{ "cells": [ { "cell_type": "markdown", "id": "d9db57e0-fb4c-4a93-8795-f2b0dcfefb32", "metadata": {}, "source": [ "## **4. COVID-19 analysis** \n", "\n", "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.\n", "\n", "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.\n", "\n", "- **Data Preprocessing** \n", "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.\n", "\n", "- **Model Training** \n", "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.\n", "\n", "- **Model Prediction** \n", "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.\n", "\n", "- **Interpretability analysis** \n", "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." ] }, { "cell_type": "markdown", "id": "2621fe84-2458-4a76-a8ad-72ba7dda0e52", "metadata": {}, "source": [ "### 1. Download Data (PBMC10k, COVID-19)\n", "\n", "- The original PBMC10k data is available at: \n", " [https://cf.10xgenomics.com/samples/cell-arc/2.0.0/pbmc_granulocyte_sorted_10k/pbmc_granulocyte_sorted_10k_filtered_feature_bc_matrix.h5](https://cf.10xgenomics.com/samples/cell-arc/2.0.0/pbmc_granulocyte_sorted_10k/pbmc_granulocyte_sorted_10k_filtered_feature_bc_matrix.h5) \n", " The original COVID-19 data is available at: \n", " [https://nubes.helmholtz-berlin.de/s/wqg6tmX4fW7pci5/download](https://nubes.helmholtz-berlin.de/s/wqg6tmX4fW7pci5/download) \n", " 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.\n", "\n", "- Download the PBMC10k data and save it as: \n", " `'./data/4_pred_newCondition/pbmc10k_atac.h5ad'` \n", " `'./data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad'` \n", " (These files will be used for model training)\n", "\n", "- Download the COVID-19 data and save it as: \n", " `'./data/4_pred_newCondition/covid_rna_harmony.h5ad'` \n", " (This file provides the model input for inferring TF activity)\n", "\n", "- Download the motif database file from: \n", " [https://meme-suite.org/meme/meme-software/Databases/motifs/motif_databases.12.27.tgz](https://meme-suite.org/meme/meme-software/Databases/motifs/motif_databases.12.27.tgz) \n", " After decompression, select the file `motif_databases/CIS-BP_2.00/Homo_sapiens.meme` and save it to: \n", " `'./data/4_pred_newCondition/Homo_sapiens.meme'`\n", "\n", "- Download the human genome file from: \n", " [https://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz](https://hgdownload.soe.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz) \n", " and decompress it.\n", "\n", "- The raw batch-corrected cell embeddings are stored in `RNA.obsm['X_pca_harmony']`, and cell type labels are available in `RNA.obs['celltypeL0']`." ] }, { "cell_type": "code", "execution_count": 1, "id": "22ebaef5-3d4f-4ce0-a1db-184ac5c3f729", "metadata": {}, "outputs": [], "source": [ "import scanpy as sc\n", "import xchrom as xc" ] }, { "cell_type": "code", "execution_count": 2, "id": "a0d8df83-15d5-4701-9a32-846bfc15b62e", "metadata": {}, "outputs": [], "source": [ "# import os\n", "# os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"3,2,1,0\" " ] }, { "cell_type": "markdown", "id": "94b0534d-a56b-46ad-aaee-ab44a1525bc5", "metadata": {}, "source": [ "### 2. Training/test data prepare" ] }, { "cell_type": "code", "execution_count": 3, "id": "8c992117-0452-49da-931b-b9a593038a6a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train/test data is saved in: data/4_pred_newCondition/train_data\n", "successful writing bed file.\n", "successful writing train/test split file.\n", "successful writing train/test anndata file.\n", "successful writing sparse m.\n", "Successfully saving all sequence h5 file...\n", "Successfully saving trainval sequence h5 file...\n", "Successfully saving test sequence h5 file...\n" ] } ], "source": [ "## Generate data for model training\n", "train_folder = './data/4_pred_newCondition/train_data/'\n", "input_fasta = '/picb/bigdata/project/miaoyuanyuan/hg38.fa'\n", "train_atac = sc.read_h5ad('./data/4_pred_newCondition/pbmc10k_atac.h5ad')\n", "dict = xc.pp.process_train_test_single(\n", " ad_atac=train_atac, ## can be a str, Path, or anndata.AnnData object\n", " input_fasta=input_fasta,\n", " output_path=train_folder\n", ")" ] }, { "cell_type": "markdown", "id": "bf663e24-8604-4643-ac88-669b6f2f5ada", "metadata": {}, "source": [ "We performed preprocessing on the filtered PBMC10k scATAC:\n", "\n", "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:\n", "- `ad_trainval.h5ad`: containing training cells and training peaks\n", "- `m_trainval.npz`: corresponding count matrix\n", "- `trainval_seqs.h5`: base sequence file for training peaks \n", "\n", "All files were saved in `'./data/4_pred_newCondition/train_data/'`.\n", "\n", "Note: The `input_fasta` parameter should be replaced with the path to the genome file corresponding to the species used in your specific dataset." ] }, { "cell_type": "markdown", "id": "7631caa1-b54c-4780-8421-592693ca25d5", "metadata": {}, "source": [ "### 3. Train the model" ] }, { "cell_type": "markdown", "id": "ab699c7c-6e18-419b-89c4-a4a4f5f359e5", "metadata": {}, "source": [ "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. \n", "\n", "- 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. \n", "\n", "- 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. \n", " \n", "- 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). " ] }, { "cell_type": "code", "execution_count": 4, "id": "30250a94-11e9-488b-977e-82083e039b24", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== Start training XChrom model ===\n", "Input folder: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_data\n", "Cell embedding file: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad\n", "Raw cell embedding key: X_pca_harmony\n", "Output path: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out\n", "Model parameters: bottleneck=32, batch_size=128, lr=0.01\n", "1. Load raw cell embedding and make z-score normalization...\n", "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']\n", "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']\n", "Initial cell embedding shape: (11898, 32)\n", "2. Load training data...\n", "3. Prepare train/val data split...\n", "Training peak number: 81963, Validation peak number: 9107\n", "4. Create TensorFlow dataset...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "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\n", "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "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\n", "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\n", "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\n", "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\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "5. Build and compile model...\n", "Model: \"model\"\n", "__________________________________________________________________________________________________\n", "Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", "sequence (InputLayer) [(None, 1344, 4)] 0 \n", "__________________________________________________________________________________________________\n", "stochastic_reverse_complement ( ((None, 1344, 4), () 0 sequence[0][0] \n", "__________________________________________________________________________________________________\n", "stochastic_shift (StochasticShi (None, 1344, 4) 0 stochastic_reverse_complement[0][\n", "__________________________________________________________________________________________________\n", "gelu (GELU) (None, 1344, 4) 0 stochastic_shift[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d (Conv1D) (None, 1344, 288) 19584 gelu[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization (BatchNorma (None, 1344, 288) 1152 conv1d[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d (MaxPooling1D) (None, 448, 288) 0 batch_normalization[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_1 (GELU) (None, 448, 288) 0 max_pooling1d[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_1 (Conv1D) (None, 448, 288) 414720 gelu_1[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_1 (BatchNor (None, 448, 288) 1152 conv1d_1[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_1 (MaxPooling1D) (None, 224, 288) 0 batch_normalization_1[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_2 (GELU) (None, 224, 288) 0 max_pooling1d_1[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_2 (Conv1D) (None, 224, 323) 465120 gelu_2[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_2 (BatchNor (None, 224, 323) 1292 conv1d_2[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_2 (MaxPooling1D) (None, 112, 323) 0 batch_normalization_2[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_3 (GELU) (None, 112, 323) 0 max_pooling1d_2[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_3 (Conv1D) (None, 112, 363) 586245 gelu_3[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_3 (BatchNor (None, 112, 363) 1452 conv1d_3[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_3 (MaxPooling1D) (None, 56, 363) 0 batch_normalization_3[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_4 (GELU) (None, 56, 363) 0 max_pooling1d_3[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_4 (Conv1D) (None, 56, 407) 738705 gelu_4[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_4 (BatchNor (None, 56, 407) 1628 conv1d_4[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_4 (MaxPooling1D) (None, 28, 407) 0 batch_normalization_4[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_5 (GELU) (None, 28, 407) 0 max_pooling1d_4[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_5 (Conv1D) (None, 28, 456) 927960 gelu_5[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_5 (BatchNor (None, 28, 456) 1824 conv1d_5[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_5 (MaxPooling1D) (None, 14, 456) 0 batch_normalization_5[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_6 (GELU) (None, 14, 456) 0 max_pooling1d_5[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_6 (Conv1D) (None, 14, 512) 1167360 gelu_6[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_6 (BatchNor (None, 14, 512) 2048 conv1d_6[0][0] \n", "__________________________________________________________________________________________________\n", "max_pooling1d_6 (MaxPooling1D) (None, 7, 512) 0 batch_normalization_6[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_7 (GELU) (None, 7, 512) 0 max_pooling1d_6[0][0] \n", "__________________________________________________________________________________________________\n", "conv1d_7 (Conv1D) (None, 7, 256) 131072 gelu_7[0][0] \n", "__________________________________________________________________________________________________\n", "batch_normalization_7 (BatchNor (None, 7, 256) 1024 conv1d_7[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_8 (GELU) (None, 7, 256) 0 batch_normalization_7[0][0] \n", "__________________________________________________________________________________________________\n", "reshape (Reshape) (None, 1, 1792) 0 gelu_8[0][0] \n", "__________________________________________________________________________________________________\n", "dense (Dense) (None, 1, 32) 57344 reshape[0][0] \n", "__________________________________________________________________________________________________\n", "cell_embed (InputLayer) [(None, 10709, 32)] 0 \n", "__________________________________________________________________________________________________\n", "batch_normalization_8 (BatchNor (None, 1, 32) 128 dense[0][0] \n", "__________________________________________________________________________________________________\n", "lambda (Lambda) (None, 10709, 32) 0 cell_embed[0][0] \n", "__________________________________________________________________________________________________\n", "dropout (Dropout) (None, 1, 32) 0 batch_normalization_8[0][0] \n", "__________________________________________________________________________________________________\n", "layer_normalization (LayerNorma (None, 10709, 32) 64 lambda[0][0] \n", "__________________________________________________________________________________________________\n", "gelu_9 (GELU) (None, 1, 32) 0 dropout[0][0] \n", "__________________________________________________________________________________________________\n", "dense_1 (Dense) (None, 10709, 64) 2112 layer_normalization[0][0] \n", "__________________________________________________________________________________________________\n", "tf.compat.v1.squeeze (TFOpLambd (None, 32) 0 gelu_9[0][0] \n", "__________________________________________________________________________________________________\n", "sequencing_depth (InputLayer) [(None, 10709)] 0 \n", "__________________________________________________________________________________________________\n", "final_cellembed (Dense) (None, 10709, 32) 2080 dense_1[0][0] \n", "__________________________________________________________________________________________________\n", "tf.expand_dims (TFOpLambda) (None, 32, 1) 0 tf.compat.v1.squeeze[0][0] \n", "__________________________________________________________________________________________________\n", "tf.expand_dims_1 (TFOpLambda) (None, 10709, 1) 0 sequencing_depth[0][0] \n", "__________________________________________________________________________________________________\n", "tf.linalg.matmul (TFOpLambda) (None, 10709, 1) 0 final_cellembed[0][0] \n", " tf.expand_dims[0][0] \n", "__________________________________________________________________________________________________\n", "dense_2 (Dense) (None, 10709, 1) 2 tf.expand_dims_1[0][0] \n", "__________________________________________________________________________________________________\n", "tf.compat.v1.squeeze_2 (TFOpLam (None, 10709) 0 tf.linalg.matmul[0][0] \n", "__________________________________________________________________________________________________\n", "tf.compat.v1.squeeze_1 (TFOpLam (None, 10709) 0 dense_2[0][0] \n", "__________________________________________________________________________________________________\n", "tf.__operators__.add (TFOpLambd (None, 10709) 0 tf.compat.v1.squeeze_2[0][0] \n", " tf.compat.v1.squeeze_1[0][0] \n", "__________________________________________________________________________________________________\n", "tf.math.sigmoid (TFOpLambda) (None, 10709) 0 tf.__operators__.add[0][0] \n", "==================================================================================================\n", "Total params: 4,524,068\n", "Trainable params: 4,518,218\n", "Non-trainable params: 5,850\n", "__________________________________________________________________________________________________\n", "6. Set training callbacks...\n", "7. Start training...\n", "Model will be saved to: data/4_pred_newCondition/train_out/E1000best_model.h5\n", "Epoch 1/1000\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "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)\n", "2025-08-18 15:11:46.107242: I tensorflow/stream_executor/cuda/cuda_dnn.cc:369] Loaded cuDNN version 8800\n", "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.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "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\n", "Epoch 2/1000\n", "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\n", "Epoch 3/1000\n", "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\n", "Epoch 4/1000\n", "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\n", "Epoch 5/1000\n", "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\n", "Epoch 6/1000\n", "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\n", "Epoch 7/1000\n", "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\n", "Epoch 8/1000\n", "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\n", "Epoch 9/1000\n", "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\n", "Epoch 10/1000\n", "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\n", "Epoch 11/1000\n", "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\n", "Epoch 12/1000\n", "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\n", "Epoch 13/1000\n", "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\n", "Epoch 14/1000\n", "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\n", "Epoch 15/1000\n", "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\n", "Epoch 16/1000\n", "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\n", "Epoch 17/1000\n", "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\n", "Epoch 18/1000\n", "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\n", "Epoch 19/1000\n", "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\n", "Epoch 20/1000\n", "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\n", "Epoch 21/1000\n", "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\n", "Epoch 22/1000\n", "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\n", "Epoch 23/1000\n", "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\n", "Epoch 24/1000\n", "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\n", "Epoch 25/1000\n", "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\n", "Epoch 26/1000\n", "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\n", "Epoch 27/1000\n", "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\n", "Epoch 28/1000\n", "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\n", "Epoch 29/1000\n", "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\n", "Epoch 30/1000\n", "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\n", "Epoch 31/1000\n", "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\n", "Epoch 32/1000\n", "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\n", "Epoch 33/1000\n", "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\n", "Epoch 34/1000\n", "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\n", "Epoch 35/1000\n", "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\n", "Epoch 36/1000\n", "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\n", "Epoch 37/1000\n", "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\n", "Epoch 38/1000\n", "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\n", "Epoch 39/1000\n", "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\n", "Epoch 40/1000\n", "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\n", "Epoch 41/1000\n", "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\n", "Epoch 42/1000\n", "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\n", "Epoch 43/1000\n", "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\n", "Epoch 44/1000\n", "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\n", "Epoch 45/1000\n", "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\n", "Epoch 46/1000\n", "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\n", "Epoch 47/1000\n", "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\n", "Epoch 48/1000\n", "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\n", "Epoch 49/1000\n", "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\n", "Epoch 50/1000\n", "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\n", "Epoch 51/1000\n", "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\n", "Epoch 52/1000\n", "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\n", "Epoch 53/1000\n", "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\n", "Epoch 54/1000\n", "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\n", "Epoch 55/1000\n", "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\n", "Epoch 56/1000\n", "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\n", "Epoch 57/1000\n", "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\n", "Epoch 58/1000\n", "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\n", "Epoch 59/1000\n", "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\n", "Epoch 60/1000\n", "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\n", "Epoch 61/1000\n", "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\n", "Epoch 62/1000\n", "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\n", "Epoch 63/1000\n", "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\n", "Epoch 64/1000\n", "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\n", "Epoch 65/1000\n", "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\n", "Epoch 66/1000\n", "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\n", "Epoch 67/1000\n", "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\n", "Epoch 68/1000\n", "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\n", "Epoch 69/1000\n", "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\n", "Epoch 70/1000\n", "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\n", "Epoch 71/1000\n", "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\n", "Epoch 72/1000\n", "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\n", "Epoch 73/1000\n", "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\n", "Epoch 74/1000\n", "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\n", "Epoch 75/1000\n", "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\n", "Epoch 76/1000\n", "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\n", "Epoch 77/1000\n", "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\n", "Epoch 78/1000\n", "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\n", "Epoch 79/1000\n", "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\n", "Epoch 80/1000\n", "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\n", "Epoch 81/1000\n", "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\n", "Epoch 82/1000\n", "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\n", "Epoch 83/1000\n", "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\n", "Epoch 84/1000\n", "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\n", "Epoch 85/1000\n", "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\n", "Epoch 86/1000\n", "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\n", "Epoch 87/1000\n", "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\n", "Epoch 88/1000\n", "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\n", "Epoch 89/1000\n", "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\n", "Epoch 90/1000\n", "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\n", "Epoch 91/1000\n", "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\n", "Epoch 92/1000\n", "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\n", "Epoch 93/1000\n", "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\n", "Epoch 94/1000\n", "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\n", "Epoch 95/1000\n", "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\n", "Epoch 96/1000\n", "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\n", "Epoch 97/1000\n", "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\n", "Epoch 98/1000\n", "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\n", "Epoch 99/1000\n", "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\n", "Epoch 100/1000\n", "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\n", "Epoch 101/1000\n", "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\n", "Epoch 102/1000\n", "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\n", "Epoch 103/1000\n", "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\n", "Epoch 104/1000\n", "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\n", "Epoch 105/1000\n", "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\n", "Epoch 106/1000\n", "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\n", "Epoch 107/1000\n", "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\n", "Epoch 108/1000\n", "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\n", "Epoch 109/1000\n", "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\n", "Epoch 110/1000\n", "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\n", "Epoch 111/1000\n", "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\n", "Epoch 112/1000\n", "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\n", "Epoch 113/1000\n", "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\n", "Epoch 114/1000\n", "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\n", "Epoch 115/1000\n", "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\n", "Epoch 116/1000\n", "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\n", "Epoch 117/1000\n", "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\n", "Epoch 118/1000\n", "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\n", "Epoch 119/1000\n", "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\n", "Epoch 120/1000\n", "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\n", "Epoch 121/1000\n", "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\n", "Epoch 122/1000\n", "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\n", "Epoch 123/1000\n", "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\n", "Epoch 124/1000\n", "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\n", "Epoch 125/1000\n", "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\n", "Epoch 126/1000\n", "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\n", "Epoch 127/1000\n", "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\n", "Epoch 128/1000\n", "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\n", "Epoch 129/1000\n", "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\n", "Epoch 130/1000\n", "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\n", "Epoch 131/1000\n", "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\n", "Epoch 132/1000\n", "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\n", "Epoch 133/1000\n", "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\n", "Epoch 134/1000\n", "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\n", "Epoch 135/1000\n", "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\n", "Epoch 136/1000\n", "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\n", "Epoch 137/1000\n", "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\n", "Epoch 138/1000\n", "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\n", "Epoch 139/1000\n", "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\n", "Epoch 140/1000\n", "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\n", "Epoch 141/1000\n", "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\n", "Epoch 142/1000\n", "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\n", "Epoch 143/1000\n", "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\n", "Epoch 144/1000\n", "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\n", "Epoch 145/1000\n", "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\n", "Epoch 146/1000\n", "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\n", "Epoch 147/1000\n", "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\n", "Epoch 148/1000\n", "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\n", "Epoch 149/1000\n", "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\n", "Epoch 150/1000\n", "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\n", "Epoch 151/1000\n", "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\n", "Epoch 152/1000\n", "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\n", "Epoch 153/1000\n", "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\n", "Epoch 154/1000\n", "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\n", "Epoch 155/1000\n", "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\n", "Epoch 156/1000\n", "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\n", "Epoch 157/1000\n", "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\n", "Epoch 158/1000\n", "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\n", "Epoch 159/1000\n", "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\n", "Epoch 160/1000\n", "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\n", "Epoch 161/1000\n", "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\n", "Epoch 162/1000\n", "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\n", "Epoch 163/1000\n", "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\n", "Epoch 164/1000\n", "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\n", "Epoch 165/1000\n", "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\n", "Epoch 166/1000\n", "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\n", "Epoch 167/1000\n", "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\n", "Epoch 168/1000\n", "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\n", "Epoch 169/1000\n", "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\n", "Epoch 170/1000\n", "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\n", "Epoch 171/1000\n", "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\n", "Epoch 172/1000\n", "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\n", "Epoch 173/1000\n", "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\n", "Epoch 174/1000\n", "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\n", "Epoch 175/1000\n", "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\n", "Epoch 176/1000\n", "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\n", "Epoch 177/1000\n", "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\n", "Epoch 178/1000\n", "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\n", "Epoch 179/1000\n", "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\n", "Epoch 180/1000\n", "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\n", "Epoch 181/1000\n", "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\n", "Epoch 182/1000\n", "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\n", "Epoch 183/1000\n", "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\n", "Epoch 184/1000\n", "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\n", "Epoch 185/1000\n", "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\n", "Epoch 186/1000\n", "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\n", "Epoch 187/1000\n", "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\n", "Epoch 188/1000\n", "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\n", "Epoch 189/1000\n", "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\n", "Epoch 190/1000\n", "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\n", "Epoch 191/1000\n", "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\n", "Epoch 192/1000\n", "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\n", "Epoch 193/1000\n", "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\n", "Epoch 194/1000\n", "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\n", "Epoch 195/1000\n", "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\n", "Epoch 196/1000\n", "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\n", "Epoch 197/1000\n", "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\n", "Epoch 198/1000\n", "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\n", "Epoch 199/1000\n", "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\n", "Epoch 200/1000\n", "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\n", "Epoch 201/1000\n", "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\n", "Epoch 202/1000\n", "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\n", "Epoch 203/1000\n", "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\n", "Epoch 204/1000\n", "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\n", "Epoch 205/1000\n", "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\n", "Epoch 206/1000\n", "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\n", "Epoch 207/1000\n", "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\n", "Epoch 208/1000\n", "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\n", "Epoch 209/1000\n", "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\n", "Epoch 210/1000\n", "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\n", "Epoch 211/1000\n", "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\n", "Epoch 212/1000\n", "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\n", "Epoch 213/1000\n", "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\n", "Epoch 214/1000\n", "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\n", "Epoch 215/1000\n", "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\n", "Epoch 216/1000\n", "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\n", "Epoch 217/1000\n", "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\n", "Epoch 218/1000\n", "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\n", "Epoch 219/1000\n", "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\n", "Epoch 220/1000\n", "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\n", "Epoch 221/1000\n", "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\n", "Epoch 222/1000\n", "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\n", "Epoch 223/1000\n", "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\n", "Epoch 224/1000\n", "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\n", "Epoch 225/1000\n", "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\n", "Epoch 226/1000\n", "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\n", "Epoch 227/1000\n", "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\n", "Epoch 228/1000\n", "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\n", "Epoch 229/1000\n", "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\n", "Epoch 230/1000\n", "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\n", "Epoch 231/1000\n", "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\n", "Epoch 232/1000\n", "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\n", "Epoch 233/1000\n", "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\n", "Epoch 234/1000\n", "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\n", "Epoch 235/1000\n", "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\n", "Epoch 236/1000\n", "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\n", "Epoch 237/1000\n", "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\n", "Epoch 238/1000\n", "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\n", "Epoch 239/1000\n", "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\n", "Epoch 240/1000\n", "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\n", "Epoch 241/1000\n", "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\n", "Epoch 242/1000\n", "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\n", "Epoch 243/1000\n", "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\n", "Epoch 244/1000\n", "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\n", "Epoch 245/1000\n", "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\n", "Epoch 246/1000\n", "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\n", "Epoch 247/1000\n", "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\n", "Epoch 248/1000\n", "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\n", "Epoch 249/1000\n", "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\n", "Epoch 250/1000\n", "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\n", "Epoch 251/1000\n", "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\n", "Epoch 252/1000\n", "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\n", "Epoch 253/1000\n", "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\n", "Epoch 254/1000\n", "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\n", "Epoch 255/1000\n", "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\n", "Epoch 256/1000\n", "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\n", "Epoch 257/1000\n", "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\n", "Epoch 258/1000\n", "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\n", "Epoch 259/1000\n", "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\n", "Epoch 260/1000\n", "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\n", "Epoch 261/1000\n", "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\n", "Epoch 262/1000\n", "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\n", "Epoch 263/1000\n", "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\n", "Epoch 264/1000\n", "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\n", "Epoch 265/1000\n", "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\n", "Epoch 266/1000\n", "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\n", "Epoch 267/1000\n", "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\n", "Epoch 268/1000\n", "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\n", "Epoch 269/1000\n", "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\n", "Epoch 270/1000\n", "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\n", "Epoch 271/1000\n", "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\n", "Epoch 272/1000\n", "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\n", "Epoch 273/1000\n", "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\n", "Epoch 274/1000\n", "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\n", "Epoch 275/1000\n", "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\n", "Epoch 276/1000\n", "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\n", "Epoch 277/1000\n", "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\n", "Epoch 278/1000\n", "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\n", "Epoch 279/1000\n", "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\n", "Epoch 280/1000\n", "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\n", "Epoch 281/1000\n", "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\n", "Epoch 282/1000\n", "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\n", "Epoch 283/1000\n", "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\n", "Epoch 284/1000\n", "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\n", "Epoch 285/1000\n", "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\n", "Epoch 286/1000\n", "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\n", "Epoch 287/1000\n", "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\n", "Epoch 288/1000\n", "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\n", "Epoch 289/1000\n", "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\n", "Epoch 290/1000\n", "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\n", "Epoch 291/1000\n", "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\n", "Epoch 292/1000\n", "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\n", "Epoch 293/1000\n", "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\n", "Epoch 294/1000\n", "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\n", "Epoch 295/1000\n", "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\n", "Epoch 296/1000\n", "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\n", "Epoch 297/1000\n", "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\n", "Epoch 298/1000\n", "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\n", "Epoch 299/1000\n", "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\n", "Epoch 300/1000\n", "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\n", "Epoch 301/1000\n", "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\n", "Epoch 302/1000\n", "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\n", "Epoch 303/1000\n", "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\n", "Epoch 304/1000\n", "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\n", "Epoch 305/1000\n", "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\n", "Epoch 306/1000\n", "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\n", "Epoch 307/1000\n", "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\n", "Epoch 308/1000\n", "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\n", "Epoch 309/1000\n", "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\n", "Epoch 310/1000\n", "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\n", "Epoch 311/1000\n", "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\n", "Epoch 312/1000\n", "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\n", "Epoch 313/1000\n", "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\n", "Epoch 314/1000\n", "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\n", "Epoch 315/1000\n", "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\n", "Epoch 316/1000\n", "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\n", "Epoch 317/1000\n", "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\n", "Epoch 318/1000\n", "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\n", "Epoch 319/1000\n", "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\n", "Epoch 320/1000\n", "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\n", "Epoch 321/1000\n", "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\n", "Epoch 322/1000\n", "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\n", "Epoch 323/1000\n", "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\n", "Epoch 324/1000\n", "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\n", "Epoch 325/1000\n", "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\n", "Epoch 326/1000\n", "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\n", "Epoch 327/1000\n", "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\n", "Epoch 328/1000\n", "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\n", "Epoch 329/1000\n", "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\n", "Epoch 330/1000\n", "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\n", "Epoch 331/1000\n", "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\n", "Epoch 332/1000\n", "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\n", "Epoch 333/1000\n", "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\n", "Epoch 334/1000\n", "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\n", "Epoch 335/1000\n", "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\n", "Epoch 336/1000\n", "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\n", "Epoch 337/1000\n", "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\n", "Epoch 338/1000\n", "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\n", "Epoch 339/1000\n", "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\n", "Epoch 340/1000\n", "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\n", "Epoch 341/1000\n", "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\n", "Epoch 342/1000\n", "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\n", "Epoch 343/1000\n", "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\n", "Epoch 344/1000\n", "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\n", "Epoch 345/1000\n", "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\n", "Epoch 346/1000\n", "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\n", "Epoch 347/1000\n", "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\n", "Epoch 348/1000\n", "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\n", "Epoch 349/1000\n", "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\n", "Epoch 350/1000\n", "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\n", "Epoch 351/1000\n", "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\n", "Epoch 352/1000\n", "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\n", "Epoch 353/1000\n", "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\n", "Epoch 354/1000\n", "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\n", "Epoch 355/1000\n", "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\n", "Epoch 356/1000\n", "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\n", "Epoch 357/1000\n", "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\n", "Epoch 358/1000\n", "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\n", "Epoch 359/1000\n", "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\n", "Epoch 360/1000\n", "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\n", "Epoch 361/1000\n", "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\n", "Epoch 362/1000\n", "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\n", "Epoch 363/1000\n", "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\n", "Epoch 364/1000\n", "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\n", "Epoch 365/1000\n", "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\n", "Epoch 366/1000\n", "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\n", "Epoch 367/1000\n", "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\n", "Epoch 368/1000\n", "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\n", "Epoch 369/1000\n", "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\n", "Epoch 370/1000\n", "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\n", "Epoch 371/1000\n", "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\n", "Epoch 372/1000\n", "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\n", "Epoch 373/1000\n", "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\n", "Epoch 374/1000\n", "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\n", "Epoch 375/1000\n", "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\n", "Epoch 376/1000\n", "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\n", "Epoch 377/1000\n", "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\n", "Epoch 378/1000\n", "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\n", "Epoch 379/1000\n", "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\n", "Epoch 380/1000\n", "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\n", "Epoch 381/1000\n", "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\n", "Epoch 382/1000\n", "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\n", "Epoch 383/1000\n", "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\n", "Epoch 384/1000\n", "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\n", "Epoch 385/1000\n", "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\n", "Epoch 386/1000\n", "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\n", "Epoch 387/1000\n", "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\n", "Epoch 388/1000\n", "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\n", "Epoch 389/1000\n", "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\n", "Epoch 390/1000\n", "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\n", "Epoch 391/1000\n", "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\n", "Epoch 392/1000\n", "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\n", "Epoch 393/1000\n", "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\n", "Epoch 394/1000\n", "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\n", "Epoch 395/1000\n", "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\n", "Epoch 396/1000\n", "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\n", "Epoch 397/1000\n", "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\n", "Epoch 398/1000\n", "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\n", "Epoch 399/1000\n", "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\n", "Epoch 400/1000\n", "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\n", "Epoch 401/1000\n", "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\n", "Epoch 402/1000\n", "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\n", "Epoch 403/1000\n", "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\n", "Epoch 404/1000\n", "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\n", "Epoch 405/1000\n", "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\n", "Epoch 406/1000\n", "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\n", "Epoch 407/1000\n", "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\n", "Epoch 408/1000\n", "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\n", "Epoch 409/1000\n", "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\n", "Epoch 410/1000\n", "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\n", "Epoch 411/1000\n", "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\n", "Epoch 412/1000\n", "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\n", "Epoch 413/1000\n", "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\n", "Epoch 414/1000\n", "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\n", "Epoch 415/1000\n", "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\n", "Epoch 416/1000\n", "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\n", "Epoch 417/1000\n", "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\n", "Epoch 418/1000\n", "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\n", "Epoch 419/1000\n", "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\n", "Epoch 420/1000\n", "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\n", "Epoch 421/1000\n", "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\n", "Epoch 422/1000\n", "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\n", "Epoch 423/1000\n", "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\n", "Epoch 424/1000\n", "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\n", "Epoch 425/1000\n", "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\n", "Epoch 426/1000\n", "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\n", "Epoch 427/1000\n", "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\n", "Epoch 428/1000\n", "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\n", "Epoch 429/1000\n", "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\n", "Epoch 430/1000\n", "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\n", "Epoch 431/1000\n", "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\n", "Epoch 432/1000\n", "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\n", "Epoch 433/1000\n", "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\n", "Epoch 434/1000\n", "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\n", "Epoch 435/1000\n", "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\n", "Epoch 436/1000\n", "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\n", "Epoch 437/1000\n", "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\n", "Epoch 438/1000\n", "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\n", "Epoch 439/1000\n", "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\n", "Epoch 440/1000\n", "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\n", "Epoch 441/1000\n", "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\n", "Epoch 442/1000\n", "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\n", "Epoch 443/1000\n", "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\n", "Epoch 444/1000\n", "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\n", "Epoch 445/1000\n", "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\n", "Epoch 446/1000\n", "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\n", "Epoch 447/1000\n", "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\n", "Epoch 448/1000\n", "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\n", "Epoch 449/1000\n", "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\n", "Epoch 450/1000\n", "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\n", "Epoch 451/1000\n", "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\n", "Epoch 452/1000\n", "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\n", "Epoch 453/1000\n", "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\n", "Epoch 454/1000\n", "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\n", "Epoch 455/1000\n", "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\n", "Epoch 456/1000\n", "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\n", "Epoch 457/1000\n", "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\n", "Epoch 458/1000\n", "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\n", "Epoch 459/1000\n", "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\n", "Epoch 460/1000\n", "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\n", "Epoch 461/1000\n", "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\n", "Epoch 462/1000\n", "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\n", "Epoch 463/1000\n", "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\n", "Epoch 464/1000\n", "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\n", "Epoch 465/1000\n", "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\n", "Epoch 466/1000\n", "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\n", "Epoch 467/1000\n", "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\n", "Epoch 468/1000\n", "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\n", "Epoch 469/1000\n", "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\n", "Epoch 470/1000\n", "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\n", "Epoch 471/1000\n", "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\n", "Epoch 472/1000\n", "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\n", "Epoch 473/1000\n", "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\n", "Epoch 474/1000\n", "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\n", "Epoch 475/1000\n", "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\n", "Epoch 476/1000\n", "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\n", "Epoch 477/1000\n", "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\n", "Epoch 478/1000\n", "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\n", "Epoch 479/1000\n", "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\n", "Epoch 480/1000\n", "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\n", "Epoch 481/1000\n", "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\n", "Epoch 482/1000\n", "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\n", "Epoch 483/1000\n", "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\n", "Epoch 484/1000\n", "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\n", "Epoch 485/1000\n", "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\n", "Epoch 486/1000\n", "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\n", "Epoch 487/1000\n", "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\n", "Epoch 488/1000\n", "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\n", "Epoch 489/1000\n", "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\n", "Epoch 490/1000\n", "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\n", "Epoch 491/1000\n", "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\n", "Epoch 492/1000\n", "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\n", "Epoch 493/1000\n", "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\n", "Epoch 494/1000\n", "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\n", "Epoch 495/1000\n", "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\n", "Epoch 496/1000\n", "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\n", "Epoch 497/1000\n", "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\n", "Epoch 498/1000\n", "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\n", "Epoch 499/1000\n", "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\n", "Epoch 500/1000\n", "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\n", "Epoch 501/1000\n", "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\n", "Epoch 502/1000\n", "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\n", "Epoch 503/1000\n", "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\n", "Epoch 504/1000\n", "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\n", "Epoch 505/1000\n", "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\n", "Epoch 506/1000\n", "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\n", "Epoch 507/1000\n", "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\n", "Epoch 508/1000\n", "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\n", "Epoch 509/1000\n", "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\n", "Epoch 510/1000\n", "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\n", "Epoch 511/1000\n", "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\n", "Epoch 512/1000\n", "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\n", "Epoch 513/1000\n", "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\n", "Epoch 514/1000\n", "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\n", "Epoch 515/1000\n", "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\n", "Epoch 516/1000\n", "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\n", "Epoch 517/1000\n", "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\n", "Epoch 518/1000\n", "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\n", "Epoch 519/1000\n", "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\n", "Epoch 520/1000\n", "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\n", "Epoch 521/1000\n", "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\n", "Epoch 522/1000\n", "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\n", "Epoch 523/1000\n", "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\n", "Epoch 524/1000\n", "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\n", "Epoch 525/1000\n", "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\n", "Epoch 526/1000\n", "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\n", "Epoch 527/1000\n", "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\n", "Epoch 528/1000\n", "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\n", "Epoch 529/1000\n", "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\n", "Epoch 530/1000\n", "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\n", "Epoch 531/1000\n", "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\n", "Epoch 532/1000\n", "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\n", "Epoch 533/1000\n", "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\n", "Epoch 534/1000\n", "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\n", "Epoch 535/1000\n", "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\n", "Epoch 536/1000\n", "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\n", "Epoch 537/1000\n", "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\n", "Epoch 538/1000\n", "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\n", "Epoch 539/1000\n", "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\n", "Epoch 540/1000\n", "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\n", "Epoch 541/1000\n", "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\n", "Epoch 542/1000\n", "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\n", "Epoch 543/1000\n", "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\n", "Epoch 544/1000\n", "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\n", "Epoch 545/1000\n", "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\n", "Epoch 546/1000\n", "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\n", "Epoch 547/1000\n", "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\n", "Epoch 548/1000\n", "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\n", "Epoch 549/1000\n", "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\n", "Epoch 550/1000\n", "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\n", "Epoch 551/1000\n", "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\n", "Epoch 552/1000\n", "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\n", "Epoch 553/1000\n", "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\n", "Epoch 554/1000\n", "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\n", "Epoch 555/1000\n", "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\n", "Epoch 556/1000\n", "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\n", "Epoch 557/1000\n", "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\n", "Epoch 558/1000\n", "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\n", "Epoch 559/1000\n", "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\n", "Epoch 560/1000\n", "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\n", "Epoch 561/1000\n", "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\n", "Epoch 562/1000\n", "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\n", "Epoch 563/1000\n", "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\n", "Epoch 564/1000\n", "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\n", "Epoch 565/1000\n", "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\n", "Epoch 566/1000\n", "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\n", "Epoch 567/1000\n", "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\n", "Epoch 568/1000\n", "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\n", "Epoch 569/1000\n", "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\n", "Epoch 570/1000\n", "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\n", "Epoch 571/1000\n", "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\n", "Epoch 572/1000\n", "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\n", "Epoch 573/1000\n", "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\n", "Epoch 574/1000\n", "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\n", "Epoch 575/1000\n", "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\n", "Epoch 576/1000\n", "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\n", "Epoch 577/1000\n", "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\n", "Epoch 578/1000\n", "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\n", "Epoch 579/1000\n", "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\n", "Epoch 580/1000\n", "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\n", "Epoch 581/1000\n", "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\n", "Epoch 582/1000\n", "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\n", "Epoch 583/1000\n", "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\n", "Epoch 584/1000\n", "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\n", "Epoch 585/1000\n", "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\n", "Epoch 586/1000\n", "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\n", "Epoch 587/1000\n", "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\n", "Epoch 588/1000\n", "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\n", "Epoch 589/1000\n", "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\n", "Epoch 590/1000\n", "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\n", "Epoch 591/1000\n", "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\n", "Epoch 592/1000\n", "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\n", "Epoch 593/1000\n", "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\n", "Epoch 594/1000\n", "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\n", "Epoch 595/1000\n", "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\n", "Epoch 596/1000\n", "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\n", "Epoch 597/1000\n", "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\n", "Epoch 598/1000\n", "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\n", "Epoch 599/1000\n", "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\n", "Epoch 600/1000\n", "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\n", "Epoch 601/1000\n", "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\n", "Epoch 602/1000\n", "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\n", "Epoch 603/1000\n", "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\n", "Epoch 604/1000\n", "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\n", "Epoch 605/1000\n", "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\n", "Epoch 606/1000\n", "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\n", "Epoch 607/1000\n", "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\n", "Epoch 608/1000\n", "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\n", "Epoch 609/1000\n", "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\n", "Epoch 610/1000\n", "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\n", "Epoch 611/1000\n", "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\n", "Epoch 612/1000\n", "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\n", "Epoch 613/1000\n", "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\n", "Epoch 614/1000\n", "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\n", "Epoch 615/1000\n", "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\n", "Epoch 616/1000\n", "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\n", "Epoch 617/1000\n", "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\n", "Epoch 618/1000\n", "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\n", "Epoch 619/1000\n", "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\n", "Epoch 620/1000\n", "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\n", "Epoch 621/1000\n", "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\n", "Epoch 622/1000\n", "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\n", "Epoch 623/1000\n", "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\n", "Epoch 624/1000\n", "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\n", "Epoch 625/1000\n", "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\n", "Epoch 626/1000\n", "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\n", "Epoch 627/1000\n", "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\n", "Epoch 628/1000\n", "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\n", "Epoch 629/1000\n", "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\n", "Epoch 630/1000\n", "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\n", "Epoch 631/1000\n", "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\n", "Epoch 632/1000\n", "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\n", "Epoch 633/1000\n", "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\n", "Epoch 634/1000\n", "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\n", "Epoch 635/1000\n", "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\n", "Epoch 636/1000\n", "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\n", "Epoch 637/1000\n", "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\n", "Epoch 638/1000\n", "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\n", "Epoch 639/1000\n", "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\n", "Epoch 640/1000\n", "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\n", "Epoch 641/1000\n", "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\n", "Epoch 642/1000\n", "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\n", "Epoch 643/1000\n", "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\n", "Epoch 644/1000\n", "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\n", "Epoch 645/1000\n", "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\n", "Epoch 646/1000\n", "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\n", "Epoch 647/1000\n", "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\n", "Epoch 648/1000\n", "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\n", "Epoch 649/1000\n", "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\n", "Epoch 650/1000\n", "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\n", "Epoch 651/1000\n", "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\n", "Epoch 652/1000\n", "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\n", "Epoch 653/1000\n", "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\n", "Epoch 654/1000\n", "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\n", "Epoch 655/1000\n", "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\n", "Epoch 656/1000\n", "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\n", "Epoch 657/1000\n", "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\n", "Epoch 658/1000\n", "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\n", "Epoch 659/1000\n", "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\n", "Epoch 660/1000\n", "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\n", "Epoch 661/1000\n", "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\n", "Epoch 662/1000\n", "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\n", "Epoch 663/1000\n", "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\n", "Epoch 664/1000\n", "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\n", "Epoch 665/1000\n", "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\n", "Epoch 666/1000\n", "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\n", "Epoch 667/1000\n", "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\n", "Epoch 668/1000\n", "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\n", "Epoch 669/1000\n", "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\n", "Epoch 670/1000\n", "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\n", "Epoch 671/1000\n", "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\n", "Epoch 672/1000\n", "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\n", "Epoch 673/1000\n", "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\n", "Epoch 674/1000\n", "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\n", "Epoch 675/1000\n", "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\n", "Epoch 676/1000\n", "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\n", "Epoch 677/1000\n", "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\n", "Epoch 678/1000\n", "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\n", "Epoch 679/1000\n", "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\n", "Epoch 680/1000\n", "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\n", "Epoch 681/1000\n", "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\n", "Epoch 682/1000\n", "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\n", "Epoch 683/1000\n", "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\n", "Epoch 684/1000\n", "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\n", "Epoch 685/1000\n", "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\n", "Epoch 686/1000\n", "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\n", "Epoch 687/1000\n", "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\n", "Epoch 688/1000\n", "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\n", "Epoch 689/1000\n", "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\n", "Epoch 690/1000\n", "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\n", "Epoch 691/1000\n", "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\n", "Epoch 692/1000\n", "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\n", "Epoch 693/1000\n", "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\n", "Epoch 694/1000\n", "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\n", "Epoch 695/1000\n", "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\n", "Epoch 696/1000\n", "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\n", "Epoch 697/1000\n", "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\n", "Epoch 698/1000\n", "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\n", "Epoch 699/1000\n", "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\n", "Epoch 700/1000\n", "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\n", "Epoch 701/1000\n", "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\n", "Epoch 702/1000\n", "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\n", "Epoch 703/1000\n", "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\n", "Epoch 704/1000\n", "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\n", "Epoch 705/1000\n", "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\n", "Epoch 706/1000\n", "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\n", "Epoch 707/1000\n", "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\n", "Epoch 708/1000\n", "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\n", "Epoch 709/1000\n", "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\n", "Epoch 710/1000\n", "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\n", "Epoch 711/1000\n", "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\n", "Epoch 712/1000\n", "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\n", "Epoch 713/1000\n", "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\n", "Epoch 714/1000\n", "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\n", "Epoch 715/1000\n", "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\n", "Epoch 716/1000\n", "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\n", "Epoch 717/1000\n", "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\n", "Epoch 718/1000\n", "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\n", "Epoch 719/1000\n", "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\n", "Epoch 720/1000\n", "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\n", "Epoch 721/1000\n", "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\n", "Epoch 722/1000\n", "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\n", "Epoch 723/1000\n", "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\n", "Epoch 724/1000\n", "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\n", "Epoch 725/1000\n", "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\n", "Epoch 726/1000\n", "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\n", "Epoch 727/1000\n", "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\n", "Epoch 728/1000\n", "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\n", "Epoch 729/1000\n", "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\n", "Epoch 730/1000\n", "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\n", "Epoch 731/1000\n", "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\n", "Epoch 732/1000\n", "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\n", "Epoch 733/1000\n", "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\n", "Epoch 734/1000\n", "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\n", "Epoch 735/1000\n", "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\n", "Epoch 736/1000\n", "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\n", "Epoch 737/1000\n", "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\n", "Epoch 738/1000\n", "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\n", "Epoch 739/1000\n", "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\n", "Epoch 740/1000\n", "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\n", "Epoch 741/1000\n", "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\n", "Epoch 742/1000\n", "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\n", "Epoch 743/1000\n", "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\n", "Epoch 744/1000\n", "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\n", "Epoch 745/1000\n", "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\n", "Epoch 746/1000\n", "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\n", "Epoch 747/1000\n", "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\n", "Epoch 748/1000\n", "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\n", "Epoch 749/1000\n", "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\n", "Epoch 750/1000\n", "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\n", "Epoch 751/1000\n", "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\n", "Epoch 752/1000\n", "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\n", "Epoch 753/1000\n", "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\n", "Epoch 754/1000\n", "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\n", "Epoch 755/1000\n", "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\n", "Epoch 756/1000\n", "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\n", "Epoch 757/1000\n", "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\n", "Epoch 758/1000\n", "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\n", "Epoch 759/1000\n", "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\n", "Epoch 760/1000\n", "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\n", "Epoch 761/1000\n", "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\n", "Epoch 762/1000\n", "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\n", "Epoch 763/1000\n", "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\n", "Epoch 764/1000\n", "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\n", "Epoch 765/1000\n", "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\n", "Epoch 766/1000\n", "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\n", "Epoch 767/1000\n", "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\n", "Epoch 768/1000\n", "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\n", "Epoch 769/1000\n", "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\n", "Epoch 770/1000\n", "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\n", "Epoch 771/1000\n", "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\n", "Epoch 772/1000\n", "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\n", "Epoch 773/1000\n", "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\n", "Epoch 774/1000\n", "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\n", "Epoch 775/1000\n", "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\n", "Epoch 776/1000\n", "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\n", "Epoch 777/1000\n", "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\n", "Epoch 778/1000\n", "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\n", "Epoch 779/1000\n", "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\n", "Epoch 780/1000\n", "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\n", "Epoch 781/1000\n", "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\n", "Epoch 782/1000\n", "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\n", "Epoch 783/1000\n", "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\n", "Epoch 784/1000\n", "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\n", "Epoch 785/1000\n", "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\n", "Epoch 786/1000\n", "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\n", "Epoch 787/1000\n", "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\n", "Epoch 788/1000\n", "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\n", "Epoch 789/1000\n", "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\n", "Epoch 790/1000\n", "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\n", "Epoch 791/1000\n", "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\n", "Epoch 792/1000\n", "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\n", "Epoch 793/1000\n", "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\n", "Epoch 794/1000\n", "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\n", "Epoch 00794: early stopping\n", "8. Save training results...\n", "=== Training completed! ===\n", "Best model: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out/E1000best_model.h5\n", "Training history: /picb/bigdata/project/miaoyuanyuan/train/XChrom_test/XChrom/source/Tutorials/data/4_pred_newCondition/train_out/history.pickle\n" ] } ], "source": [ "history = xc.tr.train_XChrom(\n", " input_folder='./data/4_pred_newCondition/train_data/',\n", " cell_embedding_ad='./data/4_pred_newCondition/pbmc10k_rna_harmony.h5ad',\n", " cellembed_raw='X_pca_harmony',\n", " out_path='./data/4_pred_newCondition/train_out/',\n", " epochs = 1000,\n", " verbose = 1\n", ")" ] }, { "cell_type": "markdown", "id": "bce7e85c-34be-4866-831c-5c4555335827", "metadata": {}, "source": [ "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). \n", "\n", "The metrics computed during training are saved in `./data/4_pred_newCondition/train_out/history.pickle`. Load them with: \n", "\n", "```python\n", "import pickle\n", "with open('./data/4_pred_newCondition/train_out/history.pickle', 'rb') as f:\n", " history = pickle.load(f)\n", "```\n", "\n", "You can then use this `history` object to plot training/validation metrics (e.g., loss, auROC/auPRC, NS/LS) over epochs. \n", "\n", "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. " ] }, { "cell_type": "code", "execution_count": 5, "id": "0b12fcff-a22d-4767-b2f1-2ec770cd378b", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "xc.pl.plot_train_history(\n", " history = history['history'],\n", " savefig = True,\n", " out_file = './data/4_pred_newCondition/train_out/train_history_plot.pdf'\n", " )" ] }, { "cell_type": "markdown", "id": "70bdc417-e75e-4d76-b675-9f4d784c9717", "metadata": {}, "source": [ "### 4. Calculate TF activity\n", "We performed motif insertion on trained XChrom to compute a TF activity score for each TF for each cell. \n", "\n", "- 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. \n", "\n", "- For this，you must install fasta_ushuffle first with: `conda install bioconda::fasta_ushuffle` " ] }, { "cell_type": "code", "execution_count": 6, "id": "5fe46181-9ab6-4bf8-b13c-5b83f5ba3ca4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== Start preparing motif data ===\n", "1. Read BED file: ./data/4_pred_newCondition/train_data/peaks.bed\n", "Sampled 1000 regions from ./data/4_pred_newCondition/train_data/peaks.bed\n", "2. Extract background sequences...\n", "Extracting sequences from BED file...\n", "Reference genome: /picb/bigdata/project/miaoyuanyuan/hg38.fa\n", "Sequence length: 1344\n", "Consider strand information: False\n", "Successfully extracted 1000 sequences\n", "Writing to FASTA file: data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta\n", "FASTA file saved to: data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta\n", "Number of sequences written: 1000\n", "Extracted 1000 sequences, saved to data/4_pred_newCondition/motif_fasta/ref_peaks1000.fasta\n", "3. Generate shuffled background sequences...\n", "Using fasta_ushuffle from: /home/miaoyuanyuan/miniconda3/envs/py3.8_tf2.6.0/bin/fasta_ushuffle\n", "Dinucleotide shuffled 1000 sequences, saved to data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta\n", "4. Read motif file(meme format)...\n", "Read 1065 motifs from ./data/4_pred_newCondition/Homo_sapiens.meme\n", "5. Generate motif inserted sequences...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Processing motifs: 100%|████████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [04:59<00:00, 3.56it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "=== motif data preparation completed ===\n", "Background sequence file: data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta\n", "Motif inserted sequence directory: data/4_pred_newCondition/motif_fasta/shuffled_peaks_motifs\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "seq_path = xc.tl.generate_tf_activity_data(\n", " bed_file = './data/4_pred_newCondition/train_data/peaks.bed', ## to generate background sequence\n", " input_fasta = '/picb/bigdata/project/miaoyuanyuan/hg38.fa',\n", " motif_file = './data/4_pred_newCondition/Homo_sapiens.meme',\n", " output_dir = './data/4_pred_newCondition/motif_fasta/',\n", " n_samples = 1000,\n", " n_motif_instances = 1000)" ] }, { "cell_type": "markdown", "id": "fb8f8b63-5a39-4be6-abf3-a866cf268df6", "metadata": {}, "source": [ "Note: Since the COVID-19 data lacks paired scATAC data, background sequences can only be sampled from the training set. " ] }, { "cell_type": "code", "execution_count": 8, "id": "e3090d8c-4f81-4187-a92b-31799b965d19", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== Start calculating TF Activity ===\n", "1. Prepare raw cell embedding...\n", "2. Generate motif insertion sequence h5 files...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Generating H5 files: 100%|██████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [06:56<00:00, 2.56it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Found 1065 motif files\n", "3. Generate background sequence h5 file...\n", "Generating background sequence h5 file...\n", "4. Prepare data for XChrom model input...\n", "Converting adata.X to dense array. For large datasets, consider pre-computing and saving as sparse matrix.\n", "5. Load trained model...\n", "6. Calculate background sequence prediction...\n", "7. Calculate motif insertion scores...\n", "Processing 1065 motif files...\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 1065/1065 [5:00:22<00:00, 16.92s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "8. Save results...\n", "=== Done! Results saved to: data/4_pred_newCondition/analysis_out/tf_activity.h5ad ===\n", "TF activity matrix shape: (90312, 1065) (cells × motifs)\n" ] } ], "source": [ "covid_rna = sc.read_h5ad('./data/4_pred_newCondition/covid_rna_harmony.h5ad')\n", "tf_act = xc.tl.calc_tf_activity(\n", " motif_dir = './data/4_pred_newCondition/motif_fasta/shuffled_peaks_motifs/',\n", " background_fasta = './data/4_pred_newCondition/motif_fasta/shuffled_peaks.fasta',\n", " model_path = './data/4_pred_newCondition/train_out/E1000best_model.h5',\n", " ad_rna = covid_rna,\n", " output_file = './data/4_pred_newCondition/analysis_out/tf_activity.h5ad',\n", " cell_embed_raw = 'X_pca_harmony',\n", " regenerate_motif_h5 = True,\n", " regenerate_bg_h5 = True)" ] }, { "cell_type": "markdown", "id": "7a9457a1-4a06-419a-8ff4-d0dfa5b92acc", "metadata": {}, "source": [ "Note: This process will take a long time\n", "\n", "If you do not need to calculate activities for all motifs, you can keep only the motif files you require in the `motif_dir`. \n", "\n", "Set `regenerate_bg_h5=False` if you have already generated the background sequences in H5 format,\n", "Set `regenerate_motif_h5=False` if you have already generated H5 files for each motif." ] }, { "cell_type": "markdown", "id": "9e8689fd-c79f-4333-bfae-8ed1cb758680", "metadata": {}, "source": [ "### 5. Check TF activity in different cell types" ] }, { "cell_type": "code", "execution_count": 9, "id": "c8470e13-eab2-41c8-9575-5c3b4f4f6a7d", "metadata": {}, "outputs": [], "source": [ "covid_rna = sc.read_h5ad('./data/4_pred_newCondition/covid_rna_harmony.h5ad')\n", "tf_act = sc.read_h5ad('./data/4_pred_newCondition/analysis_out/tf_activity.h5ad')" ] }, { "cell_type": "code", "execution_count": 10, "id": "590e61c9-9668-421a-8c02-22f8e10140e8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Plot saved to: ./CEBPB_activity.pdf\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 374, "width": 956 } }, "output_type": "display_data" } ], "source": [ "xc.pl.plot_motif_activity(\n", " cell_embedding_ad = covid_rna,\n", " celltype_key = 'celltypeL0',\n", " tf_act_raw = tf_act,\n", " motif_name = 'CEBPB',\n", " save_path = './CEBPB_activity.pdf'\n", ")" ] }, { "cell_type": "markdown", "id": "3b7f9512-cde2-4a49-89fc-c53ebade2c0b", "metadata": {}, "source": [ "The `plot_motif_activity()` function performs z-score normalization of the calculated TF activity across cell types. In the resulting visualization:\n", "- **Red** indicates that CEBPB shows relatively higher activity in Mono\n", "- **Blue** indicates relatively lower activity\n", "\n", "This normalization allows for clear comparison of TF activity patterns across different cell types and conditions." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.15" } }, "nbformat": 4, "nbformat_minor": 5 }