoch 55/1000
641/641 [==============================] - 220s 341ms/step - loss: 0.1994 - binary_accuracy: 0.9264 - auc: 0.8737 - pr: 0.4824 - val_loss: 0.2212 - val_binary_accuracy: 0.9221 - val_auc: 0.8358 - val_pr: 0.4029
Epoch 56/1000
641/641 [==============================] - 228s 352ms/step - loss: 0.1993 - binary_accuracy: 0.9263 - auc: 0.8740 - pr: 0.4818 - val_loss: 0.2197 - val_binary_accuracy: 0.9228 - val_auc: 0.8378 - val_pr: 0.4088
Epoch 57/1000
641/641 [==============================] - 228s 353ms/step - loss: 0.1990 - binary_accuracy: 0.9265 - auc: 0.8746 - pr: 0.4835 - val_loss: 0.2197 - val_binary_accuracy: 0.9228 - val_auc: 0.8379 - val_pr: 0.4083
Epoch 58/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1988 - binary_accuracy: 0.9265 - auc: 0.8748 - pr: 0.4837 - val_loss: 0.2202 - val_binary_accuracy: 0.9226 - val_auc: 0.8378 - val_pr: 0.4081
Epoch 59/1000
641/641 [==============================] - 216s 328ms/step - loss: 0.1989 - binary_accuracy: 0.9264 - auc: 0.8749 - pr: 0.4836 - val_loss: 0.2188 - val_binary_accuracy: 0.9231 - val_auc: 0.8392 - val_pr: 0.4126
Epoch 60/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1984 - binary_accuracy: 0.9266 - auc: 0.8757 - pr: 0.4855 - val_loss: 0.2199 - val_binary_accuracy: 0.9228 - val_auc: 0.8383 - val_pr: 0.4096
Epoch 61/1000
641/641 [==============================] - 227s 351ms/step - loss: 0.1983 - binary_accuracy: 0.9266 - auc: 0.8759 - pr: 0.4856 - val_loss: 0.2179 - val_binary_accuracy: 0.9227 - val_auc: 0.8398 - val_pr: 0.4152
Epoch 62/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1982 - binary_accuracy: 0.9266 - auc: 0.8762 - pr: 0.4858 - val_loss: 0.2175 - val_binary_accuracy: 0.9233 - val_auc: 0.8397 - val_pr: 0.4142
Epoch 63/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1979 - binary_accuracy: 0.9266 - auc: 0.8767 - pr: 0.4868 - val_loss: 0.2182 - val_binary_accuracy: 0.9232 - val_auc: 0.8391 - val_pr: 0.4127
Epoch 64/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1977 - binary_accuracy: 0.9267 - auc: 0.8772 - pr: 0.4876 - val_loss: 0.2174 - val_binary_accuracy: 0.9234 - val_auc: 0.8394 - val_pr: 0.4151
Epoch 65/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1976 - binary_accuracy: 0.9266 - auc: 0.8774 - pr: 0.4878 - val_loss: 0.2178 - val_binary_accuracy: 0.9233 - val_auc: 0.8386 - val_pr: 0.4133
Epoch 66/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1975 - binary_accuracy: 0.9266 - auc: 0.8777 - pr: 0.4878 - val_loss: 0.2204 - val_binary_accuracy: 0.9228 - val_auc: 0.8393 - val_pr: 0.4109
Epoch 67/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1973 - binary_accuracy: 0.9267 - auc: 0.8781 - pr: 0.4887 - val_loss: 0.2182 - val_binary_accuracy: 0.9231 - val_auc: 0.8394 - val_pr: 0.4121
Epoch 68/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1973 - binary_accuracy: 0.9267 - auc: 0.8781 - pr: 0.4888 - val_loss: 0.2221 - val_binary_accuracy: 0.9229 - val_auc: 0.8368 - val_pr: 0.4086
Epoch 69/1000
641/641 [==============================] - 214s 325ms/step - loss: 0.1969 - binary_accuracy: 0.9268 - auc: 0.8788 - pr: 0.4903 - val_loss: 0.2198 - val_binary_accuracy: 0.9229 - val_auc: 0.8367 - val_pr: 0.4076
Epoch 70/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.1968 - binary_accuracy: 0.9268 - auc: 0.8791 - pr: 0.4906 - val_loss: 0.2184 - val_binary_accuracy: 0.9234 - val_auc: 0.8391 - val_pr: 0.4149
Epoch 71/1000
641/641 [==============================] - 216s 331ms/step - loss: 0.1967 - binary_accuracy: 0.9268 - auc: 0.8794 - pr: 0.4904 - val_loss: 0.2183 - val_binary_accuracy: 0.9231 - val_auc: 0.8391 - val_pr: 0.4129
Epoch 72/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1965 - binary_accuracy: 0.9268 - auc: 0.8797 - pr: 0.4915 - val_loss: 0.2192 - val_binary_accuracy: 0.9232 - val_auc: 0.8389 - val_pr: 0.4126
Epoch 73/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1963 - binary_accuracy: 0.9269 - auc: 0.8800 - pr: 0.4920 - val_loss: 0.2201 - val_binary_accuracy: 0.9227 - val_auc: 0.8377 - val_pr: 0.4107
Epoch 74/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1963 - binary_accuracy: 0.9269 - auc: 0.8802 - pr: 0.4915 - val_loss: 0.2204 - val_binary_accuracy: 0.9228 - val_auc: 0.8377 - val_pr: 0.4108
Epoch 75/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1961 - binary_accuracy: 0.9269 - auc: 0.8804 - pr: 0.4923 - val_loss: 0.2185 - val_binary_accuracy: 0.9231 - val_auc: 0.8388 - val_pr: 0.4125
Epoch 76/1000
641/641 [==============================] - 208s 318ms/step - loss: 0.1961 - binary_accuracy: 0.9268 - auc: 0.8806 - pr: 0.4923 - val_loss: 0.2197 - val_binary_accuracy: 0.9231 - val_auc: 0.8390 - val_pr: 0.4120
Epoch 77/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1958 - binary_accuracy: 0.9269 - auc: 0.8810 - pr: 0.4933 - val_loss: 0.2176 - val_binary_accuracy: 0.9231 - val_auc: 0.8391 - val_pr: 0.4149
Epoch 78/1000
641/641 [==============================] - 221s 339ms/step - loss: 0.1958 - binary_accuracy: 0.9269 - auc: 0.8812 - pr: 0.4933 - val_loss: 0.2195 - val_binary_accuracy: 0.9232 - val_auc: 0.8389 - val_pr: 0.4138
Epoch 79/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1956 - binary_accuracy: 0.9269 - auc: 0.8815 - pr: 0.4939 - val_loss: 0.2188 - val_binary_accuracy: 0.9233 - val_auc: 0.8387 - val_pr: 0.4138
Epoch 80/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1955 - binary_accuracy: 0.9269 - auc: 0.8817 - pr: 0.4940 - val_loss: 0.2180 - val_binary_accuracy: 0.9232 - val_auc: 0.8390 - val_pr: 0.4132
Epoch 81/1000
641/641 [==============================] - 206s 315ms/step - loss: 0.1953 - binary_accuracy: 0.9270 - auc: 0.8820 - pr: 0.4949 - val_loss: 0.2183 - val_binary_accuracy: 0.9231 - val_auc: 0.8388 - val_pr: 0.4138
Epoch 82/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1953 - binary_accuracy: 0.9270 - auc: 0.8822 - pr: 0.4947 - val_loss: 0.2195 - val_binary_accuracy: 0.9233 - val_auc: 0.8391 - val_pr: 0.4146
Epoch 83/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1952 - binary_accuracy: 0.9270 - auc: 0.8823 - pr: 0.4952 - val_loss: 0.2209 - val_binary_accuracy: 0.9231 - val_auc: 0.8382 - val_pr: 0.4127
Epoch 84/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1950 - binary_accuracy: 0.9270 - auc: 0.8826 - pr: 0.4956 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8385 - val_pr: 0.4131
Epoch 85/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1950 - binary_accuracy: 0.9270 - auc: 0.8828 - pr: 0.4955 - val_loss: 0.2190 - val_binary_accuracy: 0.9230 - val_auc: 0.8386 - val_pr: 0.4123
Epoch 86/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1948 - binary_accuracy: 0.9270 - auc: 0.8830 - pr: 0.4961 - val_loss: 0.2186 - val_binary_accuracy: 0.9231 - val_auc: 0.8380 - val_pr: 0.4093
Epoch 87/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1947 - binary_accuracy: 0.9271 - auc: 0.8833 - pr: 0.4965 - val_loss: 0.2198 - val_binary_accuracy: 0.9230 - val_auc: 0.8371 - val_pr: 0.4091
Epoch 88/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1947 - binary_accuracy: 0.9271 - auc: 0.8832 - pr: 0.4962 - val_loss: 0.2208 - val_binary_accuracy: 0.9227 - val_auc: 0.8376 - val_pr: 0.4101
Epoch 89/1000
641/641 [==============================] - 202s 312ms/step - loss: 0.1947 - binary_accuracy: 0.9270 - auc: 0.8833 - pr: 0.4960 - val_loss: 0.2213 - val_binary_accuracy: 0.9225 - val_auc: 0.8376 - val_pr: 0.4085
Epoch 90/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1946 - binary_accuracy: 0.9271 - auc: 0.8835 - pr: 0.4970 - val_loss: 0.2199 - val_binary_accuracy: 0.9228 - val_auc: 0.8386 - val_pr: 0.4113
Epoch 91/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1943 - binary_accuracy: 0.9271 - auc: 0.8840 - pr: 0.4975 - val_loss: 0.2192 - val_binary_accuracy: 0.9232 - val_auc: 0.8387 - val_pr: 0.4124
Epoch 92/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1944 - binary_accuracy: 0.9271 - auc: 0.8840 - pr: 0.4971 - val_loss: 0.2200 - val_binary_accuracy: 0.9230 - val_auc: 0.8384 - val_pr: 0.4114
Epoch 93/1000
641/641 [==============================] - 204s 310ms/step - loss: 0.1942 - binary_accuracy: 0.9271 - auc: 0.8844 - pr: 0.4976 - val_loss: 0.2192 - val_binary_accuracy: 0.9233 - val_auc: 0.8394 - val_pr: 0.4154
Epoch 94/1000
641/641 [==============================] - 204s 313ms/step - loss: 0.1940 - binary_accuracy: 0.9272 - auc: 0.8847 - pr: 0.4986 - val_loss: 0.2208 - val_binary_accuracy: 0.9230 - val_auc: 0.8380 - val_pr: 0.4119
Epoch 95/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1941 - binary_accuracy: 0.9271 - auc: 0.8845 - pr: 0.4982 - val_loss: 0.2189 - val_binary_accuracy: 0.9233 - val_auc: 0.8394 - val_pr: 0.4138
Epoch 96/1000
641/641 [==============================] - 216s 330ms/step - loss: 0.1940 - binary_accuracy: 0.9271 - auc: 0.8848 - pr: 0.4982 - val_loss: 0.2205 - val_binary_accuracy: 0.9230 - val_auc: 0.8384 - val_pr: 0.4126
Epoch 97/1000
641/641 [==============================] - 206s 317ms/step - loss: 0.1938 - binary_accuracy: 0.9272 - auc: 0.8850 - pr: 0.4993 - val_loss: 0.2187 - val_binary_accuracy: 0.9231 - val_auc: 0.8385 - val_pr: 0.4129
Epoch 98/1000
641/641 [==============================] - 205s 317ms/step - loss: 0.1937 - binary_accuracy: 0.9272 - auc: 0.8852 - pr: 0.4992 - val_loss: 0.2182 - val_binary_accuracy: 0.9233 - val_auc: 0.8392 - val_pr: 0.4151
Epoch 99/1000
641/641 [==============================] - 200s 305ms/step - loss: 0.1937 - binary_accuracy: 0.9271 - auc: 0.8852 - pr: 0.4991 - val_loss: 0.2186 - val_binary_accuracy: 0.9234 - val_auc: 0.8397 - val_pr: 0.4150
Epoch 100/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1937 - binary_accuracy: 0.9272 - auc: 0.8853 - pr: 0.4991 - val_loss: 0.2192 - val_binary_accuracy: 0.9230 - val_auc: 0.8395 - val_pr: 0.4150
Epoch 101/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1937 - binary_accuracy: 0.9272 - auc: 0.8853 - pr: 0.4993 - val_loss: 0.2199 - val_binary_accuracy: 0.9229 - val_auc: 0.8390 - val_pr: 0.4122
Epoch 102/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1935 - binary_accuracy: 0.9272 - auc: 0.8856 - pr: 0.4995 - val_loss: 0.2203 - val_binary_accuracy: 0.9230 - val_auc: 0.8386 - val_pr: 0.4129
Epoch 103/1000
641/641 [==============================] - 219s 337ms/step - loss: 0.1935 - binary_accuracy: 0.9272 - auc: 0.8858 - pr: 0.4999 - val_loss: 0.2204 - val_binary_accuracy: 0.9231 - val_auc: 0.8386 - val_pr: 0.4129
Epoch 104/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1933 - binary_accuracy: 0.9273 - auc: 0.8860 - pr: 0.5007 - val_loss: 0.2189 - val_binary_accuracy: 0.9234 - val_auc: 0.8387 - val_pr: 0.4138
Epoch 105/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1933 - binary_accuracy: 0.9273 - auc: 0.8861 - pr: 0.5006 - val_loss: 0.2191 - val_binary_accuracy: 0.9231 - val_auc: 0.8374 - val_pr: 0.4108
Epoch 106/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1933 - binary_accuracy: 0.9272 - auc: 0.8862 - pr: 0.5003 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8389 - val_pr: 0.4142
Epoch 107/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1932 - binary_accuracy: 0.9273 - auc: 0.8863 - pr: 0.5007 - val_loss: 0.2211 - val_binary_accuracy: 0.9233 - val_auc: 0.8388 - val_pr: 0.4147
Epoch 108/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1932 - binary_accuracy: 0.9273 - auc: 0.8863 - pr: 0.5006 - val_loss: 0.2196 - val_binary_accuracy: 0.9233 - val_auc: 0.8392 - val_pr: 0.4141
Epoch 109/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1930 - binary_accuracy: 0.9273 - auc: 0.8867 - pr: 0.5011 - val_loss: 0.2192 - val_binary_accuracy: 0.9234 - val_auc: 0.8394 - val_pr: 0.4139
Epoch 110/1000
641/641 [==============================] - 208s 322ms/step - loss: 0.1930 - binary_accuracy: 0.9273 - auc: 0.8867 - pr: 0.5014 - val_loss: 0.2190 - val_binary_accuracy: 0.9231 - val_auc: 0.8387 - val_pr: 0.4115
Epoch 111/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1929 - binary_accuracy: 0.9273 - auc: 0.8868 - pr: 0.5017 - val_loss: 0.2198 - val_binary_accuracy: 0.9232 - val_auc: 0.8385 - val_pr: 0.4124
Epoch 112/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1928 - binary_accuracy: 0.9273 - auc: 0.8869 - pr: 0.5018 - val_loss: 0.2208 - val_binary_accuracy: 0.9225 - val_auc: 0.8378 - val_pr: 0.4094
Epoch 113/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1927 - binary_accuracy: 0.9274 - auc: 0.8871 - pr: 0.5021 - val_loss: 0.2187 - val_binary_accuracy: 0.9231 - val_auc: 0.8390 - val_pr: 0.4134
Epoch 114/1000
641/641 [==============================] - 208s 319ms/step - loss: 0.1928 - binary_accuracy: 0.9273 - auc: 0.8871 - pr: 0.5021 - val_loss: 0.2184 - val_binary_accuracy: 0.9233 - val_auc: 0.8392 - val_pr: 0.4138
Epoch 115/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1927 - binary_accuracy: 0.9273 - auc: 0.8872 - pr: 0.5020 - val_loss: 0.2204 - val_binary_accuracy: 0.9231 - val_auc: 0.8379 - val_pr: 0.4130
Epoch 116/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1928 - binary_accuracy: 0.9273 - auc: 0.8871 - pr: 0.5019 - val_loss: 0.2223 - val_binary_accuracy: 0.9228 - val_auc: 0.8371 - val_pr: 0.4097
Epoch 117/1000
641/641 [==============================] - 208s 322ms/step - loss: 0.1927 - binary_accuracy: 0.9273 - auc: 0.8873 - pr: 0.5023 - val_loss: 0.2193 - val_binary_accuracy: 0.9232 - val_auc: 0.8387 - val_pr: 0.4137
Epoch 118/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1926 - binary_accuracy: 0.9274 - auc: 0.8874 - pr: 0.5023 - val_loss: 0.2195 - val_binary_accuracy: 0.9232 - val_auc: 0.8387 - val_pr: 0.4146
Epoch 119/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1925 - binary_accuracy: 0.9274 - auc: 0.8876 - pr: 0.5029 - val_loss: 0.2184 - val_binary_accuracy: 0.9233 - val_auc: 0.8393 - val_pr: 0.4145
Epoch 120/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1925 - binary_accuracy: 0.9273 - auc: 0.8877 - pr: 0.5024 - val_loss: 0.2185 - val_binary_accuracy: 0.9232 - val_auc: 0.8389 - val_pr: 0.4132
Epoch 121/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1924 - binary_accuracy: 0.9274 - auc: 0.8878 - pr: 0.5029 - val_loss: 0.2203 - val_binary_accuracy: 0.9229 - val_auc: 0.8379 - val_pr: 0.4129
Epoch 122/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1924 - binary_accuracy: 0.9274 - auc: 0.8878 - pr: 0.5027 - val_loss: 0.2189 - val_binary_accuracy: 0.9234 - val_auc: 0.8394 - val_pr: 0.4157
Epoch 123/1000
641/641 [==============================] - 205s 317ms/step - loss: 0.1923 - binary_accuracy: 0.9274 - auc: 0.8880 - pr: 0.5033 - val_loss: 0.2179 - val_binary_accuracy: 0.9235 - val_auc: 0.8391 - val_pr: 0.4158
Epoch 124/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1924 - binary_accuracy: 0.9274 - auc: 0.8879 - pr: 0.5028 - val_loss: 0.2193 - val_binary_accuracy: 0.9231 - val_auc: 0.8383 - val_pr: 0.4138
Epoch 125/1000
641/641 [==============================] - 207s 317ms/step - loss: 0.1923 - binary_accuracy: 0.9274 - auc: 0.8881 - pr: 0.5033 - val_loss: 0.2199 - val_binary_accuracy: 0.9229 - val_auc: 0.8378 - val_pr: 0.4112
Epoch 126/1000
641/641 [==============================] - 208s 319ms/step - loss: 0.1921 - binary_accuracy: 0.9274 - auc: 0.8883 - pr: 0.5039 - val_loss: 0.2192 - val_binary_accuracy: 0.9234 - val_auc: 0.8386 - val_pr: 0.4156
Epoch 127/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1921 - binary_accuracy: 0.9274 - auc: 0.8884 - pr: 0.5039 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8382 - val_pr: 0.4137
Epoch 128/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1921 - binary_accuracy: 0.9274 - auc: 0.8884 - pr: 0.5038 - val_loss: 0.2199 - val_binary_accuracy: 0.9232 - val_auc: 0.8379 - val_pr: 0.4134
Epoch 129/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1920 - binary_accuracy: 0.9274 - auc: 0.8885 - pr: 0.5042 - val_loss: 0.2201 - val_binary_accuracy: 0.9229 - val_auc: 0.8381 - val_pr: 0.4119
Epoch 130/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1920 - binary_accuracy: 0.9274 - auc: 0.8885 - pr: 0.5039 - val_loss: 0.2193 - val_binary_accuracy: 0.9232 - val_auc: 0.8382 - val_pr: 0.4144
Epoch 131/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1920 - binary_accuracy: 0.9274 - auc: 0.8886 - pr: 0.5039 - val_loss: 0.2194 - val_binary_accuracy: 0.9233 - val_auc: 0.8380 - val_pr: 0.4142
Epoch 132/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1920 - binary_accuracy: 0.9274 - auc: 0.8885 - pr: 0.5040 - val_loss: 0.2200 - val_binary_accuracy: 0.9231 - val_auc: 0.8372 - val_pr: 0.4113
Epoch 133/1000
641/641 [==============================] - 219s 337ms/step - loss: 0.1919 - binary_accuracy: 0.9275 - auc: 0.8887 - pr: 0.5043 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8386 - val_pr: 0.4152
Epoch 134/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1918 - binary_accuracy: 0.9275 - auc: 0.8889 - pr: 0.5046 - val_loss: 0.2200 - val_binary_accuracy: 0.9230 - val_auc: 0.8372 - val_pr: 0.4119
Epoch 135/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1919 - binary_accuracy: 0.9274 - auc: 0.8888 - pr: 0.5043 - val_loss: 0.2196 - val_binary_accuracy: 0.9233 - val_auc: 0.8381 - val_pr: 0.4140
Epoch 136/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1918 - binary_accuracy: 0.9275 - auc: 0.8889 - pr: 0.5044 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8389 - val_pr: 0.4163
Epoch 137/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1917 - binary_accuracy: 0.9275 - auc: 0.8890 - pr: 0.5051 - val_loss: 0.2201 - val_binary_accuracy: 0.9232 - val_auc: 0.8373 - val_pr: 0.4131
Epoch 138/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1917 - binary_accuracy: 0.9275 - auc: 0.8891 - pr: 0.5051 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4148
Epoch 139/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1917 - binary_accuracy: 0.9275 - auc: 0.8891 - pr: 0.5047 - val_loss: 0.2190 - val_binary_accuracy: 0.9233 - val_auc: 0.8374 - val_pr: 0.4133
Epoch 140/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1916 - binary_accuracy: 0.9275 - auc: 0.8892 - pr: 0.5051 - val_loss: 0.2192 - val_binary_accuracy: 0.9233 - val_auc: 0.8381 - val_pr: 0.4145
Epoch 141/1000
641/641 [==============================] - 212s 321ms/step - loss: 0.1917 - binary_accuracy: 0.9275 - auc: 0.8891 - pr: 0.5047 - val_loss: 0.2190 - val_binary_accuracy: 0.9233 - val_auc: 0.8380 - val_pr: 0.4147
Epoch 142/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1917 - binary_accuracy: 0.9275 - auc: 0.8891 - pr: 0.5050 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4133
Epoch 143/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1916 - binary_accuracy: 0.9275 - auc: 0.8894 - pr: 0.5052 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4153
Epoch 144/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1916 - binary_accuracy: 0.9275 - auc: 0.8893 - pr: 0.5054 - val_loss: 0.2212 - val_binary_accuracy: 0.9232 - val_auc: 0.8370 - val_pr: 0.4134
Epoch 145/1000
641/641 [==============================] - 208s 316ms/step - loss: 0.1916 - binary_accuracy: 0.9275 - auc: 0.8894 - pr: 0.5055 - val_loss: 0.2196 - val_binary_accuracy: 0.9233 - val_auc: 0.8379 - val_pr: 0.4145
Epoch 146/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1915 - binary_accuracy: 0.9275 - auc: 0.8895 - pr: 0.5053 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 147/1000
641/641 [==============================] - 209s 318ms/step - loss: 0.1915 - binary_accuracy: 0.9275 - auc: 0.8894 - pr: 0.5055 - val_loss: 0.2189 - val_binary_accuracy: 0.9234 - val_auc: 0.8386 - val_pr: 0.4155
Epoch 148/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1915 - binary_accuracy: 0.9275 - auc: 0.8895 - pr: 0.5053 - val_loss: 0.2220 - val_binary_accuracy: 0.9231 - val_auc: 0.8368 - val_pr: 0.4137
Epoch 149/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1914 - binary_accuracy: 0.9275 - auc: 0.8896 - pr: 0.5056 - val_loss: 0.2211 - val_binary_accuracy: 0.9230 - val_auc: 0.8365 - val_pr: 0.4126
Epoch 150/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1914 - binary_accuracy: 0.9275 - auc: 0.8896 - pr: 0.5056 - val_loss: 0.2192 - val_binary_accuracy: 0.9233 - val_auc: 0.8391 - val_pr: 0.4168
Epoch 151/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1914 - binary_accuracy: 0.9275 - auc: 0.8897 - pr: 0.5058 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4162
Epoch 152/1000
641/641 [==============================] - 204s 314ms/step - loss: 0.1913 - binary_accuracy: 0.9275 - auc: 0.8898 - pr: 0.5062 - val_loss: 0.2213 - val_binary_accuracy: 0.9232 - val_auc: 0.8374 - val_pr: 0.4142
Epoch 153/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1913 - binary_accuracy: 0.9275 - auc: 0.8898 - pr: 0.5060 - val_loss: 0.2186 - val_binary_accuracy: 0.9233 - val_auc: 0.8385 - val_pr: 0.4154
Epoch 154/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1913 - binary_accuracy: 0.9275 - auc: 0.8898 - pr: 0.5060 - val_loss: 0.2196 - val_binary_accuracy: 0.9233 - val_auc: 0.8380 - val_pr: 0.4138
Epoch 155/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1913 - binary_accuracy: 0.9275 - auc: 0.8899 - pr: 0.5059 - val_loss: 0.2190 - val_binary_accuracy: 0.9234 - val_auc: 0.8386 - val_pr: 0.4152
Epoch 156/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1912 - binary_accuracy: 0.9276 - auc: 0.8900 - pr: 0.5063 - val_loss: 0.2188 - val_binary_accuracy: 0.9234 - val_auc: 0.8386 - val_pr: 0.4154
Epoch 157/1000
641/641 [==============================] - 216s 331ms/step - loss: 0.1912 - binary_accuracy: 0.9275 - auc: 0.8900 - pr: 0.5062 - val_loss: 0.2187 - val_binary_accuracy: 0.9234 - val_auc: 0.8382 - val_pr: 0.4159
Epoch 158/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1912 - binary_accuracy: 0.9275 - auc: 0.8900 - pr: 0.5063 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8380 - val_pr: 0.4141
Epoch 159/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1913 - binary_accuracy: 0.9275 - auc: 0.8900 - pr: 0.5060 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4140
Epoch 160/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1911 - binary_accuracy: 0.9276 - auc: 0.8901 - pr: 0.5066 - val_loss: 0.2205 - val_binary_accuracy: 0.9232 - val_auc: 0.8376 - val_pr: 0.4139
Epoch 161/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1912 - binary_accuracy: 0.9276 - auc: 0.8901 - pr: 0.5065 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8380 - val_pr: 0.4145
Epoch 162/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1912 - binary_accuracy: 0.9275 - auc: 0.8901 - pr: 0.5065 - val_loss: 0.2204 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4149
Epoch 163/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1911 - binary_accuracy: 0.9275 - auc: 0.8902 - pr: 0.5066 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8380 - val_pr: 0.4141
Epoch 164/1000
641/641 [==============================] - 223s 341ms/step - loss: 0.1911 - binary_accuracy: 0.9276 - auc: 0.8902 - pr: 0.5068 - val_loss: 0.2206 - val_binary_accuracy: 0.9232 - val_auc: 0.8371 - val_pr: 0.4120
Epoch 165/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1911 - binary_accuracy: 0.9276 - auc: 0.8902 - pr: 0.5065 - val_loss: 0.2210 - val_binary_accuracy: 0.9233 - val_auc: 0.8376 - val_pr: 0.4149
Epoch 166/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8904 - pr: 0.5069 - val_loss: 0.2205 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4149
Epoch 167/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8904 - pr: 0.5068 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4152
Epoch 168/1000
641/641 [==============================] - 201s 310ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8904 - pr: 0.5069 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4140
Epoch 169/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8905 - pr: 0.5072 - val_loss: 0.2199 - val_binary_accuracy: 0.9233 - val_auc: 0.8375 - val_pr: 0.4136
Epoch 170/1000
641/641 [==============================] - 222s 342ms/step - loss: 0.1909 - binary_accuracy: 0.9276 - auc: 0.8906 - pr: 0.5072 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4134
Epoch 171/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8904 - pr: 0.5071 - val_loss: 0.2204 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4147
Epoch 172/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1910 - binary_accuracy: 0.9276 - auc: 0.8905 - pr: 0.5070 - val_loss: 0.2198 - val_binary_accuracy: 0.9233 - val_auc: 0.8381 - val_pr: 0.4144
Epoch 173/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1909 - binary_accuracy: 0.9276 - auc: 0.8906 - pr: 0.5074 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4138
Epoch 174/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8908 - pr: 0.5078 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4144
Epoch 175/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1909 - binary_accuracy: 0.9276 - auc: 0.8907 - pr: 0.5075 - val_loss: 0.2209 - val_binary_accuracy: 0.9233 - val_auc: 0.8370 - val_pr: 0.4136
Epoch 176/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8907 - pr: 0.5073 - val_loss: 0.2211 - val_binary_accuracy: 0.9230 - val_auc: 0.8369 - val_pr: 0.4118
Epoch 177/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8908 - pr: 0.5077 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8376 - val_pr: 0.4138
Epoch 178/1000
641/641 [==============================] - 210s 319ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8909 - pr: 0.5078 - val_loss: 0.2193 - val_binary_accuracy: 0.9233 - val_auc: 0.8377 - val_pr: 0.4141
Epoch 179/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8908 - pr: 0.5076 - val_loss: 0.2204 - val_binary_accuracy: 0.9233 - val_auc: 0.8375 - val_pr: 0.4130
Epoch 180/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1907 - binary_accuracy: 0.9277 - auc: 0.8909 - pr: 0.5081 - val_loss: 0.2206 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4149
Epoch 181/1000
641/641 [==============================] - 205s 315ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8909 - pr: 0.5077 - val_loss: 0.2207 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4143
Epoch 182/1000
641/641 [==============================] - 201s 310ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8908 - pr: 0.5074 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4153
Epoch 183/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1907 - binary_accuracy: 0.9277 - auc: 0.8909 - pr: 0.5079 - val_loss: 0.2205 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4136
Epoch 184/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1908 - binary_accuracy: 0.9276 - auc: 0.8909 - pr: 0.5073 - val_loss: 0.2203 - val_binary_accuracy: 0.9233 - val_auc: 0.8374 - val_pr: 0.4137
Epoch 185/1000
641/641 [==============================] - 211s 321ms/step - loss: 0.1907 - binary_accuracy: 0.9276 - auc: 0.8910 - pr: 0.5079 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4152
Epoch 186/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1906 - binary_accuracy: 0.9277 - auc: 0.8910 - pr: 0.5083 - val_loss: 0.2186 - val_binary_accuracy: 0.9234 - val_auc: 0.8385 - val_pr: 0.4150
Epoch 187/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1906 - binary_accuracy: 0.9277 - auc: 0.8910 - pr: 0.5081 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4151
Epoch 188/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1906 - binary_accuracy: 0.9277 - auc: 0.8912 - pr: 0.5084 - val_loss: 0.2193 - val_binary_accuracy: 0.9232 - val_auc: 0.8374 - val_pr: 0.4133
Epoch 189/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1906 - binary_accuracy: 0.9276 - auc: 0.8911 - pr: 0.5080 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4141
Epoch 190/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1906 - binary_accuracy: 0.9276 - auc: 0.8911 - pr: 0.5080 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4151
Epoch 191/1000
641/641 [==============================] - 207s 317ms/step - loss: 0.1906 - binary_accuracy: 0.9277 - auc: 0.8912 - pr: 0.5084 - val_loss: 0.2188 - val_binary_accuracy: 0.9236 - val_auc: 0.8385 - val_pr: 0.4164
Epoch 192/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1906 - binary_accuracy: 0.9277 - auc: 0.8912 - pr: 0.5083 - val_loss: 0.2207 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4153
Epoch 193/1000
641/641 [==============================] - 208s 318ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8912 - pr: 0.5084 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4161
Epoch 194/1000
641/641 [==============================] - 205s 317ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8912 - pr: 0.5084 - val_loss: 0.2211 - val_binary_accuracy: 0.9231 - val_auc: 0.8366 - val_pr: 0.4121
Epoch 195/1000
641/641 [==============================] - 213s 326ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8913 - pr: 0.5085 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4152
Epoch 196/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5087 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4155
Epoch 197/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8913 - pr: 0.5083 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4141
Epoch 198/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8913 - pr: 0.5087 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4146
Epoch 199/1000
641/641 [==============================] - 209s 318ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5085 - val_loss: 0.2212 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4144
Epoch 200/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5086 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4155
Epoch 201/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5088 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4142
Epoch 202/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1905 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5086 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4154
Epoch 203/1000
641/641 [==============================] - 206s 317ms/step - loss: 0.1904 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5088 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8378 - val_pr: 0.4141
Epoch 204/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1904 - binary_accuracy: 0.9277 - auc: 0.8914 - pr: 0.5089 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4148
Epoch 205/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5091 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4140
Epoch 206/1000
641/641 [==============================] - 214s 329ms/step - loss: 0.1904 - binary_accuracy: 0.9277 - auc: 0.8915 - pr: 0.5089 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4139
Epoch 207/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1904 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5089 - val_loss: 0.2190 - val_binary_accuracy: 0.9236 - val_auc: 0.8382 - val_pr: 0.4159
Epoch 208/1000
641/641 [==============================] - 208s 316ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5091 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4145
Epoch 209/1000
641/641 [==============================] - 202s 312ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5091 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4148
Epoch 210/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5092 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4150
Epoch 211/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8917 - pr: 0.5091 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4151
Epoch 212/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8917 - pr: 0.5089 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4158
Epoch 213/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5091 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4155
Epoch 214/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8917 - pr: 0.5094 - val_loss: 0.2204 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4152
Epoch 215/1000
641/641 [==============================] - 208s 316ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5093 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4164
Epoch 216/1000
641/641 [==============================] - 203s 314ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5091 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4154
Epoch 217/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8917 - pr: 0.5092 - val_loss: 0.2208 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 218/1000
641/641 [==============================] - 201s 310ms/step - loss: 0.1903 - binary_accuracy: 0.9277 - auc: 0.8916 - pr: 0.5088 - val_loss: 0.2205 - val_binary_accuracy: 0.9233 - val_auc: 0.8365 - val_pr: 0.4133
Epoch 219/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8919 - pr: 0.5094 - val_loss: 0.2191 - val_binary_accuracy: 0.9237 - val_auc: 0.8382 - val_pr: 0.4169
Epoch 220/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5096 - val_loss: 0.2182 - val_binary_accuracy: 0.9236 - val_auc: 0.8382 - val_pr: 0.4154
Epoch 221/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8919 - pr: 0.5096 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4145
Epoch 222/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5094 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4157
Epoch 223/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5096 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4152
Epoch 224/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5094 - val_loss: 0.2207 - val_binary_accuracy: 0.9231 - val_auc: 0.8369 - val_pr: 0.4130
Epoch 225/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8919 - pr: 0.5096 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4158
Epoch 226/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1901 - binary_accuracy: 0.9278 - auc: 0.8919 - pr: 0.5100 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4150
Epoch 227/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5094 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 228/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1902 - binary_accuracy: 0.9277 - auc: 0.8918 - pr: 0.5093 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4153
Epoch 229/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1901 - binary_accuracy: 0.9278 - auc: 0.8920 - pr: 0.5098 - val_loss: 0.2187 - val_binary_accuracy: 0.9235 - val_auc: 0.8384 - val_pr: 0.4170
Epoch 230/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8919 - pr: 0.5097 - val_loss: 0.2202 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4148
Epoch 231/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8920 - pr: 0.5097 - val_loss: 0.2199 - val_binary_accuracy: 0.9233 - val_auc: 0.8378 - val_pr: 0.4145
Epoch 232/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1901 - binary_accuracy: 0.9278 - auc: 0.8920 - pr: 0.5100 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 233/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8920 - pr: 0.5098 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 234/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8921 - pr: 0.5099 - val_loss: 0.2186 - val_binary_accuracy: 0.9236 - val_auc: 0.8383 - val_pr: 0.4171
Epoch 235/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1901 - binary_accuracy: 0.9278 - auc: 0.8920 - pr: 0.5100 - val_loss: 0.2192 - val_binary_accuracy: 0.9236 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 236/1000
641/641 [==============================] - 225s 345ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8921 - pr: 0.5098 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4153
Epoch 237/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1901 - binary_accuracy: 0.9277 - auc: 0.8920 - pr: 0.5097 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8380 - val_pr: 0.4150
Epoch 238/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1901 - binary_accuracy: 0.9278 - auc: 0.8920 - pr: 0.5097 - val_loss: 0.2207 - val_binary_accuracy: 0.9234 - val_auc: 0.8369 - val_pr: 0.4138
Epoch 239/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8921 - pr: 0.5099 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4156
Epoch 240/1000
641/641 [==============================] - 219s 334ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8922 - pr: 0.5101 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4159
Epoch 241/1000
641/641 [==============================] - 207s 316ms/step - loss: 0.1900 - binary_accuracy: 0.9277 - auc: 0.8921 - pr: 0.5099 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4152
Epoch 242/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8921 - pr: 0.5098 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8380 - val_pr: 0.4157
Epoch 243/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8922 - pr: 0.5103 - val_loss: 0.2188 - val_binary_accuracy: 0.9236 - val_auc: 0.8384 - val_pr: 0.4167
Epoch 244/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5103 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8385 - val_pr: 0.4167
Epoch 245/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8922 - pr: 0.5100 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8381 - val_pr: 0.4153
Epoch 246/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8921 - pr: 0.5099 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4159
Epoch 247/1000
641/641 [==============================] - 208s 322ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8922 - pr: 0.5101 - val_loss: 0.2208 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4137
Epoch 248/1000
641/641 [==============================] - 217s 334ms/step - loss: 0.1900 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5102 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 249/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5104 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4154
Epoch 250/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5106 - val_loss: 0.2203 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4147
Epoch 251/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1899 - binary_accuracy: 0.9277 - auc: 0.8923 - pr: 0.5102 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4161
Epoch 252/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5103 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4155
Epoch 253/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5103 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4162
Epoch 254/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5104 - val_loss: 0.2200 - val_binary_accuracy: 0.9234 - val_auc: 0.8381 - val_pr: 0.4149
Epoch 255/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1900 - binary_accuracy: 0.9277 - auc: 0.8923 - pr: 0.5101 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 256/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5102 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4164
Epoch 257/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5104 - val_loss: 0.2203 - val_binary_accuracy: 0.9233 - val_auc: 0.8376 - val_pr: 0.4149
Epoch 258/1000
641/641 [==============================] - 210s 320ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5104 - val_loss: 0.2208 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4149
Epoch 259/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8923 - pr: 0.5103 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4158
Epoch 260/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5102 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4158
Epoch 261/1000
641/641 [==============================] - 213s 326ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5105 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4155
Epoch 262/1000
641/641 [==============================] - 217s 331ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5106 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4151
Epoch 263/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5104 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4156
Epoch 264/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5105 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4161
Epoch 265/1000
641/641 [==============================] - 213s 326ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5107 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 266/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5106 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8381 - val_pr: 0.4162
Epoch 267/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5103 - val_loss: 0.2200 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 268/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5107 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4151
Epoch 269/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5109 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4156
Epoch 270/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1899 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5104 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4155
Epoch 271/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5107 - val_loss: 0.2210 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4146
Epoch 272/1000
641/641 [==============================] - 210s 321ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8924 - pr: 0.5107 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4151
Epoch 273/1000
641/641 [==============================] - 222s 340ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5107 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4158
Epoch 274/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5107 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4152
Epoch 275/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8925 - pr: 0.5109 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4154
Epoch 276/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5107 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8385 - val_pr: 0.4155
Epoch 277/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5108 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4160
Epoch 278/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5109 - val_loss: 0.2202 - val_binary_accuracy: 0.9233 - val_auc: 0.8375 - val_pr: 0.4143
Epoch 279/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5110 - val_loss: 0.2183 - val_binary_accuracy: 0.9235 - val_auc: 0.8388 - val_pr: 0.4162
Epoch 280/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1898 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5108 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4154
Epoch 281/1000
641/641 [==============================] - 203s 313ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8926 - pr: 0.5112 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4151
Epoch 282/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5108 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4163
Epoch 283/1000
641/641 [==============================] - 219s 333ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5110 - val_loss: 0.2189 - val_binary_accuracy: 0.9236 - val_auc: 0.8381 - val_pr: 0.4163
Epoch 284/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5109 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4147
Epoch 285/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5108 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8380 - val_pr: 0.4153
Epoch 286/1000
641/641 [==============================] - 210s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5109 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4155
Epoch 287/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5108 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4148
Epoch 288/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2194 - val_binary_accuracy: 0.9237 - val_auc: 0.8380 - val_pr: 0.4168
Epoch 289/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2201 - val_binary_accuracy: 0.9236 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 290/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4156
Epoch 291/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4154
Epoch 292/1000
641/641 [==============================] - 206s 314ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4146
Epoch 293/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4162
Epoch 294/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5110 - val_loss: 0.2188 - val_binary_accuracy: 0.9236 - val_auc: 0.8383 - val_pr: 0.4166
Epoch 295/1000
641/641 [==============================] - 216s 330ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8383 - val_pr: 0.4166
Epoch 296/1000
641/641 [==============================] - 214s 326ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5112 - val_loss: 0.2206 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4148
Epoch 297/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5111 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 298/1000
641/641 [==============================] - 212s 322ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5111 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4165
Epoch 299/1000
641/641 [==============================] - 210s 320ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5110 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4145
Epoch 300/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5112 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 301/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5110 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4147
Epoch 302/1000
641/641 [==============================] - 217s 330ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5115 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4156
Epoch 303/1000
641/641 [==============================] - 210s 318ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5112 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4150
Epoch 304/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5111 - val_loss: 0.2191 - val_binary_accuracy: 0.9234 - val_auc: 0.8384 - val_pr: 0.4155
Epoch 305/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5114 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4156
Epoch 306/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5114 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8378 - val_pr: 0.4147
Epoch 307/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1897 - binary_accuracy: 0.9278 - auc: 0.8927 - pr: 0.5112 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8384 - val_pr: 0.4161
Epoch 308/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5113 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4153
Epoch 309/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5112 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4162
Epoch 310/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5114 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4161
Epoch 311/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5114 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4149
Epoch 312/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5112 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4163
Epoch 313/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5112 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4158
Epoch 314/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5113 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4149
Epoch 315/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8928 - pr: 0.5109 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4163
Epoch 316/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5114 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4159
Epoch 317/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5115 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4159
Epoch 318/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5115 - val_loss: 0.2189 - val_binary_accuracy: 0.9234 - val_auc: 0.8384 - val_pr: 0.4150
Epoch 319/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5113 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8378 - val_pr: 0.4153
Epoch 320/1000
641/641 [==============================] - 223s 344ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8929 - pr: 0.5114 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4152
Epoch 321/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 322/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1896 - binary_accuracy: 0.9279 - auc: 0.8929 - pr: 0.5116 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4156
Epoch 323/1000
641/641 [==============================] - 218s 334ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2200 - val_binary_accuracy: 0.9234 - val_auc: 0.8381 - val_pr: 0.4153
Epoch 324/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5117 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4158
Epoch 325/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8930 - pr: 0.5117 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4158
Epoch 326/1000
641/641 [==============================] - 216s 331ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4154
Epoch 327/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5115 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4141
Epoch 328/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.1896 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5114 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8385 - val_pr: 0.4164
Epoch 329/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8930 - pr: 0.5117 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4153
Epoch 330/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4160
Epoch 331/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5118 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4154
Epoch 332/1000
641/641 [==============================] - 225s 342ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5117 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8383 - val_pr: 0.4165
Epoch 333/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4146
Epoch 334/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5115 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4154
Epoch 335/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4161
Epoch 336/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5118 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4151
Epoch 337/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4153
Epoch 338/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 339/1000
641/641 [==============================] - 224s 343ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5118 - val_loss: 0.2189 - val_binary_accuracy: 0.9236 - val_auc: 0.8382 - val_pr: 0.4162
Epoch 340/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4159
Epoch 341/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5119 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4160
Epoch 342/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8384 - val_pr: 0.4169
Epoch 343/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1894 - binary_accuracy: 0.9278 - auc: 0.8932 - pr: 0.5118 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4163
Epoch 344/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5116 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4156
Epoch 345/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8930 - pr: 0.5115 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4152
Epoch 346/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1894 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5118 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4159
Epoch 347/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4164
Epoch 348/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5119 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4157
Epoch 349/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4163
Epoch 350/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5118 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4164
Epoch 351/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1895 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4157
Epoch 352/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5119 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4148
Epoch 353/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8931 - pr: 0.5119 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4154
Epoch 354/1000
641/641 [==============================] - 217s 331ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5120 - val_loss: 0.2185 - val_binary_accuracy: 0.9235 - val_auc: 0.8385 - val_pr: 0.4163
Epoch 355/1000
641/641 [==============================] - 220s 335ms/step - loss: 0.1894 - binary_accuracy: 0.9278 - auc: 0.8932 - pr: 0.5118 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8385 - val_pr: 0.4172
Epoch 356/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1894 - binary_accuracy: 0.9278 - auc: 0.8932 - pr: 0.5118 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8385 - val_pr: 0.4159
Epoch 357/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5119 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4158
Epoch 358/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8384 - val_pr: 0.4163
Epoch 359/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8384 - val_pr: 0.4164
Epoch 360/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4158
Epoch 361/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5120 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4159
Epoch 362/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5117 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4163
Epoch 363/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5122 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4161
Epoch 364/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5120 - val_loss: 0.2197 - val_binary_accuracy: 0.9236 - val_auc: 0.8377 - val_pr: 0.4164
Epoch 365/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1894 - binary_accuracy: 0.9278 - auc: 0.8932 - pr: 0.5118 - val_loss: 0.2185 - val_binary_accuracy: 0.9235 - val_auc: 0.8385 - val_pr: 0.4165
Epoch 366/1000
641/641 [==============================] - 214s 326ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5121 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4162
Epoch 367/1000
641/641 [==============================] - 216s 328ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5120 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4162
Epoch 368/1000
641/641 [==============================] - 209s 319ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5118 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4154
Epoch 369/1000
641/641 [==============================] - 221s 340ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5117 - val_loss: 0.2187 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4168
Epoch 370/1000
641/641 [==============================] - 217s 331ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5121 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4166
Epoch 371/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2192 - val_binary_accuracy: 0.9236 - val_auc: 0.8380 - val_pr: 0.4170
Epoch 372/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5121 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4157
Epoch 373/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2192 - val_binary_accuracy: 0.9234 - val_auc: 0.8381 - val_pr: 0.4157
Epoch 374/1000
641/641 [==============================] - 218s 333ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 375/1000
641/641 [==============================] - 220s 338ms/step - loss: 0.1895 - binary_accuracy: 0.9278 - auc: 0.8931 - pr: 0.5117 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4155
Epoch 376/1000
641/641 [==============================] - 221s 339ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5121 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 377/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4162
Epoch 378/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5121 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4159
Epoch 379/1000
641/641 [==============================] - 218s 332ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5122 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8383 - val_pr: 0.4170
Epoch 380/1000
641/641 [==============================] - 216s 329ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5119 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8383 - val_pr: 0.4173
Epoch 381/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8932 - pr: 0.5120 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4166
Epoch 382/1000
641/641 [==============================] - 214s 329ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5122 - val_loss: 0.2188 - val_binary_accuracy: 0.9236 - val_auc: 0.8384 - val_pr: 0.4165
Epoch 383/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5122 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8377 - val_pr: 0.4162
Epoch 384/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4151
Epoch 385/1000
641/641 [==============================] - 208s 322ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5120 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4154
Epoch 386/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5122 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4160
Epoch 387/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5120 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4164
Epoch 388/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4155
Epoch 389/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5122 - val_loss: 0.2186 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4158
Epoch 390/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5121 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4164
Epoch 391/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5121 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 392/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5121 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4163
Epoch 393/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5123 - val_loss: 0.2187 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4164
Epoch 394/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1894 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5120 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4162
Epoch 395/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4158
Epoch 396/1000
641/641 [==============================] - 202s 312ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5122 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4150
Epoch 397/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5122 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4152
Epoch 398/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4150
Epoch 399/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5123 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4158
Epoch 400/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5122 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4158
Epoch 401/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5123 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4157
Epoch 402/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5126 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4162
Epoch 403/1000
641/641 [==============================] - 204s 311ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8382 - val_pr: 0.4165
Epoch 404/1000
641/641 [==============================] - 210s 321ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8933 - pr: 0.5121 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4158
Epoch 405/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5125 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4166
Epoch 406/1000
641/641 [==============================] - 208s 322ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5123 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4167
Epoch 407/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5125 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4159
Epoch 408/1000
641/641 [==============================] - 203s 313ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5123 - val_loss: 0.2197 - val_binary_accuracy: 0.9236 - val_auc: 0.8377 - val_pr: 0.4155
Epoch 409/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4157
Epoch 410/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 411/1000
641/641 [==============================] - 209s 320ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4155
Epoch 412/1000
641/641 [==============================] - 204s 313ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8382 - val_pr: 0.4164
Epoch 413/1000
641/641 [==============================] - 210s 320ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4159
Epoch 414/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4162
Epoch 415/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5123 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4153
Epoch 416/1000
641/641 [==============================] - 220s 340ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5124 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4163
Epoch 417/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4160
Epoch 418/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5123 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4164
Epoch 419/1000
641/641 [==============================] - 213s 324ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4151
Epoch 420/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5125 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8380 - val_pr: 0.4162
Epoch 421/1000
641/641 [==============================] - 216s 329ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2191 - val_binary_accuracy: 0.9236 - val_auc: 0.8380 - val_pr: 0.4159
Epoch 422/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4156
Epoch 423/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4152
Epoch 424/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5127 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4157
Epoch 425/1000
641/641 [==============================] - 213s 326ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4163
Epoch 426/1000
641/641 [==============================] - 201s 305ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5124 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4160
Epoch 427/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4149
Epoch 428/1000
641/641 [==============================] - 213s 324ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5122 - val_loss: 0.2197 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4153
Epoch 429/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4153
Epoch 430/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4159
Epoch 431/1000
641/641 [==============================] - 216s 332ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2188 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 432/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5123 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4152
Epoch 433/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5124 - val_loss: 0.2187 - val_binary_accuracy: 0.9236 - val_auc: 0.8381 - val_pr: 0.4165
Epoch 434/1000
641/641 [==============================] - 217s 334ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4160
Epoch 435/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5126 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4155
Epoch 436/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4152
Epoch 437/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 438/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5127 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4156
Epoch 439/1000
641/641 [==============================] - 206s 319ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5127 - val_loss: 0.2190 - val_binary_accuracy: 0.9236 - val_auc: 0.8380 - val_pr: 0.4162
Epoch 440/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4148
Epoch 441/1000
641/641 [==============================] - 216s 329ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4155
Epoch 442/1000
641/641 [==============================] - 221s 341ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5124 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4154
Epoch 443/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4149
Epoch 444/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4156
Epoch 445/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5123 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4156
Epoch 446/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1893 - binary_accuracy: 0.9279 - auc: 0.8934 - pr: 0.5124 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8377 - val_pr: 0.4159
Epoch 447/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5127 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4153
Epoch 448/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4159
Epoch 449/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4150
Epoch 450/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5129 - val_loss: 0.2199 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 451/1000
641/641 [==============================] - 204s 314ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2192 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4160
Epoch 452/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4154
Epoch 453/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 454/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4161
Epoch 455/1000
641/641 [==============================] - 201s 310ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4158
Epoch 456/1000
641/641 [==============================] - 208s 319ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5124 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4149
Epoch 457/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5126 - val_loss: 0.2189 - val_binary_accuracy: 0.9236 - val_auc: 0.8381 - val_pr: 0.4158
Epoch 458/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5128 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 459/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2199 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 460/1000
641/641 [==============================] - 200s 308ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8375 - val_pr: 0.4153
Epoch 461/1000
641/641 [==============================] - 206s 319ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5126 - val_loss: 0.2200 - val_binary_accuracy: 0.9236 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 462/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5125 - val_loss: 0.2191 - val_binary_accuracy: 0.9236 - val_auc: 0.8379 - val_pr: 0.4162
Epoch 463/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4158
Epoch 464/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2191 - val_binary_accuracy: 0.9234 - val_auc: 0.8378 - val_pr: 0.4158
Epoch 465/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5125 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4163
Epoch 466/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4158
Epoch 467/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2189 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 468/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8935 - pr: 0.5128 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4156
Epoch 469/1000
641/641 [==============================] - 215s 333ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4159
Epoch 470/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5128 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4155
Epoch 471/1000
641/641 [==============================] - 216s 331ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4152
Epoch 472/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2193 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4161
Epoch 473/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4156
Epoch 474/1000
641/641 [==============================] - 206s 315ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5130 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4163
Epoch 475/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 476/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5125 - val_loss: 0.2191 - val_binary_accuracy: 0.9234 - val_auc: 0.8379 - val_pr: 0.4170
Epoch 477/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 478/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4156
Epoch 479/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4165
Epoch 480/1000
641/641 [==============================] - 201s 307ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4162
Epoch 481/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4157
Epoch 482/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4157
Epoch 483/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5130 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4157
Epoch 484/1000
641/641 [==============================] - 215s 333ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4160
Epoch 485/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5127 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4153
Epoch 486/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4165
Epoch 487/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2197 - val_binary_accuracy: 0.9236 - val_auc: 0.8378 - val_pr: 0.4168
Epoch 488/1000
641/641 [==============================] - 206s 316ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4158
Epoch 489/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4162
Epoch 490/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5130 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4162
Epoch 491/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4158
Epoch 492/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4146
Epoch 493/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4162
Epoch 494/1000
641/641 [==============================] - 213s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8380 - val_pr: 0.4166
Epoch 495/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5133 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4163
Epoch 496/1000
641/641 [==============================] - 205s 316ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4158
Epoch 497/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4154
Epoch 498/1000
641/641 [==============================] - 205s 317ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2191 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4160
Epoch 499/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5129 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4162
Epoch 500/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4160
Epoch 501/1000
641/641 [==============================] - 208s 316ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8381 - val_pr: 0.4169
Epoch 502/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 503/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1892 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4152
Epoch 504/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5128 - val_loss: 0.2190 - val_binary_accuracy: 0.9235 - val_auc: 0.8379 - val_pr: 0.4160
Epoch 505/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4157
Epoch 506/1000
641/641 [==============================] - 206s 317ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4158
Epoch 507/1000
641/641 [==============================] - 215s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2195 - val_binary_accuracy: 0.9236 - val_auc: 0.8376 - val_pr: 0.4158
Epoch 508/1000
641/641 [==============================] - 216s 332ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4160
Epoch 509/1000
641/641 [==============================] - 220s 337ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 510/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4155
Epoch 511/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4162
Epoch 512/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4154
Epoch 513/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 514/1000
641/641 [==============================] - 214s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4165
Epoch 515/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4155
Epoch 516/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4168
Epoch 517/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4158
Epoch 518/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8936 - pr: 0.5128 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 519/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2201 - val_binary_accuracy: 0.9236 - val_auc: 0.8371 - val_pr: 0.4152
Epoch 520/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4157
Epoch 521/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4159
Epoch 522/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4160
Epoch 523/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 524/1000
641/641 [==============================] - 218s 332ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4158
Epoch 525/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 526/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5131 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4161
Epoch 527/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4159
Epoch 528/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2201 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 529/1000
641/641 [==============================] - 206s 318ms/step - loss: 0.1891 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4161
Epoch 530/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4158
Epoch 531/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4159
Epoch 532/1000
641/641 [==============================] - 222s 340ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5131 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 533/1000
641/641 [==============================] - 226s 347ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4161
Epoch 534/1000
641/641 [==============================] - 221s 336ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4150
Epoch 535/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 536/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4153
Epoch 537/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4157
Epoch 538/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4158
Epoch 539/1000
641/641 [==============================] - 221s 338ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2191 - val_binary_accuracy: 0.9234 - val_auc: 0.8377 - val_pr: 0.4161
Epoch 540/1000
641/641 [==============================] - 214s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4154
Epoch 541/1000
641/641 [==============================] - 211s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2192 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 542/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4155
Epoch 543/1000
641/641 [==============================] - 221s 341ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4152
Epoch 544/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 545/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4154
Epoch 546/1000
641/641 [==============================] - 219s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4152
Epoch 547/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4155
Epoch 548/1000
641/641 [==============================] - 205s 317ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2202 - val_binary_accuracy: 0.9236 - val_auc: 0.8370 - val_pr: 0.4153
Epoch 549/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8377 - val_pr: 0.4161
Epoch 550/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5131 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8378 - val_pr: 0.4160
Epoch 551/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4158
Epoch 552/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2205 - val_binary_accuracy: 0.9236 - val_auc: 0.8370 - val_pr: 0.4151
Epoch 553/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4150
Epoch 554/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2204 - val_binary_accuracy: 0.9236 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 555/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5132 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4151
Epoch 556/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4154
Epoch 557/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4154
Epoch 558/1000
641/641 [==============================] - 216s 332ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5131 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4152
Epoch 559/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4159
Epoch 560/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 561/1000
641/641 [==============================] - 217s 330ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2202 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 562/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5129 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4154
Epoch 563/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4159
Epoch 564/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5134 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4157
Epoch 565/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 566/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2194 - val_binary_accuracy: 0.9236 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 567/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2197 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4158
Epoch 568/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4161
Epoch 569/1000
641/641 [==============================] - 219s 334ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8937 - pr: 0.5130 - val_loss: 0.2202 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 570/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4155
Epoch 571/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2202 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4161
Epoch 572/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2198 - val_binary_accuracy: 0.9236 - val_auc: 0.8374 - val_pr: 0.4163
Epoch 573/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 574/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2192 - val_binary_accuracy: 0.9233 - val_auc: 0.8373 - val_pr: 0.4166
Epoch 575/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4156
Epoch 576/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2206 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 577/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4153
Epoch 578/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4162
Epoch 579/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 580/1000
641/641 [==============================] - 206s 317ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5130 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4155
Epoch 581/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8376 - val_pr: 0.4162
Epoch 582/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 583/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 584/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4155
Epoch 585/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2199 - val_binary_accuracy: 0.9236 - val_auc: 0.8371 - val_pr: 0.4160
Epoch 586/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2199 - val_binary_accuracy: 0.9236 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 587/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4153
Epoch 588/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 589/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5131 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4152
Epoch 590/1000
641/641 [==============================] - 216s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 591/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4154
Epoch 592/1000
641/641 [==============================] - 219s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 593/1000
641/641 [==============================] - 217s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4156
Epoch 594/1000
641/641 [==============================] - 214s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2205 - val_binary_accuracy: 0.9236 - val_auc: 0.8367 - val_pr: 0.4151
Epoch 595/1000
641/641 [==============================] - 211s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4158
Epoch 596/1000
641/641 [==============================] - 208s 319ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4157
Epoch 597/1000
641/641 [==============================] - 200s 309ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4156
Epoch 598/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 599/1000
641/641 [==============================] - 207s 317ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4152
Epoch 600/1000
641/641 [==============================] - 213s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4153
Epoch 601/1000
641/641 [==============================] - 206s 315ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 602/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 603/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 604/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 605/1000
641/641 [==============================] - 214s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4155
Epoch 606/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 607/1000
641/641 [==============================] - 202s 307ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8367 - val_pr: 0.4152
Epoch 608/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 609/1000
641/641 [==============================] - 210s 323ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5132 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 610/1000
641/641 [==============================] - 216s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 611/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4154
Epoch 612/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 613/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4151
Epoch 614/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4157
Epoch 615/1000
641/641 [==============================] - 220s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 616/1000
641/641 [==============================] - 220s 340ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 617/1000
641/641 [==============================] - 214s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4151
Epoch 618/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 619/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 620/1000
641/641 [==============================] - 217s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4154
Epoch 621/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9236 - val_auc: 0.8373 - val_pr: 0.4160
Epoch 622/1000
641/641 [==============================] - 209s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 623/1000
641/641 [==============================] - 210s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4160
Epoch 624/1000
641/641 [==============================] - 209s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 625/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4156
Epoch 626/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 627/1000
641/641 [==============================] - 207s 320ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4164
Epoch 628/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 629/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9236 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 630/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 631/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4154
Epoch 632/1000
641/641 [==============================] - 207s 319ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 633/1000
641/641 [==============================] - 220s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2210 - val_binary_accuracy: 0.9235 - val_auc: 0.8364 - val_pr: 0.4150
Epoch 634/1000
641/641 [==============================] - 223s 341ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4162
Epoch 635/1000
641/641 [==============================] - 221s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4155
Epoch 636/1000
641/641 [==============================] - 212s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 637/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4157
Epoch 638/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 639/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4157
Epoch 640/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2194 - val_binary_accuracy: 0.9233 - val_auc: 0.8374 - val_pr: 0.4164
Epoch 641/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 642/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 643/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4155
Epoch 644/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4154
Epoch 645/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 646/1000
641/641 [==============================] - 206s 315ms/step - loss: 0.1891 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4154
Epoch 647/1000
641/641 [==============================] - 216s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4155
Epoch 648/1000
641/641 [==============================] - 226s 347ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2204 - val_binary_accuracy: 0.9236 - val_auc: 0.8368 - val_pr: 0.4150
Epoch 649/1000
641/641 [==============================] - 221s 340ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4153
Epoch 650/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5133 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4150
Epoch 651/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4158
Epoch 652/1000
641/641 [==============================] - 215s 333ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4150
Epoch 653/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 654/1000
641/641 [==============================] - 210s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 655/1000
641/641 [==============================] - 205s 313ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5132 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4157
Epoch 656/1000
641/641 [==============================] - 220s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8940 - pr: 0.5137 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 657/1000
641/641 [==============================] - 213s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 658/1000
641/641 [==============================] - 214s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 659/1000
641/641 [==============================] - 221s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 660/1000
641/641 [==============================] - 217s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8938 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4155
Epoch 661/1000
641/641 [==============================] - 220s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 662/1000
641/641 [==============================] - 220s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4153
Epoch 663/1000
641/641 [==============================] - 214s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2206 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4152
Epoch 664/1000
641/641 [==============================] - 221s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 665/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4160
Epoch 666/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 667/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 668/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2206 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4158
Epoch 669/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2202 - val_binary_accuracy: 0.9236 - val_auc: 0.8368 - val_pr: 0.4155
Epoch 670/1000
641/641 [==============================] - 221s 341ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4163
Epoch 671/1000
641/641 [==============================] - 214s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 672/1000
641/641 [==============================] - 223s 340ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 673/1000
641/641 [==============================] - 209s 323ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8940 - pr: 0.5137 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4159
Epoch 674/1000
641/641 [==============================] - 213s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 675/1000
641/641 [==============================] - 221s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5132 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 676/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8940 - pr: 0.5134 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 677/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4158
Epoch 678/1000
641/641 [==============================] - 218s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 679/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4160
Epoch 680/1000
641/641 [==============================] - 220s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4160
Epoch 681/1000
641/641 [==============================] - 216s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 682/1000
641/641 [==============================] - 217s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4155
Epoch 683/1000
641/641 [==============================] - 213s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2200 - val_binary_accuracy: 0.9234 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 684/1000
641/641 [==============================] - 226s 346ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4159
Epoch 685/1000
641/641 [==============================] - 219s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 686/1000
641/641 [==============================] - 215s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 687/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8367 - val_pr: 0.4156
Epoch 688/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4153
Epoch 689/1000
641/641 [==============================] - 216s 333ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 690/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4156
Epoch 691/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4164
Epoch 692/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4153
Epoch 693/1000
641/641 [==============================] - 215s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8366 - val_pr: 0.4150
Epoch 694/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4157
Epoch 695/1000
641/641 [==============================] - 212s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 696/1000
641/641 [==============================] - 208s 317ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4158
Epoch 697/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8940 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4160
Epoch 698/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4157
Epoch 699/1000
641/641 [==============================] - 223s 344ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4158
Epoch 700/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2194 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 701/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 702/1000
641/641 [==============================] - 206s 319ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 703/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 704/1000
641/641 [==============================] - 212s 324ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4159
Epoch 705/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4160
Epoch 706/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4161
Epoch 707/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4161
Epoch 708/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4164
Epoch 709/1000
641/641 [==============================] - 225s 342ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 710/1000
641/641 [==============================] - 215s 331ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2207 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4154
Epoch 711/1000
641/641 [==============================] - 211s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 712/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2193 - val_binary_accuracy: 0.9232 - val_auc: 0.8376 - val_pr: 0.4170
Epoch 713/1000
641/641 [==============================] - 217s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4158
Epoch 714/1000
641/641 [==============================] - 217s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4156
Epoch 715/1000
641/641 [==============================] - 223s 343ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9236 - val_auc: 0.8370 - val_pr: 0.4159
Epoch 716/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4163
Epoch 717/1000
641/641 [==============================] - 215s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4161
Epoch 718/1000
641/641 [==============================] - 218s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2192 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4162
Epoch 719/1000
641/641 [==============================] - 222s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 720/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4152
Epoch 721/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 722/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2204 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4155
Epoch 723/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4154
Epoch 724/1000
641/641 [==============================] - 214s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 725/1000
641/641 [==============================] - 220s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2203 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 726/1000
641/641 [==============================] - 218s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 727/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4155
Epoch 728/1000
641/641 [==============================] - 220s 340ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2210 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4154
Epoch 729/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4161
Epoch 730/1000
641/641 [==============================] - 217s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2192 - val_binary_accuracy: 0.9233 - val_auc: 0.8376 - val_pr: 0.4166
Epoch 731/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2205 - val_binary_accuracy: 0.9235 - val_auc: 0.8367 - val_pr: 0.4152
Epoch 732/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4162
Epoch 733/1000
641/641 [==============================] - 221s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 734/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2203 - val_binary_accuracy: 0.9236 - val_auc: 0.8369 - val_pr: 0.4153
Epoch 735/1000
641/641 [==============================] - 212s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 736/1000
641/641 [==============================] - 223s 344ms/step - loss: 0.1889 - binary_accuracy: 0.9280 - auc: 0.8940 - pr: 0.5138 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 737/1000
641/641 [==============================] - 221s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 738/1000
641/641 [==============================] - 224s 345ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5138 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4159
Epoch 739/1000
641/641 [==============================] - 210s 325ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2197 - val_binary_accuracy: 0.9233 - val_auc: 0.8374 - val_pr: 0.4162
Epoch 740/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8371 - val_pr: 0.4158
Epoch 741/1000
641/641 [==============================] - 212s 323ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4160
Epoch 742/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 743/1000
641/641 [==============================] - 204s 315ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2201 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4158
Epoch 744/1000
641/641 [==============================] - 208s 321ms/step - loss: 0.1889 - binary_accuracy: 0.9280 - auc: 0.8940 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 745/1000
641/641 [==============================] - 208s 319ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 746/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2202 - val_binary_accuracy: 0.9234 - val_auc: 0.8370 - val_pr: 0.4160
Epoch 747/1000
641/641 [==============================] - 213s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4157
Epoch 748/1000
641/641 [==============================] - 219s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8376 - val_pr: 0.4161
Epoch 749/1000
641/641 [==============================] - 218s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4162
Epoch 750/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4161
Epoch 751/1000
641/641 [==============================] - 208s 320ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2194 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4167
Epoch 752/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2193 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 753/1000
641/641 [==============================] - 222s 343ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4161
Epoch 754/1000
641/641 [==============================] - 214s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4154
Epoch 755/1000
641/641 [==============================] - 221s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4158
Epoch 756/1000
641/641 [==============================] - 211s 322ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 757/1000
641/641 [==============================] - 204s 316ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2197 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4162
Epoch 758/1000
641/641 [==============================] - 219s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2206 - val_binary_accuracy: 0.9235 - val_auc: 0.8368 - val_pr: 0.4154
Epoch 759/1000
641/641 [==============================] - 222s 342ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5138 - val_loss: 0.2196 - val_binary_accuracy: 0.9234 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 760/1000
641/641 [==============================] - 213s 329ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8938 - pr: 0.5134 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 761/1000
641/641 [==============================] - 212s 328ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4159
Epoch 762/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4157
Epoch 763/1000
641/641 [==============================] - 217s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4163
Epoch 764/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9236 - val_auc: 0.8372 - val_pr: 0.4160
Epoch 765/1000
641/641 [==============================] - 222s 343ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5138 - val_loss: 0.2193 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4162
Epoch 766/1000
641/641 [==============================] - 217s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4163
Epoch 767/1000
641/641 [==============================] - 219s 335ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 768/1000
641/641 [==============================] - 216s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5133 - val_loss: 0.2199 - val_binary_accuracy: 0.9233 - val_auc: 0.8373 - val_pr: 0.4162
Epoch 769/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2201 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4158
Epoch 770/1000
641/641 [==============================] - 227s 350ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 771/1000
641/641 [==============================] - 211s 326ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4155
Epoch 772/1000
641/641 [==============================] - 214s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4161
Epoch 773/1000
641/641 [==============================] - 211s 327ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4159
Epoch 774/1000
641/641 [==============================] - 220s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8940 - pr: 0.5136 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8371 - val_pr: 0.4156
Epoch 775/1000
641/641 [==============================] - 220s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5138 - val_loss: 0.2194 - val_binary_accuracy: 0.9232 - val_auc: 0.8377 - val_pr: 0.4168
Epoch 776/1000
641/641 [==============================] - 221s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5137 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 777/1000
641/641 [==============================] - 215s 332ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2196 - val_binary_accuracy: 0.9235 - val_auc: 0.8373 - val_pr: 0.4156
Epoch 778/1000
641/641 [==============================] - 224s 346ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4169
Epoch 779/1000
641/641 [==============================] - 218s 333ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2199 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4160
Epoch 780/1000
641/641 [==============================] - 226s 349ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2199 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 781/1000
641/641 [==============================] - 219s 338ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2202 - val_binary_accuracy: 0.9235 - val_auc: 0.8369 - val_pr: 0.4156
Epoch 782/1000
641/641 [==============================] - 217s 333ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8373 - val_pr: 0.4160
Epoch 783/1000
641/641 [==============================] - 219s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8370 - val_pr: 0.4157
Epoch 784/1000
641/641 [==============================] - 218s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2195 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4161
Epoch 785/1000
641/641 [==============================] - 216s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 786/1000
641/641 [==============================] - 225s 345ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8375 - val_pr: 0.4161
Epoch 787/1000
641/641 [==============================] - 221s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4161
Epoch 788/1000
641/641 [==============================] - 223s 344ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2200 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4157
Epoch 789/1000
641/641 [==============================] - 219s 334ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4158
Epoch 790/1000
641/641 [==============================] - 220s 339ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2204 - val_binary_accuracy: 0.9236 - val_auc: 0.8370 - val_pr: 0.4156
Epoch 791/1000
641/641 [==============================] - 216s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5134 - val_loss: 0.2198 - val_binary_accuracy: 0.9235 - val_auc: 0.8372 - val_pr: 0.4159
Epoch 792/1000
641/641 [==============================] - 220s 337ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2197 - val_binary_accuracy: 0.9235 - val_auc: 0.8374 - val_pr: 0.4159
Epoch 793/1000
641/641 [==============================] - 220s 336ms/step - loss: 0.1890 - binary_accuracy: 0.9280 - auc: 0.8939 - pr: 0.5136 - val_loss: 0.2195 - val_binary_accuracy: 0.9234 - val_auc: 0.8374 - val_pr: 0.4161
Epoch 794/1000
641/641 [==============================] - 215s 330ms/step - loss: 0.1890 - binary_accuracy: 0.9279 - auc: 0.8939 - pr: 0.5135 - val_loss: 0.2198 - val_binary_accuracy: 0.9234 - val_auc: 0.8372 - val_pr: 0.4156
Epoch 00794: early stopping
8. Save training results...
=== Training completed! ===
Best model: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out/E1000best_model.h5
Training history: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out/history.pickle

Plotting training metrics to monitor overfitting and evaluate the final model performance. Ideally, after a certain number of epochs, the validation curves plateau (i.e., remain stable).

The metrics computed during training are saved in ./data/4_pred_newCondition/train_out/history.pickle. Load them with:

import pickle
with open('./data/4_pred_newCondition/train_out/history.pickle', 'rb') as f:
    history = pickle.load(f)

You can then use this history object to plot training/validation metrics (e.g., loss, auROC/auPRC, NS/LS) over epochs.

The function plot_train_history() will automatically detect whether NS and LS values have been computed during training. If these metrics are available in the history data, they will be automatically included in the training metric plots along with other evaluation metrics such as loss, auROC, and auPRC.

[5]:

xc.pl.plot_train_history(
    history = history['history'],
    savefig = True,
    out_file = './data/4_pred_newCondition/train_out/train_history_plot.pdf'
    )

../_images/Tutorials_4_pred-newCondition_calc_TFactivity_11_0.png

4. Calculate TF activity

We performed motif insertion on trained XChrom to compute a TF activity score for each TF for each cell.

Specifically, we first generate 1000 genomic background sequences (determined by n_samples) by performing dinucleotide shuffling of 1000 randomly sampled peaks from the training sequences atlas using fasta ushuffle. For each TF in the motif database, we sampled 1000 motif sequences(determined by n_motif_instances) from the PWM and inserted each instance at the center of every background sequence. We run forward passes for both the motif-inserted sequences and their background counterparts to predict accessibility across all cells, and define the motif influence for each sequence as the difference between the two predictions. Finally, we average this influence across all 1000 sequences per cell to obtain a cell-level raw TF activity score.
For this，you must install fasta_ushuffle first with: conda install bioconda::fasta_ushuffle

[6]:

seq_path = xc.tl.generate_tf_activity_data(
    bed_file = './data/4_pred_newCondition/train_data/peaks.bed',  ## to generate background sequence
    input_fasta = '/picb/bigdata/project/miaoyuanyuan/hg38.fa',
    motif_file = './data/4_pred_newCondition/Homo_sapiens.meme',
    output_dir = './data/4_pred_newCondition/motif_fasta/',
    n_samples = 1000,
    n_motif_instances = 1000)

=== Start preparing motif data ===
1. Read BED file: ./data/4_pred_newCondition/train_data/peaks.bed
Sampled 1000 regions from ./data/4_pred_newCondition/train_data/peaks.bed
2. Extract background sequences...
Extracting sequences from BED file...
Reference genome: /picb/bigdata/project/miaoyuanyuan/hg38.fa
Sequence length: 1344
Consider strand information: False
Successfully extracted 1000 sequences
Writing to FASTA file: data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta
FASTA file saved to: data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta
Number of sequences written: 1000
Extracted 1000 sequences, saved to data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta
3. Generate shuffled background sequences...
Using fasta_ushuffle from: /home/miaoyuanyuan/miniconda3/envs/py3.8_tf2.6.0/bin/fasta_ushuffle
Dinucleotide shuffled 1000 sequences, saved to data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta
4. Read motif file(meme format)...
Read 1065 motifs from ./data/4_pred_newCondition/Homo_sapiens.meme
5. Generate motif inserted sequences...

Processing motifs: 100%|████████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [04:59<00:00,  3.56it/s]

=== motif data preparation completed ===
Background sequence file: data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta
Motif inserted sequence directory: data/4_pred_newCondition/motif_fasta/shuffled_peaks_motifs

Note: Since the COVID-19 data lacks paired scATAC data, background sequences can only be sampled from the training set.

[8]:

covid_rna = sc.read_h5ad('./data/4_pred_newCondition/covid_rna_harmony.h5ad')
tf_act = xc.tl.calc_tf_activity(
    motif_dir = './data/4_pred_newCondition/motif_fasta/shuffled_peaks_motifs/',
    background_fasta = './data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta',
    model_path = './data/4_pred_newCondition/train_out/E1000best_model.h5',
    ad_rna = covid_rna,
    output_file = './data/4_pred_newCondition/analysis_out/tf_activity.h5ad',
    cell_embed_raw = 'X_pca_harmony',
    regenerate_motif_h5 = True,
    regenerate_bg_h5 = True)

=== Start calculating TF Activity ===
1. Prepare raw cell embedding...
2. Generate motif insertion sequence h5 files...

Generating H5 files: 100%|██████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [06:56<00:00,  2.56it/s]

Found 1065 motif files
3. Generate background sequence h5 file...
Generating background sequence h5 file...
4. Prepare data for XChrom model input...
Converting adata.X to dense array. For large datasets, consider pre-computing and saving as sparse matrix.
5. Load trained model...
6. Calculate background sequence prediction...
7. Calculate motif insertion scores...
Processing 1065 motif files...

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [5:00:22<00:00, 16.92s/it]

8. Save results...
=== Done! Results saved to: data/4_pred_newCondition/analysis_out/tf_activity.h5ad ===
TF activity matrix shape: (90312, 1065) (cells × motifs)

Note: This process will take a long time

If you do not need to calculate activities for all motifs, you can keep only the motif files you require in the motif_dir.

Set regenerate_bg_h5=False if you have already generated the background sequences in H5 format, Set regenerate_motif_h5=False if you have already generated H5 files for each motif.

5. Check TF activity in different cell types

[9]:

covid_rna = sc.read_h5ad('./data/4_pred_newCondition/covid_rna_harmony.h5ad')
tf_act = sc.read_h5ad('./data/4_pred_newCondition/analysis_out/tf_activity.h5ad')

[10]:

xc.pl.plot_motif_activity(
    cell_embedding_ad = covid_rna,
    celltype_key = 'celltypeL0',
    tf_act_raw = tf_act,
    motif_name = 'CEBPB',
    save_path = './CEBPB_activity.pdf'
)

Plot saved to: ./CEBPB_activity.pdf

../_images/Tutorials_4_pred-newCondition_calc_TFactivity_19_1.png

The plot_motif_activity() function performs z-score normalization of the calculated TF activity across cell types. In the resulting visualization:

Red indicates that CEBPB shows relatively higher activity in Mono
Blue indicates relatively lower activity

This normalization allows for clear comparison of TF activity patterns across different cell types and conditions.