Live Found logdir. Deleting previous model Estimating enzyme shift in input file Current estimated shift: +4/-5 awk -v OFS="\t" '{if ($6=="+"){print $1,$2+0,$3,$4,$5,$6} else if ($6=="-") {print $1,$2,$3+1,$4,$5,$6}}' | sort -k1,1 | bedtools genomecov -bg -5 -i stdin -g /oak/stanford/groups/akundaje/soumyak/refs/hg38/GRCh38_EBV.chrom.sizes.tsv | LC_COLLATE="C" sort -k1,1 -k2,2n Making BedGraph (Filter chromosomes not in reference fasta) Making Bigwig non zero bigwig entries in the given chromosome: 134678 evaluating hyperparameters on the following chromosomes ['chr1', 'chr2', 'chr3', 'chr4', 'chr5', 'chr6', 'chr8', 'chr9', 'chr11', 'chr12', 'chr14', 'chr15', 'chr16', 'chr20', 'chr22', 'chrY', 'chr10', 'chr18'] Number of peaks input: 43615 Number of peaks filtered because the input/output is on the edge: 0 Number of peaks being used: 43615 Number of peaks input: 10928 Number of peaks filtered because the input/output is on the edge: 0 Number of peaks being used: 10928 Number of non peaks input: 87230 Number of non peaks filtered because the input/output is on the edge: 0 Number of non peaks being used: 87230 Number of non peaks input: 10928 Number of non peaks filtered because the input/output is on the edge: 0 Number of non peaks being used: 10928 Number of peaks after removing outliers: 43610 Number of nonpeaks after removing outliers: 35711 got the model Model: "functional_1" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== sequence (InputLayer) [(None, 2114, 4)] 0 [] bpnet_1st_conv (Conv1D) (None, 2094, 128) 10880 ['sequence[0][0]'] bpnet_1conv (Conv1D) (None, 2090, 128) 49280 ['bpnet_1st_conv[0][0]'] bpnet_1crop (Cropping1D) (None, 2090, 128) 0 ['bpnet_1st_conv[0][0]'] add (Add) (None, 2090, 128) 0 ['bpnet_1conv[0][0]', 'bpnet_1crop[0][0]'] bpnet_2conv (Conv1D) (None, 2082, 128) 49280 ['add[0][0]'] bpnet_2crop (Cropping1D) (None, 2082, 128) 0 ['add[0][0]'] add_1 (Add) (None, 2082, 128) 0 ['bpnet_2conv[0][0]', 'bpnet_2crop[0][0]'] bpnet_3conv (Conv1D) (None, 2066, 128) 49280 ['add_1[0][0]'] bpnet_3crop (Cropping1D) (None, 2066, 128) 0 ['add_1[0][0]'] add_2 (Add) (None, 2066, 128) 0 ['bpnet_3conv[0][0]', 'bpnet_3crop[0][0]'] bpnet_4conv (Conv1D) (None, 2034, 128) 49280 ['add_2[0][0]'] bpnet_4crop (Cropping1D) (None, 2034, 128) 0 ['add_2[0][0]'] add_3 (Add) (None, 2034, 128) 0 ['bpnet_4conv[0][0]', 'bpnet_4crop[0][0]'] prof_out_precrop (Conv1D) (None, 1960, 1) 9601 ['add_3[0][0]'] logits_profile_predictions_pre (None, 1000, 1) 0 ['prof_out_precrop[0][0]'] flatten (Cropping1D) gap (GlobalAveragePooling1D) (None, 128) 0 ['add_3[0][0]'] logits_profile_predictions (Fl (None, 1000) 0 ['logits_profile_predictions_pref atten) latten[0][0]'] logcount_predictions (Dense) (None, 1) 129 ['gap[0][0]'] ================================================================================================== Total params: 217,730 Trainable params: 217,730 Non-trainable params: 0 __________________________________________________________________________________________________ Predicting within adjust counts 1/1116 [..............................] - ETA: 29:07 6/1116 [..............................] - ETA: 12s  10/1116 [..............................] - ETA: 13s 14/1116 [..............................] - ETA: 13s 18/1116 [..............................] - ETA: 13s 23/1116 [..............................] - ETA: 13s 27/1116 [..............................] - ETA: 13s 31/1116 [..............................] - ETA: 13s 35/1116 [..............................] - ETA: 13s 39/1116 [>.............................] - ETA: 13s 43/1116 [>.............................] - ETA: 13s 47/1116 [>.............................] - ETA: 13s 51/1116 [>.............................] - ETA: 13s 55/1116 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1112/1116 [============================>.] - ETA: 0s 1116/1116 [==============================] - ETA: 0s 1116/1116 [==============================] - 16s 13ms/step got the model loading peaks... got split:test for bed regions:(10928, 10) 0/171 100/171 Bias model pearsonr performance in peaks is: -0.06 {'counts_loss_weight': '1.0', 'filters': '512', 'n_dil_layers': '8', 'bias_model_path': '/oak/stanford/groups/akundaje/projects/neuro-variants/chrombpnet_models/ameen_2022/K562_bias/ameen_2022.NC/fold_4/models/bias_model_scaled.h5', 'inputlen': '2114', 'outputlen': '1000', 'max_jitter': '500', 'chr_fold_path': '/oak/stanford/groups/akundaje/soumyak/refs/hg38/splits/fold_4.json', 'negative_sampling_ratio': '0.1'} got the model loading peaks... got split:train for bed regions:(39839, 10) loading nonpeaks... got split:train for bed regions:(32673, 10) loading peaks... got split:valid for bed regions:(3771, 10) loading nonpeaks... got split:valid for bed regions:(3038, 10) Epoch 1/50 1/685 [..............................] - ETA: 1:13:50 - loss: 65.6447 - logits_profile_predictions_loss: 64.0759 - logcount_predictions_loss: 1.5688 2/685 [..............................] - ETA: 8:14 - loss: 771.8285 - logits_profile_predictions_loss: 73.2733 - logcount_predictions_loss: 698.5551 3/685 [..............................] - ETA: 8:13 - loss: 538.9144 - logits_profile_predictions_loss: 72.7551 - logcount_predictions_loss: 466.1593 4/685 [..............................] - ETA: 8:11 - loss: 418.2324 - logits_profile_predictions_loss: 68.2268 - logcount_predictions_loss: 350.0055 5/685 [..............................] - ETA: 8:10 - loss: 349.2958 - logits_profile_predictions_loss: 68.8269 - logcount_predictions_loss: 280.4689 6/685 [..............................] - ETA: 8:08 - loss: 302.1821 - logits_profile_predictions_loss: 68.1034 - logcount_predictions_loss: 234.0787 7/685 [..............................] - ETA: 8:07 - loss: 270.6853 - logits_profile_predictions_loss: 69.6458 - logcount_predictions_loss: 201.0395 8/685 [..............................] - ETA: 8:06 - loss: 245.8848 - logits_profile_predictions_loss: 69.6691 - logcount_predictions_loss: 176.2157 9/685 [..............................] - ETA: 8:04 - loss: 225.7781 - logits_profile_predictions_loss: 68.9221 - logcount_predictions_loss: 156.8560 10/685 [..............................] - ETA: 8:04 - loss: 209.5197 - logits_profile_predictions_loss: 68.1586 - logcount_predictions_loss: 141.3611 11/685 [..............................] - ETA: 8:02 - loss: 196.6871 - logits_profile_predictions_loss: 67.9625 - logcount_predictions_loss: 128.7246 12/685 [..............................] - ETA: 8:02 - loss: 184.1842 - logits_profile_predictions_loss: 66.0726 - logcount_predictions_loss: 118.1116 13/685 [..............................] - ETA: 8:01 - loss: 175.5224 - logits_profile_predictions_loss: 66.3132 - logcount_predictions_loss: 109.2092 14/685 [..............................] - ETA: 8:00 - loss: 169.5020 - logits_profile_predictions_loss: 67.8584 - logcount_predictions_loss: 101.6436 15/685 [..............................] - ETA: 7:59 - loss: 162.2770 - logits_profile_predictions_loss: 67.2795 - logcount_predictions_loss: 94.9975  16/685 [..............................] - ETA: 7:58 - loss: 156.4086 - logits_profile_predictions_loss: 67.2071 - logcount_predictions_loss: 89.2015 17/685 [..............................] - ETA: 7:57 - loss: 151.5978 - logits_profile_predictions_loss: 67.4877 - logcount_predictions_loss: 84.1100 18/685 [..............................] - ETA: 7:56 - loss: 147.7444 - logits_profile_predictions_loss: 68.1504 - logcount_predictions_loss: 79.5940 19/685 [..............................] - ETA: 7:55 - loss: 143.6846 - logits_profile_predictions_loss: 68.1586 - logcount_predictions_loss: 75.5259 20/685 [..............................] - ETA: 7:54 - loss: 139.6717 - logits_profile_predictions_loss: 67.8153 - logcount_predictions_loss: 71.8564 21/685 [..............................] - ETA: 7:54 - loss: 136.1487 - logits_profile_predictions_loss: 67.6102 - logcount_predictions_loss: 68.5384 22/685 [..............................] - ETA: 7:53 - loss: 132.8086 - logits_profile_predictions_loss: 67.2952 - logcount_predictions_loss: 65.5134 23/685 [>.............................] - ETA: 7:52 - loss: 130.3378 - logits_profile_predictions_loss: 67.5564 - logcount_predictions_loss: 62.7814 24/685 [>.............................] - ETA: 7:51 - loss: 127.8166 - logits_profile_predictions_loss: 67.5542 - logcount_predictions_loss: 60.2624 25/685 [>.............................] - ETA: 7:50 - loss: 125.2001 - logits_profile_predictions_loss: 67.2663 - logcount_predictions_loss: 57.9338 26/685 [>.............................] - ETA: 7:50 - loss: 122.7875 - logits_profile_predictions_loss: 67.0042 - logcount_predictions_loss: 55.7832 27/685 [>.............................] - ETA: 7:49 - loss: 120.9530 - logits_profile_predictions_loss: 67.1438 - logcount_predictions_loss: 53.8092 28/685 [>.............................] - ETA: 7:48 - loss: 118.9570 - logits_profile_predictions_loss: 66.9968 - logcount_predictions_loss: 51.9602 29/685 [>.............................] - ETA: 7:48 - loss: 117.2579 - logits_profile_predictions_loss: 67.0060 - logcount_predictions_loss: 50.2518 30/685 [>.............................] - ETA: 7:47 - loss: 115.3988 - logits_profile_predictions_loss: 66.7569 - logcount_predictions_loss: 48.6419 31/685 [>.............................] - ETA: 7:46 - loss: 113.7653 - logits_profile_predictions_loss: 66.6154 - logcount_predictions_loss: 47.1498 32/685 [>.............................] - ETA: 7:46 - loss: 111.6880 - logits_profile_predictions_loss: 65.9713 - logcount_predictions_loss: 45.7167 33/685 [>.............................] - ETA: 7:45 - loss: 110.1318 - logits_profile_predictions_loss: 65.7387 - logcount_predictions_loss: 44.3930 34/685 [>.............................] - ETA: 7:44 - loss: 108.5950 - 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[============================>.] - ETA: 2s - loss: 69.7304 - logits_profile_predictions_loss: 66.6319 - logcount_predictions_loss: 3.0986 683/685 [============================>.] - ETA: 1s - loss: 69.7376 - logits_profile_predictions_loss: 66.6424 - logcount_predictions_loss: 3.0953 684/685 [============================>.] - ETA: 0s - loss: 69.7397 - logits_profile_predictions_loss: 66.6479 - logcount_predictions_loss: 3.0919 685/685 [==============================] - ETA: 0s - loss: 69.7417 - logits_profile_predictions_loss: 66.6533 - logcount_predictions_loss: 3.0885 Epoch 1: val_loss improved from inf to 68.76920, saving model to /oak/stanford/groups/akundaje/projects/neuro-variants/chrombpnet_models/ameen_2022/K562_bias/ameen_2022.NC/fold_4/models/chrombpnet.h5  685/685 [==============================] - 539s 778ms/step - loss: 69.7417 - logits_profile_predictions_loss: 66.6533 - logcount_predictions_loss: 3.0885 - val_loss: 68.7692 - val_logits_profile_predictions_loss: 68.0207 - 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[..............................] - ETA: 7:57 - loss: 65.8898 - logits_profile_predictions_loss: 65.1497 - logcount_predictions_loss: 0.7401 22/685 [..............................] - ETA: 7:56 - loss: 66.0594 - logits_profile_predictions_loss: 65.3218 - logcount_predictions_loss: 0.7376 23/685 [>.............................] - ETA: 7:55 - loss: 65.4887 - logits_profile_predictions_loss: 64.7583 - logcount_predictions_loss: 0.7304 24/685 [>.............................] - ETA: 7:55 - loss: 65.7451 - logits_profile_predictions_loss: 65.0097 - logcount_predictions_loss: 0.7354 25/685 [>.............................] - ETA: 7:54 - loss: 65.2409 - logits_profile_predictions_loss: 64.5068 - logcount_predictions_loss: 0.7341 26/685 [>.............................] - ETA: 7:53 - loss: 65.2451 - logits_profile_predictions_loss: 64.5081 - logcount_predictions_loss: 0.7370 27/685 [>.............................] - ETA: 7:53 - loss: 65.3654 - logits_profile_predictions_loss: 64.6239 - 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[=>............................] - ETA: 7:40 - loss: 65.6999 - logits_profile_predictions_loss: 64.9596 - logcount_predictions_loss: 0.7403 49/685 [=>............................] - ETA: 7:40 - loss: 65.8492 - logits_profile_predictions_loss: 65.1053 - logcount_predictions_loss: 0.7439 50/685 [=>............................] - ETA: 7:39 - loss: 65.8766 - logits_profile_predictions_loss: 65.1321 - logcount_predictions_loss: 0.7445 51/685 [=>............................] - ETA: 7:38 - loss: 65.9254 - logits_profile_predictions_loss: 65.1805 - logcount_predictions_loss: 0.7449 52/685 [=>............................] - ETA: 7:38 - loss: 65.7539 - logits_profile_predictions_loss: 65.0139 - logcount_predictions_loss: 0.7400 53/685 [=>............................] - ETA: 7:37 - loss: 65.8478 - logits_profile_predictions_loss: 65.1090 - logcount_predictions_loss: 0.7388 54/685 [=>............................] - ETA: 7:37 - loss: 65.8195 - logits_profile_predictions_loss: 65.0786 - 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[============================>.] - ETA: 5s - loss: 64.7370 - logits_profile_predictions_loss: 64.1657 - logcount_predictions_loss: 0.5714 678/685 [============================>.] - ETA: 5s - loss: 64.7234 - logits_profile_predictions_loss: 64.1522 - logcount_predictions_loss: 0.5713 679/685 [============================>.] - ETA: 4s - loss: 64.7104 - logits_profile_predictions_loss: 64.1397 - logcount_predictions_loss: 0.5708 680/685 [============================>.] - ETA: 3s - loss: 64.6979 - logits_profile_predictions_loss: 64.1273 - logcount_predictions_loss: 0.5707 681/685 [============================>.] - ETA: 2s - loss: 64.6888 - logits_profile_predictions_loss: 64.1181 - logcount_predictions_loss: 0.5708 682/685 [============================>.] - ETA: 2s - loss: 64.7098 - logits_profile_predictions_loss: 64.1390 - logcount_predictions_loss: 0.5708 683/685 [============================>.] - ETA: 1s - loss: 64.6885 - logits_profile_predictions_loss: 64.1177 - logcount_predictions_loss: 0.5708 684/685 [============================>.] - ETA: 0s - loss: 64.6897 - logits_profile_predictions_loss: 64.1191 - logcount_predictions_loss: 0.5706 685/685 [==============================] - ETA: 0s - loss: 64.6761 - logits_profile_predictions_loss: 64.1054 - logcount_predictions_loss: 0.5707 Epoch 3: val_loss improved from 67.16024 to 66.34270, saving model to /oak/stanford/groups/akundaje/projects/neuro-variants/chrombpnet_models/ameen_2022/K562_bias/ameen_2022.NC/fold_4/models/chrombpnet.h5  685/685 [==============================] - 534s 780ms/step - loss: 64.6761 - logits_profile_predictions_loss: 64.1054 - logcount_predictions_loss: 0.5707 - val_loss: 66.3427 - val_logits_profile_predictions_loss: 65.8776 - val_logcount_predictions_loss: 0.4651 Epoch 4/50 1/685 [..............................] - ETA: 8:20 - loss: 64.6659 - logits_profile_predictions_loss: 63.9907 - logcount_predictions_loss: 0.6752 2/685 [..............................] - ETA: 8:08 - loss: 63.7322 - logits_profile_predictions_loss: 63.0995 - logcount_predictions_loss: 0.6326 3/685 [..............................] - ETA: 8:10 - loss: 67.5512 - logits_profile_predictions_loss: 66.8873 - logcount_predictions_loss: 0.6638 4/685 [..............................] - ETA: 8:09 - loss: 68.6188 - logits_profile_predictions_loss: 67.9868 - logcount_predictions_loss: 0.6320 5/685 [..............................] - ETA: 8:08 - loss: 67.9264 - logits_profile_predictions_loss: 67.3101 - logcount_predictions_loss: 0.6163 6/685 [..............................] - ETA: 8:08 - loss: 67.7868 - logits_profile_predictions_loss: 67.1880 - logcount_predictions_loss: 0.5988 7/685 [..............................] - ETA: 8:07 - loss: 68.0206 - logits_profile_predictions_loss: 67.4487 - logcount_predictions_loss: 0.5720 8/685 [..............................] - ETA: 8:07 - loss: 66.8447 - logits_profile_predictions_loss: 66.2797 - logcount_predictions_loss: 0.5650 9/685 [..............................] - ETA: 8:06 - loss: 66.3814 - logits_profile_predictions_loss: 65.8079 - logcount_predictions_loss: 0.5735 10/685 [..............................] - ETA: 8:05 - loss: 65.9433 - logits_profile_predictions_loss: 65.3792 - logcount_predictions_loss: 0.5641 11/685 [..............................] - ETA: 8:04 - loss: 66.8467 - logits_profile_predictions_loss: 66.2648 - logcount_predictions_loss: 0.5819 12/685 [..............................] - ETA: 8:04 - loss: 66.0253 - logits_profile_predictions_loss: 65.4593 - logcount_predictions_loss: 0.5660 13/685 [..............................] - ETA: 8:03 - loss: 65.6966 - logits_profile_predictions_loss: 65.1260 - logcount_predictions_loss: 0.5706 14/685 [..............................] - ETA: 8:03 - loss: 65.8234 - logits_profile_predictions_loss: 65.2578 - logcount_predictions_loss: 0.5656 15/685 [..............................] - ETA: 8:02 - loss: 66.3328 - logits_profile_predictions_loss: 65.7671 - 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[>.............................] - ETA: 7:48 - loss: 64.3011 - logits_profile_predictions_loss: 63.7354 - logcount_predictions_loss: 0.5658 37/685 [>.............................] - ETA: 7:48 - loss: 64.1564 - logits_profile_predictions_loss: 63.5912 - logcount_predictions_loss: 0.5652 38/685 [>.............................] - ETA: 7:47 - loss: 64.2498 - logits_profile_predictions_loss: 63.6871 - logcount_predictions_loss: 0.5627 39/685 [>.............................] - ETA: 7:46 - loss: 64.3241 - logits_profile_predictions_loss: 63.7629 - logcount_predictions_loss: 0.5612 40/685 [>.............................] - ETA: 7:46 - loss: 64.1689 - logits_profile_predictions_loss: 63.6096 - logcount_predictions_loss: 0.5594 41/685 [>.............................] - ETA: 7:45 - loss: 64.1280 - logits_profile_predictions_loss: 63.5708 - logcount_predictions_loss: 0.5572 42/685 [>.............................] - ETA: 7:44 - loss: 64.0379 - logits_profile_predictions_loss: 63.4811 - 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[=>............................] - ETA: 7:34 - loss: 64.1145 - logits_profile_predictions_loss: 63.5737 - logcount_predictions_loss: 0.5408 64/685 [=>............................] - ETA: 7:34 - loss: 64.2076 - logits_profile_predictions_loss: 63.6677 - logcount_predictions_loss: 0.5399 65/685 [=>............................] - ETA: 7:34 - loss: 64.2815 - logits_profile_predictions_loss: 63.7413 - logcount_predictions_loss: 0.5402 66/685 [=>............................] - ETA: 7:33 - loss: 64.1236 - logits_profile_predictions_loss: 63.5828 - logcount_predictions_loss: 0.5408 67/685 [=>............................] - ETA: 7:33 - loss: 63.9059 - logits_profile_predictions_loss: 63.3667 - logcount_predictions_loss: 0.5392 68/685 [=>............................] - ETA: 7:32 - loss: 63.8310 - logits_profile_predictions_loss: 63.2918 - logcount_predictions_loss: 0.5392 69/685 [==>...........................] - ETA: 7:32 - loss: 63.7796 - logits_profile_predictions_loss: 63.2388 - 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[==>...........................] - ETA: 7:17 - loss: 64.0788 - logits_profile_predictions_loss: 63.5403 - logcount_predictions_loss: 0.5385 91/685 [==>...........................] - ETA: 7:16 - loss: 64.0827 - logits_profile_predictions_loss: 63.5443 - logcount_predictions_loss: 0.5383 92/685 [===>..........................] - ETA: 7:16 - loss: 64.1042 - logits_profile_predictions_loss: 63.5648 - logcount_predictions_loss: 0.5394 93/685 [===>..........................] - ETA: 7:15 - loss: 64.1065 - logits_profile_predictions_loss: 63.5666 - logcount_predictions_loss: 0.5399 94/685 [===>..........................] - ETA: 7:14 - loss: 64.0683 - logits_profile_predictions_loss: 63.5287 - logcount_predictions_loss: 0.5396 95/685 [===>..........................] - ETA: 7:14 - loss: 63.9253 - logits_profile_predictions_loss: 63.3871 - logcount_predictions_loss: 0.5381 96/685 [===>..........................] - ETA: 7:13 - loss: 63.8502 - logits_profile_predictions_loss: 63.3123 - 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[===>..........................] - ETA: 7:03 - loss: 63.7963 - logits_profile_predictions_loss: 63.2514 - logcount_predictions_loss: 0.5449 111/685 [===>..........................] - ETA: 7:02 - loss: 63.7422 - logits_profile_predictions_loss: 63.1985 - logcount_predictions_loss: 0.5437 112/685 [===>..........................] - ETA: 7:01 - loss: 63.7284 - logits_profile_predictions_loss: 63.1863 - logcount_predictions_loss: 0.5421 113/685 [===>..........................] - ETA: 7:01 - loss: 63.6946 - logits_profile_predictions_loss: 63.1531 - logcount_predictions_loss: 0.5415 114/685 [===>..........................] - ETA: 7:00 - loss: 63.7048 - logits_profile_predictions_loss: 63.1642 - logcount_predictions_loss: 0.5407 115/685 [====>.........................] - ETA: 7:00 - loss: 63.7668 - logits_profile_predictions_loss: 63.2270 - logcount_predictions_loss: 0.5398 116/685 [====>.........................] - ETA: 6:59 - loss: 63.8674 - logits_profile_predictions_loss: 63.3278 - 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[==============================] - ETA: 0s - loss: 63.7504 - logits_profile_predictions_loss: 63.2471 - logcount_predictions_loss: 0.5033 Epoch 5: val_loss improved from 66.25060 to 66.03979, saving model to /oak/stanford/groups/akundaje/projects/neuro-variants/chrombpnet_models/ameen_2022/K562_bias/ameen_2022.NC/fold_4/models/chrombpnet.h5  685/685 [==============================] - 535s 780ms/step - loss: 63.7504 - logits_profile_predictions_loss: 63.2471 - logcount_predictions_loss: 0.5033 - val_loss: 66.0398 - val_logits_profile_predictions_loss: 65.6268 - val_logcount_predictions_loss: 0.4130 Epoch 6/50 1/685 [..............................] - ETA: 8:21 - loss: 64.6447 - logits_profile_predictions_loss: 64.1025 - logcount_predictions_loss: 0.5422 2/685 [..............................] - ETA: 8:11 - loss: 66.5248 - logits_profile_predictions_loss: 66.0252 - logcount_predictions_loss: 0.4996 3/685 [..............................] - ETA: 8:10 - loss: 66.9140 - 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[..............................] - ETA: 8:01 - loss: 62.9415 - logits_profile_predictions_loss: 62.4699 - logcount_predictions_loss: 0.4716 18/685 [..............................] - ETA: 8:00 - loss: 62.5054 - logits_profile_predictions_loss: 62.0355 - logcount_predictions_loss: 0.4699 19/685 [..............................] - ETA: 8:00 - loss: 63.4084 - logits_profile_predictions_loss: 62.9331 - logcount_predictions_loss: 0.4753 20/685 [..............................] - ETA: 7:59 - loss: 63.3373 - logits_profile_predictions_loss: 62.8660 - logcount_predictions_loss: 0.4714 21/685 [..............................] - ETA: 7:59 - loss: 63.1521 - logits_profile_predictions_loss: 62.6612 - logcount_predictions_loss: 0.4909 22/685 [..............................] - ETA: 7:58 - loss: 63.3714 - logits_profile_predictions_loss: 62.8803 - logcount_predictions_loss: 0.4911 23/685 [>.............................] - ETA: 7:57 - loss: 63.1396 - logits_profile_predictions_loss: 62.6461 - 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[>.............................] - ETA: 7:41 - loss: 63.7645 - logits_profile_predictions_loss: 63.2597 - logcount_predictions_loss: 0.5048 45/685 [>.............................] - ETA: 7:40 - loss: 63.7385 - logits_profile_predictions_loss: 63.2357 - logcount_predictions_loss: 0.5028 46/685 [=>............................] - ETA: 7:40 - loss: 63.5918 - logits_profile_predictions_loss: 63.0910 - logcount_predictions_loss: 0.5007 47/685 [=>............................] - ETA: 7:39 - loss: 63.5102 - logits_profile_predictions_loss: 63.0083 - logcount_predictions_loss: 0.5019 48/685 [=>............................] - ETA: 7:38 - loss: 63.6129 - logits_profile_predictions_loss: 63.1088 - logcount_predictions_loss: 0.5040 49/685 [=>............................] - ETA: 7:38 - loss: 63.5645 - logits_profile_predictions_loss: 63.0606 - logcount_predictions_loss: 0.5039 50/685 [=>............................] - ETA: 7:38 - loss: 63.7186 - logits_profile_predictions_loss: 63.2169 - 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- ETA: 29s - loss: 63.1872 - logits_profile_predictions_loss: 62.7154 - logcount_predictions_loss: 0.4718 646/685 [===========================>..] - ETA: 29s - loss: 63.1867 - logits_profile_predictions_loss: 62.7151 - logcount_predictions_loss: 0.4716 647/685 [===========================>..] - ETA: 28s - loss: 63.1975 - logits_profile_predictions_loss: 62.7258 - logcount_predictions_loss: 0.4717 648/685 [===========================>..] - ETA: 27s - loss: 63.1849 - logits_profile_predictions_loss: 62.7133 - logcount_predictions_loss: 0.4715 649/685 [===========================>..] - ETA: 26s - loss: 63.1754 - logits_profile_predictions_loss: 62.7040 - logcount_predictions_loss: 0.4714 650/685 [===========================>..] - ETA: 26s - loss: 63.1625 - logits_profile_predictions_loss: 62.6912 - logcount_predictions_loss: 0.4713 651/685 [===========================>..] - ETA: 25s - loss: 63.1687 - logits_profile_predictions_loss: 62.6974 - logcount_predictions_loss: 0.4713 652/685 [===========================>..] - ETA: 24s - loss: 63.1756 - logits_profile_predictions_loss: 62.7046 - logcount_predictions_loss: 0.4710 653/685 [===========================>..] - ETA: 23s - loss: 63.1936 - logits_profile_predictions_loss: 62.7226 - logcount_predictions_loss: 0.4710 654/685 [===========================>..] - ETA: 23s - loss: 63.1959 - logits_profile_predictions_loss: 62.7246 - logcount_predictions_loss: 0.4713 655/685 [===========================>..] - ETA: 22s - loss: 63.1872 - logits_profile_predictions_loss: 62.7159 - logcount_predictions_loss: 0.4713 656/685 [===========================>..] - ETA: 21s - loss: 63.1887 - logits_profile_predictions_loss: 62.7174 - logcount_predictions_loss: 0.4713 657/685 [===========================>..] - ETA: 20s - loss: 63.1947 - logits_profile_predictions_loss: 62.7235 - logcount_predictions_loss: 0.4711 658/685 [===========================>..] - ETA: 20s - loss: 63.2021 - logits_profile_predictions_loss: 62.7304 - 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- ETA: 9s - loss: 63.1831 - logits_profile_predictions_loss: 62.7112 - logcount_predictions_loss: 0.4719  673/685 [============================>.] - ETA: 8s - loss: 63.2147 - logits_profile_predictions_loss: 62.7427 - logcount_predictions_loss: 0.4720 674/685 [============================>.] - ETA: 8s - loss: 63.2044 - logits_profile_predictions_loss: 62.7326 - logcount_predictions_loss: 0.4719 675/685 [============================>.] - ETA: 7s - loss: 63.1922 - logits_profile_predictions_loss: 62.7202 - logcount_predictions_loss: 0.4721 676/685 [============================>.] - ETA: 6s - loss: 63.1828 - logits_profile_predictions_loss: 62.7107 - logcount_predictions_loss: 0.4721 677/685 [============================>.] - ETA: 5s - loss: 63.1820 - logits_profile_predictions_loss: 62.7095 - logcount_predictions_loss: 0.4725 678/685 [============================>.] - ETA: 5s - loss: 63.1995 - logits_profile_predictions_loss: 62.7265 - logcount_predictions_loss: 0.4729 679/685 [============================>.] - ETA: 4s - loss: 63.2078 - logits_profile_predictions_loss: 62.7349 - logcount_predictions_loss: 0.4730 680/685 [============================>.] - ETA: 3s - loss: 63.1999 - logits_profile_predictions_loss: 62.7269 - logcount_predictions_loss: 0.4729 681/685 [============================>.] - ETA: 2s - loss: 63.1893 - logits_profile_predictions_loss: 62.7164 - logcount_predictions_loss: 0.4730 682/685 [============================>.] - ETA: 2s - loss: 63.2048 - logits_profile_predictions_loss: 62.7316 - logcount_predictions_loss: 0.4731 683/685 [============================>.] - ETA: 1s - loss: 63.2049 - logits_profile_predictions_loss: 62.7317 - logcount_predictions_loss: 0.4732 684/685 [============================>.] - ETA: 0s - loss: 63.2308 - logits_profile_predictions_loss: 62.7573 - logcount_predictions_loss: 0.4735 685/685 [==============================] - ETA: 0s - loss: 63.2452 - logits_profile_predictions_loss: 62.7715 - logcount_predictions_loss: 0.4737 Epoch 6: val_loss did not improve from 66.03979  685/685 [==============================] - 534s 779ms/step - loss: 63.2452 - logits_profile_predictions_loss: 62.7715 - logcount_predictions_loss: 0.4737 - val_loss: 66.3208 - val_logits_profile_predictions_loss: 65.8713 - val_logcount_predictions_loss: 0.4494 Epoch 7/50 1/685 [..............................] - ETA: 8:23 - loss: 84.6369 - logits_profile_predictions_loss: 84.1531 - logcount_predictions_loss: 0.4838 2/685 [..............................] - ETA: 8:09 - loss: 71.8009 - logits_profile_predictions_loss: 71.2377 - logcount_predictions_loss: 0.5632 3/685 [..............................] - ETA: 8:10 - loss: 67.4909 - logits_profile_predictions_loss: 66.9833 - logcount_predictions_loss: 0.5075 4/685 [..............................] - ETA: 8:09 - loss: 64.0617 - logits_profile_predictions_loss: 63.5576 - logcount_predictions_loss: 0.5041 5/685 [..............................] - ETA: 8:09 - loss: 62.8298 - logits_profile_predictions_loss: 62.3370 - logcount_predictions_loss: 0.4928 6/685 [..............................] - ETA: 8:08 - loss: 63.7695 - logits_profile_predictions_loss: 63.2720 - logcount_predictions_loss: 0.4974 7/685 [..............................] - ETA: 8:07 - loss: 63.7257 - logits_profile_predictions_loss: 63.2452 - logcount_predictions_loss: 0.4805 8/685 [..............................] - ETA: 8:07 - loss: 62.8717 - logits_profile_predictions_loss: 62.4045 - logcount_predictions_loss: 0.4672 9/685 [..............................] - ETA: 8:06 - loss: 63.3557 - logits_profile_predictions_loss: 62.8881 - logcount_predictions_loss: 0.4677 10/685 [..............................] - ETA: 8:05 - loss: 64.1361 - logits_profile_predictions_loss: 63.6561 - logcount_predictions_loss: 0.4800 11/685 [..............................] - ETA: 8:05 - loss: 63.0383 - logits_profile_predictions_loss: 62.5565 - logcount_predictions_loss: 0.4818 12/685 [..............................] - ETA: 8:04 - loss: 62.3353 - logits_profile_predictions_loss: 61.8633 - logcount_predictions_loss: 0.4720 13/685 [..............................] - ETA: 8:03 - loss: 63.1992 - logits_profile_predictions_loss: 62.7147 - logcount_predictions_loss: 0.4845 14/685 [..............................] - ETA: 8:03 - loss: 63.7811 - logits_profile_predictions_loss: 63.3119 - logcount_predictions_loss: 0.4692 15/685 [..............................] - ETA: 8:02 - loss: 63.8937 - logits_profile_predictions_loss: 63.4247 - logcount_predictions_loss: 0.4691 16/685 [..............................] - ETA: 8:02 - loss: 64.1250 - logits_profile_predictions_loss: 63.6621 - logcount_predictions_loss: 0.4629 17/685 [..............................] - ETA: 8:01 - loss: 64.3497 - logits_profile_predictions_loss: 63.8922 - logcount_predictions_loss: 0.4574 18/685 [..............................] - ETA: 8:00 - loss: 63.8957 - logits_profile_predictions_loss: 63.4368 - logcount_predictions_loss: 0.4589 19/685 [..............................] - ETA: 7:59 - loss: 63.3524 - logits_profile_predictions_loss: 62.9017 - logcount_predictions_loss: 0.4508 20/685 [..............................] - ETA: 7:59 - loss: 63.1344 - logits_profile_predictions_loss: 62.6876 - logcount_predictions_loss: 0.4469 21/685 [..............................] - ETA: 7:58 - loss: 62.5728 - logits_profile_predictions_loss: 62.1231 - logcount_predictions_loss: 0.4498 22/685 [..............................] - ETA: 7:58 - loss: 62.6802 - logits_profile_predictions_loss: 62.2327 - logcount_predictions_loss: 0.4475 23/685 [>.............................] - ETA: 7:57 - loss: 62.4557 - logits_profile_predictions_loss: 62.0119 - logcount_predictions_loss: 0.4438 24/685 [>.............................] - ETA: 7:56 - loss: 62.5007 - logits_profile_predictions_loss: 62.0584 - logcount_predictions_loss: 0.4422 25/685 [>.............................] - ETA: 7:56 - loss: 62.3685 - logits_profile_predictions_loss: 61.9254 - logcount_predictions_loss: 0.4430 26/685 [>.............................] - ETA: 7:55 - loss: 62.1935 - logits_profile_predictions_loss: 61.7528 - logcount_predictions_loss: 0.4407 27/685 [>.............................] - ETA: 7:54 - loss: 62.3454 - logits_profile_predictions_loss: 61.9030 - logcount_predictions_loss: 0.4423 28/685 [>.............................] - ETA: 7:54 - loss: 62.2284 - logits_profile_predictions_loss: 61.7880 - logcount_predictions_loss: 0.4404 29/685 [>.............................] - ETA: 7:53 - loss: 62.0822 - logits_profile_predictions_loss: 61.6442 - logcount_predictions_loss: 0.4380 30/685 [>.............................] - ETA: 7:52 - loss: 62.5554 - logits_profile_predictions_loss: 62.1187 - logcount_predictions_loss: 0.4367 31/685 [>.............................] - ETA: 7:52 - loss: 62.4680 - logits_profile_predictions_loss: 62.0369 - logcount_predictions_loss: 0.4311 32/685 [>.............................] - 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[>.............................] - ETA: 7:47 - loss: 62.6986 - logits_profile_predictions_loss: 62.2766 - logcount_predictions_loss: 0.4220 40/685 [>.............................] - ETA: 7:46 - loss: 62.5791 - logits_profile_predictions_loss: 62.1547 - logcount_predictions_loss: 0.4244 41/685 [>.............................] - ETA: 7:45 - loss: 62.3929 - logits_profile_predictions_loss: 61.9656 - logcount_predictions_loss: 0.4274 42/685 [>.............................] - ETA: 7:45 - loss: 62.5569 - logits_profile_predictions_loss: 62.1267 - logcount_predictions_loss: 0.4302 43/685 [>.............................] - ETA: 7:44 - loss: 62.6535 - logits_profile_predictions_loss: 62.2210 - logcount_predictions_loss: 0.4325 44/685 [>.............................] - ETA: 7:44 - loss: 62.6321 - logits_profile_predictions_loss: 62.1980 - logcount_predictions_loss: 0.4341 45/685 [>.............................] - ETA: 7:43 - loss: 62.4978 - logits_profile_predictions_loss: 62.0632 - logcount_predictions_loss: 0.4347 46/685 [=>............................] - ETA: 7:42 - loss: 62.5337 - logits_profile_predictions_loss: 62.0998 - logcount_predictions_loss: 0.4338 47/685 [=>............................] - ETA: 7:42 - loss: 62.3286 - logits_profile_predictions_loss: 61.8945 - logcount_predictions_loss: 0.4340 48/685 [=>............................] - ETA: 7:41 - loss: 62.2800 - logits_profile_predictions_loss: 61.8451 - logcount_predictions_loss: 0.4349 49/685 [=>............................] - ETA: 7:41 - loss: 62.3879 - logits_profile_predictions_loss: 61.9497 - logcount_predictions_loss: 0.4382 50/685 [=>............................] - ETA: 7:40 - loss: 62.2393 - logits_profile_predictions_loss: 61.8009 - logcount_predictions_loss: 0.4384 51/685 [=>............................] - ETA: 7:39 - loss: 62.1509 - logits_profile_predictions_loss: 61.7130 - logcount_predictions_loss: 0.4379 52/685 [=>............................] - ETA: 7:39 - loss: 62.1499 - logits_profile_predictions_loss: 61.7117 - logcount_predictions_loss: 0.4382 53/685 [=>............................] - ETA: 7:38 - loss: 62.1696 - logits_profile_predictions_loss: 61.7319 - logcount_predictions_loss: 0.4377 54/685 [=>............................] - ETA: 7:37 - loss: 62.3577 - logits_profile_predictions_loss: 61.9178 - logcount_predictions_loss: 0.4399 55/685 [=>............................] - ETA: 7:37 - loss: 62.3636 - logits_profile_predictions_loss: 61.9240 - logcount_predictions_loss: 0.4396 56/685 [=>............................] - ETA: 7:36 - loss: 62.2689 - logits_profile_predictions_loss: 61.8283 - logcount_predictions_loss: 0.4405 57/685 [=>............................] - ETA: 7:36 - loss: 62.4702 - logits_profile_predictions_loss: 62.0310 - logcount_predictions_loss: 0.4392 58/685 [=>............................] - ETA: 7:35 - loss: 62.3462 - logits_profile_predictions_loss: 61.9059 - logcount_predictions_loss: 0.4403 59/685 [=>............................] - ETA: 7:35 - loss: 62.4827 - logits_profile_predictions_loss: 62.0425 - logcount_predictions_loss: 0.4402 60/685 [=>............................] - ETA: 7:34 - loss: 62.3245 - logits_profile_predictions_loss: 61.8826 - logcount_predictions_loss: 0.4419 61/685 [=>............................] - ETA: 7:34 - loss: 62.4045 - logits_profile_predictions_loss: 61.9630 - logcount_predictions_loss: 0.4415 62/685 [=>............................] - ETA: 7:33 - loss: 62.5180 - logits_profile_predictions_loss: 62.0766 - logcount_predictions_loss: 0.4414 63/685 [=>............................] - ETA: 7:33 - loss: 62.4700 - logits_profile_predictions_loss: 62.0309 - logcount_predictions_loss: 0.4392 64/685 [=>............................] - ETA: 7:32 - loss: 62.3930 - logits_profile_predictions_loss: 61.9550 - logcount_predictions_loss: 0.4381 65/685 [=>............................] - ETA: 7:32 - loss: 62.4924 - logits_profile_predictions_loss: 62.0524 - logcount_predictions_loss: 0.4401 66/685 [=>............................] - ETA: 7:31 - loss: 62.5346 - logits_profile_predictions_loss: 62.0919 - logcount_predictions_loss: 0.4427 67/685 [=>............................] - ETA: 7:31 - loss: 62.5845 - logits_profile_predictions_loss: 62.1435 - logcount_predictions_loss: 0.4410 68/685 [=>............................] - ETA: 7:30 - loss: 62.5382 - logits_profile_predictions_loss: 62.0970 - logcount_predictions_loss: 0.4413 69/685 [==>...........................] - ETA: 7:29 - loss: 62.5538 - logits_profile_predictions_loss: 62.1123 - logcount_predictions_loss: 0.4415 70/685 [==>...........................] - ETA: 7:29 - loss: 62.4684 - logits_profile_predictions_loss: 62.0263 - logcount_predictions_loss: 0.4421 71/685 [==>...........................] - ETA: 7:28 - loss: 62.4802 - logits_profile_predictions_loss: 62.0362 - logcount_predictions_loss: 0.4441 72/685 [==>...........................] - ETA: 7:27 - loss: 62.4837 - logits_profile_predictions_loss: 62.0401 - logcount_predictions_loss: 0.4436 73/685 [==>...........................] - ETA: 7:27 - loss: 62.3192 - logits_profile_predictions_loss: 61.8751 - logcount_predictions_loss: 0.4441 74/685 [==>...........................] - ETA: 7:26 - loss: 62.3446 - logits_profile_predictions_loss: 61.9007 - logcount_predictions_loss: 0.4440 75/685 [==>...........................] - ETA: 7:25 - loss: 62.4098 - logits_profile_predictions_loss: 61.9651 - logcount_predictions_loss: 0.4447 76/685 [==>...........................] - ETA: 7:25 - loss: 62.5291 - logits_profile_predictions_loss: 62.0841 - logcount_predictions_loss: 0.4450 77/685 [==>...........................] - ETA: 7:24 - loss: 62.4681 - logits_profile_predictions_loss: 62.0231 - logcount_predictions_loss: 0.4450 78/685 [==>...........................] - ETA: 7:23 - loss: 62.4205 - logits_profile_predictions_loss: 61.9776 - logcount_predictions_loss: 0.4430 79/685 [==>...........................] - ETA: 7:23 - loss: 62.5366 - logits_profile_predictions_loss: 62.0933 - logcount_predictions_loss: 0.4433 80/685 [==>...........................] - ETA: 7:22 - loss: 62.5567 - logits_profile_predictions_loss: 62.1150 - logcount_predictions_loss: 0.4416 81/685 [==>...........................] - ETA: 7:21 - loss: 62.5065 - logits_profile_predictions_loss: 62.0655 - logcount_predictions_loss: 0.4410 82/685 [==>...........................] - ETA: 7:21 - loss: 62.6197 - logits_profile_predictions_loss: 62.1787 - logcount_predictions_loss: 0.4410 83/685 [==>...........................] - ETA: 7:20 - loss: 62.6470 - logits_profile_predictions_loss: 62.2045 - logcount_predictions_loss: 0.4425 84/685 [==>...........................] - ETA: 7:19 - loss: 62.6071 - logits_profile_predictions_loss: 62.1653 - logcount_predictions_loss: 0.4418 85/685 [==>...........................] - ETA: 7:19 - loss: 62.6915 - logits_profile_predictions_loss: 62.2487 - logcount_predictions_loss: 0.4428 86/685 [==>...........................] - 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logcount_predictions_loss: 0.4531 681/685 [============================>.] - ETA: 3s - loss: 62.9440 - logits_profile_predictions_loss: 62.4911 - logcount_predictions_loss: 0.4531 682/685 [============================>.] - ETA: 2s - loss: 62.9322 - logits_profile_predictions_loss: 62.4795 - logcount_predictions_loss: 0.4528 683/685 [============================>.] - ETA: 1s - loss: 62.9397 - logits_profile_predictions_loss: 62.4870 - logcount_predictions_loss: 0.4528 684/685 [============================>.] - ETA: 0s - loss: 62.9392 - logits_profile_predictions_loss: 62.4868 - logcount_predictions_loss: 0.4525 685/685 [==============================] - ETA: 0s - loss: 62.9566 - logits_profile_predictions_loss: 62.5042 - logcount_predictions_loss: 0.4525 Epoch 7: val_loss did not improve from 66.03979  685/685 [==============================] - 535s 781ms/step - loss: 62.9566 - logits_profile_predictions_loss: 62.5042 - logcount_predictions_loss: 0.4525 - val_loss: 66.2087 - val_logits_profile_predictions_loss: 65.7853 - val_logcount_predictions_loss: 0.4234 Epoch 8/50 1/685 [..............................] - ETA: 8:19 - loss: 59.6145 - logits_profile_predictions_loss: 59.2311 - logcount_predictions_loss: 0.3834 2/685 [..............................] - ETA: 8:11 - loss: 63.5487 - logits_profile_predictions_loss: 63.1358 - logcount_predictions_loss: 0.4130 3/685 [..............................] - ETA: 8:10 - loss: 68.3212 - logits_profile_predictions_loss: 67.8751 - logcount_predictions_loss: 0.4461 4/685 [..............................] - ETA: 8:10 - loss: 68.0843 - logits_profile_predictions_loss: 67.6329 - logcount_predictions_loss: 0.4514 5/685 [..............................] - ETA: 8:10 - loss: 66.5017 - logits_profile_predictions_loss: 66.0321 - logcount_predictions_loss: 0.4696 6/685 [..............................] - ETA: 8:09 - loss: 66.4342 - logits_profile_predictions_loss: 65.9599 - logcount_predictions_loss: 0.4743 7/685 [..............................] - ETA: 8:08 - loss: 65.1044 - logits_profile_predictions_loss: 64.6527 - logcount_predictions_loss: 0.4516 8/685 [..............................] - ETA: 8:08 - loss: 64.1420 - logits_profile_predictions_loss: 63.7040 - logcount_predictions_loss: 0.4380 9/685 [..............................] - ETA: 8:07 - loss: 63.1691 - logits_profile_predictions_loss: 62.7381 - logcount_predictions_loss: 0.4311 10/685 [..............................] - ETA: 7:51 - loss: 62.2016 - logits_profile_predictions_loss: 61.7799 - logcount_predictions_loss: 0.4217 11/685 [..............................] - ETA: 7:52 - loss: 61.9855 - logits_profile_predictions_loss: 61.5639 - logcount_predictions_loss: 0.4216 12/685 [..............................] - ETA: 7:52 - loss: 61.6828 - logits_profile_predictions_loss: 61.2613 - logcount_predictions_loss: 0.4215 13/685 [..............................] - ETA: 7:53 - loss: 61.8199 - logits_profile_predictions_loss: 61.3960 - logcount_predictions_loss: 0.4239 14/685 [..............................] - ETA: 7:53 - loss: 61.7670 - logits_profile_predictions_loss: 61.3336 - logcount_predictions_loss: 0.4334 15/685 [..............................] - ETA: 7:53 - loss: 61.3270 - logits_profile_predictions_loss: 60.8978 - logcount_predictions_loss: 0.4292 16/685 [..............................] - ETA: 7:53 - loss: 61.2789 - logits_profile_predictions_loss: 60.8438 - logcount_predictions_loss: 0.4350 17/685 [..............................] - ETA: 7:53 - loss: 61.6773 - logits_profile_predictions_loss: 61.2476 - logcount_predictions_loss: 0.4296 18/685 [..............................] - ETA: 7:53 - loss: 61.8058 - logits_profile_predictions_loss: 61.3791 - logcount_predictions_loss: 0.4266 19/685 [..............................] - ETA: 7:53 - loss: 61.4823 - logits_profile_predictions_loss: 61.0574 - logcount_predictions_loss: 0.4248 20/685 [..............................] - ETA: 7:52 - loss: 61.2928 - logits_profile_predictions_loss: 60.8661 - logcount_predictions_loss: 0.4266 21/685 [..............................] - ETA: 7:52 - loss: 61.5509 - logits_profile_predictions_loss: 61.1163 - logcount_predictions_loss: 0.4346 22/685 [..............................] - ETA: 7:52 - loss: 61.3312 - logits_profile_predictions_loss: 60.9006 - logcount_predictions_loss: 0.4306 23/685 [>.............................] - ETA: 7:51 - loss: 61.8239 - logits_profile_predictions_loss: 61.3924 - logcount_predictions_loss: 0.4314 24/685 [>.............................] - ETA: 7:51 - loss: 61.2657 - logits_profile_predictions_loss: 60.8388 - logcount_predictions_loss: 0.4269 25/685 [>.............................] - ETA: 7:51 - loss: 60.9827 - logits_profile_predictions_loss: 60.5624 - logcount_predictions_loss: 0.4203 26/685 [>.............................] - ETA: 7:50 - loss: 61.1625 - logits_profile_predictions_loss: 60.7471 - logcount_predictions_loss: 0.4154 27/685 [>.............................] - ETA: 7:50 - loss: 61.4884 - logits_profile_predictions_loss: 61.0779 - logcount_predictions_loss: 0.4106 28/685 [>.............................] - ETA: 7:49 - loss: 61.5898 - logits_profile_predictions_loss: 61.1787 - logcount_predictions_loss: 0.4111 29/685 [>.............................] - ETA: 7:49 - loss: 62.0955 - logits_profile_predictions_loss: 61.6851 - logcount_predictions_loss: 0.4104 30/685 [>.............................] - ETA: 7:48 - loss: 62.2972 - logits_profile_predictions_loss: 61.8837 - logcount_predictions_loss: 0.4135 31/685 [>.............................] - ETA: 7:48 - loss: 62.3872 - logits_profile_predictions_loss: 61.9748 - logcount_predictions_loss: 0.4123 32/685 [>.............................] - ETA: 7:47 - loss: 62.6812 - logits_profile_predictions_loss: 62.2636 - logcount_predictions_loss: 0.4176 33/685 [>.............................] - ETA: 7:47 - loss: 62.6205 - logits_profile_predictions_loss: 62.2037 - logcount_predictions_loss: 0.4168 34/685 [>.............................] - ETA: 7:46 - loss: 62.6011 - logits_profile_predictions_loss: 62.1833 - logcount_predictions_loss: 0.4178 35/685 [>.............................] - ETA: 7:46 - loss: 62.9424 - logits_profile_predictions_loss: 62.5193 - logcount_predictions_loss: 0.4231 36/685 [>.............................] - ETA: 7:45 - loss: 62.8839 - logits_profile_predictions_loss: 62.4588 - logcount_predictions_loss: 0.4251 37/685 [>.............................] - ETA: 7:45 - loss: 62.6285 - logits_profile_predictions_loss: 62.2014 - logcount_predictions_loss: 0.4271 38/685 [>.............................] - ETA: 7:44 - loss: 62.2695 - logits_profile_predictions_loss: 61.8451 - logcount_predictions_loss: 0.4244 39/685 [>.............................] - ETA: 7:44 - loss: 62.2073 - logits_profile_predictions_loss: 61.7806 - logcount_predictions_loss: 0.4267 40/685 [>.............................] - ETA: 7:43 - loss: 62.2730 - logits_profile_predictions_loss: 61.8445 - logcount_predictions_loss: 0.4285 41/685 [>.............................] - ETA: 7:43 - loss: 62.3677 - logits_profile_predictions_loss: 61.9361 - logcount_predictions_loss: 0.4316 42/685 [>.............................] - ETA: 7:42 - loss: 62.2626 - logits_profile_predictions_loss: 61.8293 - logcount_predictions_loss: 0.4333 43/685 [>.............................] - ETA: 7:41 - loss: 62.6879 - logits_profile_predictions_loss: 62.2546 - logcount_predictions_loss: 0.4332 44/685 [>.............................] - ETA: 7:41 - loss: 62.4686 - logits_profile_predictions_loss: 62.0328 - logcount_predictions_loss: 0.4358 45/685 [>.............................] - ETA: 7:40 - loss: 62.7065 - logits_profile_predictions_loss: 62.2689 - logcount_predictions_loss: 0.4376 46/685 [=>............................] - ETA: 7:40 - loss: 62.6215 - logits_profile_predictions_loss: 62.1841 - logcount_predictions_loss: 0.4374 47/685 [=>............................] - ETA: 7:39 - loss: 62.7132 - logits_profile_predictions_loss: 62.2740 - logcount_predictions_loss: 0.4392 48/685 [=>............................] - ETA: 7:39 - loss: 62.6989 - logits_profile_predictions_loss: 62.2563 - logcount_predictions_loss: 0.4426 49/685 [=>............................] - ETA: 7:39 - loss: 62.8236 - logits_profile_predictions_loss: 62.3768 - logcount_predictions_loss: 0.4468 50/685 [=>............................] - ETA: 7:38 - loss: 62.6479 - logits_profile_predictions_loss: 62.2022 - logcount_predictions_loss: 0.4457 51/685 [=>............................] - ETA: 7:38 - loss: 62.5457 - logits_profile_predictions_loss: 62.0996 - logcount_predictions_loss: 0.4460 52/685 [=>............................] - ETA: 7:37 - loss: 62.7316 - logits_profile_predictions_loss: 62.2886 - logcount_predictions_loss: 0.4429 53/685 [=>............................] - ETA: 7:37 - loss: 62.8734 - logits_profile_predictions_loss: 62.4296 - logcount_predictions_loss: 0.4438 54/685 [=>............................] - ETA: 7:36 - loss: 62.7444 - logits_profile_predictions_loss: 62.2988 - logcount_predictions_loss: 0.4456 55/685 [=>............................] - ETA: 7:35 - loss: 62.7988 - logits_profile_predictions_loss: 62.3510 - logcount_predictions_loss: 0.4477 56/685 [=>............................] - ETA: 7:35 - loss: 63.0267 - logits_profile_predictions_loss: 62.5762 - logcount_predictions_loss: 0.4505 57/685 [=>............................] - ETA: 7:34 - loss: 63.0456 - logits_profile_predictions_loss: 62.5961 - logcount_predictions_loss: 0.4495 58/685 [=>............................] - ETA: 7:34 - loss: 63.0252 - logits_profile_predictions_loss: 62.5734 - logcount_predictions_loss: 0.4517 59/685 [=>............................] - ETA: 7:33 - loss: 62.9188 - logits_profile_predictions_loss: 62.4611 - logcount_predictions_loss: 0.4577 60/685 [=>............................] - ETA: 7:33 - loss: 62.8934 - logits_profile_predictions_loss: 62.4362 - logcount_predictions_loss: 0.4572 61/685 [=>............................] - ETA: 7:32 - loss: 62.7655 - logits_profile_predictions_loss: 62.3079 - logcount_predictions_loss: 0.4576 62/685 [=>............................] - ETA: 7:32 - loss: 62.8604 - logits_profile_predictions_loss: 62.4007 - logcount_predictions_loss: 0.4597 63/685 [=>............................] - ETA: 7:31 - loss: 62.7903 - logits_profile_predictions_loss: 62.3288 - logcount_predictions_loss: 0.4615 64/685 [=>............................] - ETA: 7:31 - loss: 62.8755 - logits_profile_predictions_loss: 62.4144 - logcount_predictions_loss: 0.4611 65/685 [=>............................] - ETA: 7:30 - loss: 62.8650 - logits_profile_predictions_loss: 62.4037 - logcount_predictions_loss: 0.4613 66/685 [=>............................] - ETA: 7:30 - loss: 62.7931 - logits_profile_predictions_loss: 62.3303 - logcount_predictions_loss: 0.4628 67/685 [=>............................] - ETA: 7:29 - loss: 62.8335 - logits_profile_predictions_loss: 62.3710 - logcount_predictions_loss: 0.4625 68/685 [=>............................] - ETA: 7:29 - loss: 62.8035 - logits_profile_predictions_loss: 62.3410 - logcount_predictions_loss: 0.4624 69/685 [==>...........................] - ETA: 7:28 - loss: 62.7989 - logits_profile_predictions_loss: 62.3386 - logcount_predictions_loss: 0.4603 70/685 [==>...........................] - ETA: 7:27 - loss: 62.9356 - logits_profile_predictions_loss: 62.4733 - logcount_predictions_loss: 0.4622 71/685 [==>...........................] - ETA: 7:27 - loss: 63.0083 - logits_profile_predictions_loss: 62.5456 - logcount_predictions_loss: 0.4627 72/685 [==>...........................] - ETA: 7:26 - loss: 63.2758 - logits_profile_predictions_loss: 62.8127 - logcount_predictions_loss: 0.4631 73/685 [==>...........................] - ETA: 7:26 - loss: 63.1485 - logits_profile_predictions_loss: 62.6863 - logcount_predictions_loss: 0.4622 74/685 [==>...........................] - ETA: 7:25 - loss: 63.1903 - logits_profile_predictions_loss: 62.7296 - logcount_predictions_loss: 0.4607 75/685 [==>...........................] - ETA: 7:25 - loss: 63.1371 - logits_profile_predictions_loss: 62.6754 - logcount_predictions_loss: 0.4617 76/685 [==>...........................] - ETA: 7:24 - loss: 63.1871 - logits_profile_predictions_loss: 62.7241 - logcount_predictions_loss: 0.4629 77/685 [==>...........................] - ETA: 7:23 - loss: 63.1509 - logits_profile_predictions_loss: 62.6873 - logcount_predictions_loss: 0.4637 78/685 [==>...........................] - ETA: 7:23 - loss: 63.1187 - logits_profile_predictions_loss: 62.6558 - logcount_predictions_loss: 0.4629 79/685 [==>...........................] - ETA: 7:22 - loss: 63.2376 - logits_profile_predictions_loss: 62.7742 - logcount_predictions_loss: 0.4634 80/685 [==>...........................] - ETA: 7:21 - loss: 63.1805 - logits_profile_predictions_loss: 62.7182 - logcount_predictions_loss: 0.4623 81/685 [==>...........................] - ETA: 7:21 - loss: 63.1654 - logits_profile_predictions_loss: 62.7045 - logcount_predictions_loss: 0.4608 82/685 [==>...........................] - ETA: 7:20 - loss: 63.1478 - logits_profile_predictions_loss: 62.6875 - logcount_predictions_loss: 0.4603 83/685 [==>...........................] - ETA: 7:19 - loss: 63.1476 - logits_profile_predictions_loss: 62.6871 - logcount_predictions_loss: 0.4606 84/685 [==>...........................] - ETA: 7:19 - loss: 63.1409 - logits_profile_predictions_loss: 62.6816 - logcount_predictions_loss: 0.4593 85/685 [==>...........................] - ETA: 7:18 - loss: 63.1050 - logits_profile_predictions_loss: 62.6475 - logcount_predictions_loss: 0.4575 86/685 [==>...........................] - ETA: 7:17 - loss: 63.1424 - logits_profile_predictions_loss: 62.6837 - logcount_predictions_loss: 0.4587 87/685 [==>...........................] - ETA: 7:17 - loss: 63.1379 - logits_profile_predictions_loss: 62.6784 - logcount_predictions_loss: 0.4595 88/685 [==>...........................] - ETA: 7:16 - loss: 63.0941 - logits_profile_predictions_loss: 62.6366 - logcount_predictions_loss: 0.4575 89/685 [==>...........................] - ETA: 7:15 - loss: 63.1441 - logits_profile_predictions_loss: 62.6869 - logcount_predictions_loss: 0.4573 90/685 [==>...........................] - ETA: 7:15 - loss: 63.0593 - logits_profile_predictions_loss: 62.6041 - logcount_predictions_loss: 0.4552 91/685 [==>...........................] - ETA: 7:14 - loss: 63.0704 - logits_profile_predictions_loss: 62.6154 - logcount_predictions_loss: 0.4549 92/685 [===>..........................] - ETA: 7:14 - loss: 62.9836 - logits_profile_predictions_loss: 62.5284 - logcount_predictions_loss: 0.4552 93/685 [===>..........................] - ETA: 7:13 - loss: 62.9325 - logits_profile_predictions_loss: 62.4761 - logcount_predictions_loss: 0.4564 94/685 [===>..........................] - ETA: 7:12 - loss: 62.8896 - logits_profile_predictions_loss: 62.4329 - logcount_predictions_loss: 0.4567 95/685 [===>..........................] - ETA: 7:12 - loss: 62.9241 - logits_profile_predictions_loss: 62.4665 - logcount_predictions_loss: 0.4575 96/685 [===>..........................] - ETA: 7:11 - loss: 62.8869 - logits_profile_predictions_loss: 62.4303 - logcount_predictions_loss: 0.4566 97/685 [===>..........................] - ETA: 7:10 - loss: 62.8954 - logits_profile_predictions_loss: 62.4384 - logcount_predictions_loss: 0.4569 98/685 [===>..........................] - ETA: 7:10 - loss: 62.8808 - logits_profile_predictions_loss: 62.4226 - logcount_predictions_loss: 0.4582 99/685 [===>..........................] - ETA: 7:09 - loss: 62.8549 - logits_profile_predictions_loss: 62.3967 - logcount_predictions_loss: 0.4581 100/685 [===>..........................] - ETA: 7:08 - loss: 62.7786 - logits_profile_predictions_loss: 62.3200 - logcount_predictions_loss: 0.4586 101/685 [===>..........................] - ETA: 7:08 - loss: 62.7856 - logits_profile_predictions_loss: 62.3257 - logcount_predictions_loss: 0.4599 102/685 [===>..........................] - ETA: 7:07 - loss: 62.8419 - logits_profile_predictions_loss: 62.3799 - logcount_predictions_loss: 0.4621 103/685 [===>..........................] - ETA: 7:06 - loss: 62.8615 - logits_profile_predictions_loss: 62.3991 - logcount_predictions_loss: 0.4623 104/685 [===>..........................] - ETA: 7:06 - loss: 62.8667 - logits_profile_predictions_loss: 62.4044 - logcount_predictions_loss: 0.4623 105/685 [===>..........................] - ETA: 7:05 - loss: 62.7746 - logits_profile_predictions_loss: 62.3103 - logcount_predictions_loss: 0.4642 106/685 [===>..........................] - ETA: 7:04 - loss: 62.7416 - logits_profile_predictions_loss: 62.2793 - logcount_predictions_loss: 0.4623 107/685 [===>..........................] - ETA: 7:03 - loss: 62.6836 - logits_profile_predictions_loss: 62.2222 - logcount_predictions_loss: 0.4614 108/685 [===>..........................] - ETA: 7:03 - loss: 62.8463 - logits_profile_predictions_loss: 62.3827 - logcount_predictions_loss: 0.4636 109/685 [===>..........................] - ETA: 7:02 - loss: 62.8272 - logits_profile_predictions_loss: 62.3637 - logcount_predictions_loss: 0.4635 110/685 [===>..........................] - ETA: 7:01 - loss: 62.7966 - logits_profile_predictions_loss: 62.3316 - logcount_predictions_loss: 0.4650 111/685 [===>..........................] - ETA: 7:01 - loss: 62.7728 - logits_profile_predictions_loss: 62.3077 - logcount_predictions_loss: 0.4650 112/685 [===>..........................] - ETA: 7:01 - loss: 62.8357 - logits_profile_predictions_loss: 62.3711 - logcount_predictions_loss: 0.4646 113/685 [===>..........................] - ETA: 7:01 - loss: 62.7788 - logits_profile_predictions_loss: 62.3141 - logcount_predictions_loss: 0.4648 114/685 [===>..........................] - ETA: 7:00 - loss: 62.8471 - logits_profile_predictions_loss: 62.3825 - logcount_predictions_loss: 0.4646 115/685 [====>.........................] - ETA: 7:00 - loss: 62.7845 - logits_profile_predictions_loss: 62.3202 - logcount_predictions_loss: 0.4643 116/685 [====>.........................] - ETA: 7:00 - loss: 62.8635 - logits_profile_predictions_loss: 62.3981 - logcount_predictions_loss: 0.4654 117/685 [====>.........................] - ETA: 6:59 - loss: 62.9102 - logits_profile_predictions_loss: 62.4446 - logcount_predictions_loss: 0.4656 118/685 [====>.........................] - ETA: 6:58 - loss: 62.8965 - logits_profile_predictions_loss: 62.4313 - logcount_predictions_loss: 0.4652 119/685 [====>.........................] - ETA: 6:58 - loss: 62.9298 - logits_profile_predictions_loss: 62.4653 - logcount_predictions_loss: 0.4645 120/685 [====>.........................] - ETA: 6:57 - loss: 62.9058 - logits_profile_predictions_loss: 62.4426 - logcount_predictions_loss: 0.4632 121/685 [====>.........................] - ETA: 6:56 - loss: 62.8665 - 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- ETA: 42s - loss: 62.4435 - logits_profile_predictions_loss: 61.9917 - logcount_predictions_loss: 0.4519 629/685 [==========================>...] - ETA: 41s - loss: 62.4403 - logits_profile_predictions_loss: 61.9886 - logcount_predictions_loss: 0.4518 630/685 [==========================>...] - ETA: 41s - loss: 62.4519 - logits_profile_predictions_loss: 62.0004 - logcount_predictions_loss: 0.4516 631/685 [==========================>...] - ETA: 40s - loss: 62.4477 - logits_profile_predictions_loss: 61.9962 - logcount_predictions_loss: 0.4515 632/685 [==========================>...] - ETA: 39s - loss: 62.4345 - logits_profile_predictions_loss: 61.9833 - logcount_predictions_loss: 0.4513 633/685 [==========================>...] - ETA: 38s - loss: 62.4232 - logits_profile_predictions_loss: 61.9721 - logcount_predictions_loss: 0.4511 634/685 [==========================>...] - ETA: 38s - loss: 62.4198 - logits_profile_predictions_loss: 61.9688 - logcount_predictions_loss: 0.4510 635/685 [==========================>...] - ETA: 37s - loss: 62.4183 - logits_profile_predictions_loss: 61.9673 - logcount_predictions_loss: 0.4510 636/685 [==========================>...] - ETA: 36s - loss: 62.4223 - logits_profile_predictions_loss: 61.9715 - logcount_predictions_loss: 0.4508 637/685 [==========================>...] - ETA: 35s - loss: 62.4373 - logits_profile_predictions_loss: 61.9864 - logcount_predictions_loss: 0.4509 638/685 [==========================>...] - ETA: 35s - loss: 62.4428 - logits_profile_predictions_loss: 61.9920 - logcount_predictions_loss: 0.4508 639/685 [==========================>...] - ETA: 34s - loss: 62.4507 - logits_profile_predictions_loss: 62.0003 - logcount_predictions_loss: 0.4505 640/685 [===========================>..] - ETA: 33s - loss: 62.4539 - logits_profile_predictions_loss: 62.0037 - logcount_predictions_loss: 0.4503 641/685 [===========================>..] - ETA: 32s - loss: 62.4564 - logits_profile_predictions_loss: 62.0063 - 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[===========================>..] - ETA: 17s - loss: 62.4780 - logits_profile_predictions_loss: 62.0295 - logcount_predictions_loss: 0.4485 663/685 [============================>.] - ETA: 16s - loss: 62.4806 - logits_profile_predictions_loss: 62.0322 - logcount_predictions_loss: 0.4484 664/685 [============================>.] - ETA: 15s - loss: 62.4837 - logits_profile_predictions_loss: 62.0352 - logcount_predictions_loss: 0.4486 665/685 [============================>.] - ETA: 14s - loss: 62.4713 - logits_profile_predictions_loss: 62.0226 - logcount_predictions_loss: 0.4487 666/685 [============================>.] - ETA: 14s - loss: 62.4599 - logits_profile_predictions_loss: 62.0115 - logcount_predictions_loss: 0.4484 667/685 [============================>.] - ETA: 13s - loss: 62.4435 - logits_profile_predictions_loss: 61.9952 - logcount_predictions_loss: 0.4484 668/685 [============================>.] - ETA: 12s - loss: 62.4463 - logits_profile_predictions_loss: 61.9977 - logcount_predictions_loss: 0.4486 669/685 [============================>.] - ETA: 11s - loss: 62.4486 - logits_profile_predictions_loss: 62.0001 - logcount_predictions_loss: 0.4486 670/685 [============================>.] - ETA: 11s - loss: 62.4438 - logits_profile_predictions_loss: 61.9952 - logcount_predictions_loss: 0.4486 671/685 [============================>.] - ETA: 10s - loss: 62.4311 - logits_profile_predictions_loss: 61.9825 - logcount_predictions_loss: 0.4486 672/685 [============================>.] - ETA: 9s - loss: 62.4242 - logits_profile_predictions_loss: 61.9758 - logcount_predictions_loss: 0.4484  673/685 [============================>.] - ETA: 8s - loss: 62.4326 - logits_profile_predictions_loss: 61.9844 - logcount_predictions_loss: 0.4483 674/685 [============================>.] - ETA: 8s - loss: 62.4266 - logits_profile_predictions_loss: 61.9785 - logcount_predictions_loss: 0.4481 675/685 [============================>.] - ETA: 7s - loss: 62.4214 - logits_profile_predictions_loss: 61.9733 - logcount_predictions_loss: 0.4481 676/685 [============================>.] - ETA: 6s - loss: 62.4219 - logits_profile_predictions_loss: 61.9733 - logcount_predictions_loss: 0.4486 677/685 [============================>.] - ETA: 5s - loss: 62.4184 - logits_profile_predictions_loss: 61.9699 - logcount_predictions_loss: 0.4486 678/685 [============================>.] - ETA: 5s - loss: 62.4182 - logits_profile_predictions_loss: 61.9695 - logcount_predictions_loss: 0.4488 679/685 [============================>.] - ETA: 4s - loss: 62.4470 - logits_profile_predictions_loss: 61.9981 - logcount_predictions_loss: 0.4490 680/685 [============================>.] - ETA: 3s - loss: 62.4574 - logits_profile_predictions_loss: 62.0085 - logcount_predictions_loss: 0.4490 681/685 [============================>.] - ETA: 2s - loss: 62.4739 - logits_profile_predictions_loss: 62.0248 - logcount_predictions_loss: 0.4492 682/685 [============================>.] - ETA: 2s - loss: 62.4901 - logits_profile_predictions_loss: 62.0409 - logcount_predictions_loss: 0.4493 683/685 [============================>.] - ETA: 1s - loss: 62.4879 - logits_profile_predictions_loss: 62.0388 - logcount_predictions_loss: 0.4492 684/685 [============================>.] - ETA: 0s - loss: 62.4768 - logits_profile_predictions_loss: 62.0278 - logcount_predictions_loss: 0.4491 685/685 [==============================] - ETA: 0s - loss: 62.4816 - logits_profile_predictions_loss: 62.0324 - logcount_predictions_loss: 0.4493 Epoch 8: val_loss did not improve from 66.03979  685/685 [==============================] - 534s 779ms/step - loss: 62.4816 - logits_profile_predictions_loss: 62.0324 - logcount_predictions_loss: 0.4493 - val_loss: 66.6432 - val_logits_profile_predictions_loss: 66.0850 - val_logcount_predictions_loss: 0.5582 Epoch 9/50 1/685 [..............................] - ETA: 8:19 - loss: 53.1253 - logits_profile_predictions_loss: 52.6249 - logcount_predictions_loss: 0.5004 2/685 [..............................] - ETA: 8:11 - loss: 59.6980 - logits_profile_predictions_loss: 59.2130 - logcount_predictions_loss: 0.4850 3/685 [..............................] - ETA: 8:09 - loss: 60.9417 - logits_profile_predictions_loss: 60.4704 - logcount_predictions_loss: 0.4713 4/685 [..............................] - ETA: 8:09 - loss: 58.2638 - logits_profile_predictions_loss: 57.7672 - logcount_predictions_loss: 0.4966 5/685 [..............................] - ETA: 8:08 - loss: 60.6052 - logits_profile_predictions_loss: 60.0870 - logcount_predictions_loss: 0.5182 6/685 [..............................] - ETA: 8:08 - loss: 60.2504 - logits_profile_predictions_loss: 59.7459 - logcount_predictions_loss: 0.5045 7/685 [..............................] - ETA: 8:07 - loss: 61.0935 - logits_profile_predictions_loss: 60.5951 - logcount_predictions_loss: 0.4984 8/685 [..............................] - ETA: 8:07 - loss: 62.1517 - logits_profile_predictions_loss: 61.6417 - logcount_predictions_loss: 0.5100 9/685 [..............................] - ETA: 8:06 - loss: 61.7452 - logits_profile_predictions_loss: 61.2440 - logcount_predictions_loss: 0.5011 10/685 [..............................] - ETA: 8:05 - loss: 62.0414 - logits_profile_predictions_loss: 61.5479 - logcount_predictions_loss: 0.4935 11/685 [..............................] - ETA: 8:05 - loss: 62.0351 - logits_profile_predictions_loss: 61.5486 - logcount_predictions_loss: 0.4865 12/685 [..............................] - ETA: 8:04 - loss: 61.4043 - logits_profile_predictions_loss: 60.9259 - logcount_predictions_loss: 0.4784 13/685 [..............................] - ETA: 8:04 - loss: 62.1247 - logits_profile_predictions_loss: 61.6485 - logcount_predictions_loss: 0.4762 14/685 [..............................] - ETA: 8:03 - loss: 62.1294 - logits_profile_predictions_loss: 61.6636 - logcount_predictions_loss: 0.4658 15/685 [..............................] - ETA: 8:03 - loss: 63.7299 - logits_profile_predictions_loss: 63.2574 - logcount_predictions_loss: 0.4725 16/685 [..............................] - ETA: 8:03 - loss: 63.8034 - logits_profile_predictions_loss: 63.3248 - logcount_predictions_loss: 0.4786 17/685 [..............................] - ETA: 8:02 - loss: 63.1382 - logits_profile_predictions_loss: 62.6669 - logcount_predictions_loss: 0.4714 18/685 [..............................] - ETA: 8:01 - loss: 62.9191 - logits_profile_predictions_loss: 62.4503 - logcount_predictions_loss: 0.4687 19/685 [..............................] - ETA: 8:01 - loss: 62.4177 - logits_profile_predictions_loss: 61.9527 - logcount_predictions_loss: 0.4649 20/685 [..............................] - ETA: 8:00 - loss: 63.0337 - logits_profile_predictions_loss: 62.5693 - logcount_predictions_loss: 0.4644 21/685 [..............................] - ETA: 7:59 - loss: 62.3540 - logits_profile_predictions_loss: 61.8943 - logcount_predictions_loss: 0.4597 22/685 [..............................] - 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[==========================>...] - ETA: 41s - loss: 61.9314 - logits_profile_predictions_loss: 61.5095 - logcount_predictions_loss: 0.4219 631/685 [==========================>...] - ETA: 40s - loss: 61.9245 - logits_profile_predictions_loss: 61.5027 - logcount_predictions_loss: 0.4218 632/685 [==========================>...] - ETA: 39s - loss: 61.9569 - logits_profile_predictions_loss: 61.5348 - logcount_predictions_loss: 0.4221 633/685 [==========================>...] - ETA: 38s - loss: 61.9711 - logits_profile_predictions_loss: 61.5491 - logcount_predictions_loss: 0.4220 634/685 [==========================>...] - ETA: 38s - loss: 61.9755 - logits_profile_predictions_loss: 61.5534 - logcount_predictions_loss: 0.4221 635/685 [==========================>...] - ETA: 37s - loss: 61.9835 - logits_profile_predictions_loss: 61.5615 - logcount_predictions_loss: 0.4220 636/685 [==========================>...] - ETA: 36s - loss: 61.9703 - logits_profile_predictions_loss: 61.5482 - 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- ETA: 26s - loss: 61.9985 - logits_profile_predictions_loss: 61.5756 - logcount_predictions_loss: 0.4230 651/685 [===========================>..] - ETA: 25s - loss: 62.0074 - logits_profile_predictions_loss: 61.5846 - logcount_predictions_loss: 0.4228 652/685 [===========================>..] - ETA: 24s - loss: 61.9963 - logits_profile_predictions_loss: 61.5736 - logcount_predictions_loss: 0.4227 653/685 [===========================>..] - ETA: 23s - loss: 61.9863 - logits_profile_predictions_loss: 61.5637 - logcount_predictions_loss: 0.4226 654/685 [===========================>..] - ETA: 23s - loss: 61.9683 - logits_profile_predictions_loss: 61.5458 - logcount_predictions_loss: 0.4225 655/685 [===========================>..] - ETA: 22s - loss: 61.9741 - logits_profile_predictions_loss: 61.5513 - logcount_predictions_loss: 0.4228 656/685 [===========================>..] - ETA: 21s - loss: 61.9971 - logits_profile_predictions_loss: 61.5742 - logcount_predictions_loss: 0.4229 657/685 [===========================>..] - ETA: 20s - loss: 61.9972 - logits_profile_predictions_loss: 61.5743 - logcount_predictions_loss: 0.4229 658/685 [===========================>..] - ETA: 20s - loss: 62.0102 - logits_profile_predictions_loss: 61.5873 - logcount_predictions_loss: 0.4229 659/685 [===========================>..] - ETA: 19s - loss: 62.0041 - logits_profile_predictions_loss: 61.5808 - logcount_predictions_loss: 0.4233 660/685 [===========================>..] - ETA: 18s - loss: 62.0010 - logits_profile_predictions_loss: 61.5777 - logcount_predictions_loss: 0.4233 661/685 [===========================>..] - ETA: 17s - loss: 61.9955 - logits_profile_predictions_loss: 61.5723 - logcount_predictions_loss: 0.4233 662/685 [===========================>..] - ETA: 17s - loss: 61.9929 - logits_profile_predictions_loss: 61.5694 - logcount_predictions_loss: 0.4235 663/685 [============================>.] - ETA: 16s - loss: 62.0037 - logits_profile_predictions_loss: 61.5800 - logcount_predictions_loss: 0.4237 664/685 [============================>.] - ETA: 15s - loss: 62.0143 - logits_profile_predictions_loss: 61.5906 - logcount_predictions_loss: 0.4236 665/685 [============================>.] - ETA: 14s - loss: 62.0176 - logits_profile_predictions_loss: 61.5938 - logcount_predictions_loss: 0.4238 666/685 [============================>.] - ETA: 14s - loss: 62.0077 - logits_profile_predictions_loss: 61.5835 - logcount_predictions_loss: 0.4242 667/685 [============================>.] - ETA: 13s - loss: 62.0067 - logits_profile_predictions_loss: 61.5825 - logcount_predictions_loss: 0.4242 668/685 [============================>.] - ETA: 12s - loss: 61.9989 - logits_profile_predictions_loss: 61.5749 - logcount_predictions_loss: 0.4240 669/685 [============================>.] - ETA: 11s - loss: 62.0000 - logits_profile_predictions_loss: 61.5758 - logcount_predictions_loss: 0.4242 670/685 [============================>.] - ETA: 11s - loss: 61.9807 - logits_profile_predictions_loss: 61.5564 - logcount_predictions_loss: 0.4243 671/685 [============================>.] - ETA: 10s - loss: 61.9779 - logits_profile_predictions_loss: 61.5538 - logcount_predictions_loss: 0.4241 672/685 [============================>.] - ETA: 9s - loss: 61.9803 - logits_profile_predictions_loss: 61.5561 - logcount_predictions_loss: 0.4242  673/685 [============================>.] - ETA: 8s - loss: 61.9995 - logits_profile_predictions_loss: 61.5751 - logcount_predictions_loss: 0.4244 674/685 [============================>.] - ETA: 8s - loss: 61.9983 - logits_profile_predictions_loss: 61.5739 - logcount_predictions_loss: 0.4244 675/685 [============================>.] - ETA: 7s - loss: 61.9983 - logits_profile_predictions_loss: 61.5741 - logcount_predictions_loss: 0.4242 676/685 [============================>.] - ETA: 6s - loss: 61.9863 - logits_profile_predictions_loss: 61.5618 - logcount_predictions_loss: 0.4244 677/685 [============================>.] - ETA: 5s - loss: 62.0114 - logits_profile_predictions_loss: 61.5861 - logcount_predictions_loss: 0.4253 678/685 [============================>.] - ETA: 5s - loss: 62.0153 - logits_profile_predictions_loss: 61.5899 - logcount_predictions_loss: 0.4254 679/685 [============================>.] - ETA: 4s - loss: 62.0216 - logits_profile_predictions_loss: 61.5961 - logcount_predictions_loss: 0.4255 680/685 [============================>.] - ETA: 3s - loss: 62.0204 - logits_profile_predictions_loss: 61.5946 - logcount_predictions_loss: 0.4258 681/685 [============================>.] - ETA: 2s - loss: 62.0193 - logits_profile_predictions_loss: 61.5936 - logcount_predictions_loss: 0.4257 682/685 [============================>.] - ETA: 2s - loss: 62.0104 - logits_profile_predictions_loss: 61.5846 - logcount_predictions_loss: 0.4259 683/685 [============================>.] - ETA: 1s - loss: 62.0109 - logits_profile_predictions_loss: 61.5850 - logcount_predictions_loss: 0.4258 684/685 [============================>.] - ETA: 0s - loss: 62.0178 - logits_profile_predictions_loss: 61.5921 - logcount_predictions_loss: 0.4258 685/685 [==============================] - ETA: 0s - loss: 62.0071 - logits_profile_predictions_loss: 61.5813 - logcount_predictions_loss: 0.4258 Epoch 9: val_loss did not improve from 66.03979  685/685 [==============================] - 534s 779ms/step - loss: 62.0071 - logits_profile_predictions_loss: 61.5813 - logcount_predictions_loss: 0.4258 - val_loss: 66.9444 - val_logits_profile_predictions_loss: 66.4221 - val_logcount_predictions_loss: 0.5223 Epoch 10/50 1/685 [..............................] - ETA: 8:21 - loss: 57.9321 - logits_profile_predictions_loss: 57.5217 - logcount_predictions_loss: 0.4104 2/685 [..............................] - ETA: 8:10 - loss: 60.9163 - logits_profile_predictions_loss: 60.4134 - logcount_predictions_loss: 0.5029 3/685 [..............................] - ETA: 8:09 - loss: 62.2657 - logits_profile_predictions_loss: 61.7996 - logcount_predictions_loss: 0.4661 4/685 [..............................] - ETA: 8:09 - loss: 62.3837 - logits_profile_predictions_loss: 61.9331 - logcount_predictions_loss: 0.4507 5/685 [..............................] - ETA: 8:09 - loss: 60.2366 - logits_profile_predictions_loss: 59.7845 - logcount_predictions_loss: 0.4521 6/685 [..............................] - ETA: 8:08 - loss: 61.2845 - logits_profile_predictions_loss: 60.8157 - logcount_predictions_loss: 0.4688 7/685 [..............................] - ETA: 8:07 - loss: 61.4406 - logits_profile_predictions_loss: 60.9765 - logcount_predictions_loss: 0.4641 8/685 [..............................] - ETA: 8:07 - loss: 62.1840 - logits_profile_predictions_loss: 61.7385 - logcount_predictions_loss: 0.4455 9/685 [..............................] - ETA: 8:06 - loss: 60.9194 - logits_profile_predictions_loss: 60.4854 - logcount_predictions_loss: 0.4340 10/685 [..............................] - ETA: 8:05 - loss: 62.2496 - logits_profile_predictions_loss: 61.8050 - logcount_predictions_loss: 0.4446 11/685 [..............................] - ETA: 8:05 - loss: 61.5769 - logits_profile_predictions_loss: 61.1312 - logcount_predictions_loss: 0.4457 12/685 [..............................] - ETA: 8:04 - loss: 61.6558 - logits_profile_predictions_loss: 61.2016 - logcount_predictions_loss: 0.4542 13/685 [..............................] - ETA: 8:04 - loss: 61.6419 - logits_profile_predictions_loss: 61.1878 - logcount_predictions_loss: 0.4541 14/685 [..............................] - ETA: 8:03 - loss: 61.1595 - logits_profile_predictions_loss: 60.7005 - logcount_predictions_loss: 0.4590 15/685 [..............................] - ETA: 8:02 - loss: 60.9449 - logits_profile_predictions_loss: 60.4922 - logcount_predictions_loss: 0.4526 16/685 [..............................] - ETA: 8:02 - loss: 61.2347 - logits_profile_predictions_loss: 60.7763 - logcount_predictions_loss: 0.4584 17/685 [..............................] - ETA: 8:01 - loss: 60.2619 - logits_profile_predictions_loss: 59.8094 - logcount_predictions_loss: 0.4525 18/685 [..............................] - ETA: 8:01 - loss: 60.0316 - logits_profile_predictions_loss: 59.5880 - logcount_predictions_loss: 0.4435 19/685 [..............................] - ETA: 8:00 - loss: 59.8703 - logits_profile_predictions_loss: 59.4222 - logcount_predictions_loss: 0.4481 20/685 [..............................] - ETA: 7:59 - loss: 59.8746 - logits_profile_predictions_loss: 59.4246 - logcount_predictions_loss: 0.4500 21/685 [..............................] - ETA: 7:59 - loss: 59.7275 - logits_profile_predictions_loss: 59.2820 - logcount_predictions_loss: 0.4454 22/685 [..............................] - ETA: 7:58 - loss: 59.3389 - logits_profile_predictions_loss: 58.8964 - logcount_predictions_loss: 0.4424 23/685 [>.............................] - ETA: 7:57 - loss: 59.9780 - logits_profile_predictions_loss: 59.5400 - logcount_predictions_loss: 0.4380 24/685 [>.............................] - ETA: 7:57 - loss: 60.2909 - logits_profile_predictions_loss: 59.8573 - logcount_predictions_loss: 0.4336 25/685 [>.............................] - ETA: 7:56 - loss: 60.3538 - logits_profile_predictions_loss: 59.9173 - logcount_predictions_loss: 0.4365 26/685 [>.............................] - ETA: 7:55 - loss: 60.4434 - logits_profile_predictions_loss: 60.0066 - logcount_predictions_loss: 0.4368 27/685 [>.............................] - ETA: 7:55 - loss: 60.6808 - logits_profile_predictions_loss: 60.2477 - logcount_predictions_loss: 0.4331 28/685 [>.............................] - ETA: 7:54 - loss: 60.8235 - logits_profile_predictions_loss: 60.3911 - logcount_predictions_loss: 0.4324 29/685 [>.............................] - ETA: 7:53 - loss: 61.0065 - logits_profile_predictions_loss: 60.5787 - logcount_predictions_loss: 0.4278 30/685 [>.............................] - ETA: 7:53 - loss: 60.8043 - logits_profile_predictions_loss: 60.3783 - logcount_predictions_loss: 0.4260 31/685 [>.............................] - ETA: 7:52 - loss: 60.4930 - logits_profile_predictions_loss: 60.0626 - logcount_predictions_loss: 0.4304 32/685 [>.............................] - ETA: 7:51 - loss: 60.3747 - logits_profile_predictions_loss: 59.9445 - logcount_predictions_loss: 0.4302 33/685 [>.............................] - ETA: 7:51 - loss: 60.2997 - logits_profile_predictions_loss: 59.8681 - logcount_predictions_loss: 0.4316 34/685 [>.............................] - ETA: 7:50 - loss: 60.1679 - logits_profile_predictions_loss: 59.7375 - logcount_predictions_loss: 0.4304 35/685 [>.............................] - ETA: 7:50 - loss: 60.0503 - logits_profile_predictions_loss: 59.6198 - logcount_predictions_loss: 0.4305 36/685 [>.............................] - ETA: 7:49 - loss: 60.2952 - logits_profile_predictions_loss: 59.8650 - logcount_predictions_loss: 0.4303 37/685 [>.............................] - ETA: 7:48 - loss: 60.0635 - logits_profile_predictions_loss: 59.6337 - logcount_predictions_loss: 0.4298 38/685 [>.............................] - ETA: 7:48 - loss: 60.3460 - logits_profile_predictions_loss: 59.9140 - logcount_predictions_loss: 0.4320 39/685 [>.............................] - ETA: 7:47 - loss: 60.2707 - logits_profile_predictions_loss: 59.8391 - logcount_predictions_loss: 0.4317 40/685 [>.............................] - ETA: 7:46 - loss: 60.2011 - logits_profile_predictions_loss: 59.7712 - logcount_predictions_loss: 0.4299 41/685 [>.............................] - ETA: 7:46 - loss: 59.9663 - logits_profile_predictions_loss: 59.5346 - logcount_predictions_loss: 0.4317 42/685 [>.............................] - ETA: 7:45 - loss: 60.1362 - logits_profile_predictions_loss: 59.7060 - logcount_predictions_loss: 0.4302 43/685 [>.............................] - ETA: 7:44 - loss: 60.1299 - logits_profile_predictions_loss: 59.7002 - logcount_predictions_loss: 0.4297 44/685 [>.............................] - ETA: 7:44 - loss: 60.3103 - logits_profile_predictions_loss: 59.8793 - logcount_predictions_loss: 0.4310 45/685 [>.............................] - ETA: 7:43 - loss: 60.2642 - logits_profile_predictions_loss: 59.8364 - logcount_predictions_loss: 0.4278 46/685 [=>............................] - ETA: 7:43 - loss: 60.2513 - logits_profile_predictions_loss: 59.8261 - logcount_predictions_loss: 0.4253 47/685 [=>............................] - ETA: 7:43 - loss: 60.0462 - logits_profile_predictions_loss: 59.6237 - logcount_predictions_loss: 0.4225 48/685 [=>............................] - ETA: 7:42 - loss: 60.0495 - logits_profile_predictions_loss: 59.6255 - logcount_predictions_loss: 0.4240 49/685 [=>............................] - ETA: 7:41 - loss: 59.9678 - logits_profile_predictions_loss: 59.5446 - logcount_predictions_loss: 0.4232 50/685 [=>............................] - ETA: 7:41 - loss: 60.0454 - logits_profile_predictions_loss: 59.6215 - logcount_predictions_loss: 0.4239 51/685 [=>............................] - ETA: 7:40 - loss: 60.0271 - logits_profile_predictions_loss: 59.6033 - logcount_predictions_loss: 0.4238 52/685 [=>............................] - ETA: 7:39 - loss: 59.9281 - logits_profile_predictions_loss: 59.5075 - logcount_predictions_loss: 0.4206 53/685 [=>............................] - ETA: 7:39 - loss: 60.1754 - logits_profile_predictions_loss: 59.7558 - logcount_predictions_loss: 0.4196 54/685 [=>............................] - ETA: 7:38 - loss: 60.1687 - logits_profile_predictions_loss: 59.7499 - logcount_predictions_loss: 0.4188 55/685 [=>............................] - ETA: 7:37 - loss: 60.1121 - logits_profile_predictions_loss: 59.6893 - logcount_predictions_loss: 0.4228 56/685 [=>............................] - ETA: 7:37 - loss: 60.3547 - logits_profile_predictions_loss: 59.9325 - logcount_predictions_loss: 0.4223 57/685 [=>............................] - ETA: 7:36 - loss: 60.3776 - logits_profile_predictions_loss: 59.9574 - 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- ETA: 24s - loss: 61.2928 - logits_profile_predictions_loss: 60.8793 - logcount_predictions_loss: 0.4136 653/685 [===========================>..] - ETA: 23s - loss: 61.2905 - logits_profile_predictions_loss: 60.8767 - logcount_predictions_loss: 0.4138 654/685 [===========================>..] - ETA: 23s - loss: 61.3046 - logits_profile_predictions_loss: 60.8904 - logcount_predictions_loss: 0.4143 655/685 [===========================>..] - ETA: 22s - loss: 61.3188 - logits_profile_predictions_loss: 60.9047 - logcount_predictions_loss: 0.4142 656/685 [===========================>..] - ETA: 21s - loss: 61.3354 - logits_profile_predictions_loss: 60.9213 - logcount_predictions_loss: 0.4142 657/685 [===========================>..] - ETA: 20s - loss: 61.3303 - logits_profile_predictions_loss: 60.9160 - logcount_predictions_loss: 0.4143 658/685 [===========================>..] - ETA: 20s - loss: 61.3300 - logits_profile_predictions_loss: 60.9157 - logcount_predictions_loss: 0.4144 659/685 [===========================>..] - ETA: 19s - loss: 61.3291 - logits_profile_predictions_loss: 60.9148 - logcount_predictions_loss: 0.4144 660/685 [===========================>..] - ETA: 18s - loss: 61.3353 - logits_profile_predictions_loss: 60.9208 - logcount_predictions_loss: 0.4145 661/685 [===========================>..] - ETA: 17s - loss: 61.3460 - logits_profile_predictions_loss: 60.9315 - logcount_predictions_loss: 0.4145 662/685 [===========================>..] - ETA: 17s - loss: 61.3531 - logits_profile_predictions_loss: 60.9386 - logcount_predictions_loss: 0.4146 663/685 [============================>.] - ETA: 16s - loss: 61.3426 - logits_profile_predictions_loss: 60.9282 - logcount_predictions_loss: 0.4144 664/685 [============================>.] - ETA: 15s - loss: 61.3452 - logits_profile_predictions_loss: 60.9309 - logcount_predictions_loss: 0.4143 665/685 [============================>.] - ETA: 14s - loss: 61.3505 - logits_profile_predictions_loss: 60.9361 - logcount_predictions_loss: 0.4145 666/685 [============================>.] - ETA: 14s - loss: 61.3547 - logits_profile_predictions_loss: 60.9401 - logcount_predictions_loss: 0.4146 667/685 [============================>.] - ETA: 13s - loss: 61.3560 - logits_profile_predictions_loss: 60.9414 - logcount_predictions_loss: 0.4146 668/685 [============================>.] - ETA: 12s - loss: 61.3508 - logits_profile_predictions_loss: 60.9364 - logcount_predictions_loss: 0.4145 669/685 [============================>.] - ETA: 11s - loss: 61.3607 - logits_profile_predictions_loss: 60.9461 - logcount_predictions_loss: 0.4146 670/685 [============================>.] - ETA: 11s - loss: 61.3526 - logits_profile_predictions_loss: 60.9378 - logcount_predictions_loss: 0.4148 671/685 [============================>.] - ETA: 10s - loss: 61.3594 - logits_profile_predictions_loss: 60.9445 - logcount_predictions_loss: 0.4149 672/685 [============================>.] - ETA: 9s - loss: 61.3505 - logits_profile_predictions_loss: 60.9358 - logcount_predictions_loss: 0.4148  673/685 [============================>.] - ETA: 8s - loss: 61.3518 - logits_profile_predictions_loss: 60.9370 - logcount_predictions_loss: 0.4148 674/685 [============================>.] - ETA: 8s - loss: 61.3315 - logits_profile_predictions_loss: 60.9168 - logcount_predictions_loss: 0.4147 675/685 [============================>.] - ETA: 7s - loss: 61.3483 - logits_profile_predictions_loss: 60.9335 - logcount_predictions_loss: 0.4148 676/685 [============================>.] - ETA: 6s - loss: 61.3516 - logits_profile_predictions_loss: 60.9370 - logcount_predictions_loss: 0.4146 677/685 [============================>.] - ETA: 5s - loss: 61.3345 - logits_profile_predictions_loss: 60.9201 - logcount_predictions_loss: 0.4144 678/685 [============================>.] - ETA: 5s - loss: 61.3281 - logits_profile_predictions_loss: 60.9137 - logcount_predictions_loss: 0.4145 679/685 [============================>.] - ETA: 4s - loss: 61.3429 - logits_profile_predictions_loss: 60.9285 - logcount_predictions_loss: 0.4144 680/685 [============================>.] - ETA: 3s - loss: 61.3411 - logits_profile_predictions_loss: 60.9265 - logcount_predictions_loss: 0.4146 681/685 [============================>.] - ETA: 2s - loss: 61.3515 - logits_profile_predictions_loss: 60.9366 - logcount_predictions_loss: 0.4150 682/685 [============================>.] - ETA: 2s - loss: 61.3600 - logits_profile_predictions_loss: 60.9452 - logcount_predictions_loss: 0.4148 683/685 [============================>.] - ETA: 1s - loss: 61.3636 - logits_profile_predictions_loss: 60.9489 - logcount_predictions_loss: 0.4148 684/685 [============================>.] - ETA: 0s - loss: 61.3607 - logits_profile_predictions_loss: 60.9461 - logcount_predictions_loss: 0.4146 685/685 [==============================] - ETA: 0s - loss: 61.3601 - logits_profile_predictions_loss: 60.9452 - logcount_predictions_loss: 0.4149 Epoch 10: val_loss did not improve from 66.03979 Restoring model weights from the end of the best epoch: 5.  685/685 [==============================] - 534s 779ms/step - loss: 61.3601 - logits_profile_predictions_loss: 60.9452 - logcount_predictions_loss: 0.4149 - val_loss: 67.2282 - val_logits_profile_predictions_loss: 66.8509 - val_logcount_predictions_loss: 0.3773 Epoch 10: early stopping save model save model without bias got the model loading peaks... got split:test for bed regions:(10928, 10) 0/171 100/171 MOTIF_NAME MOTIF_PWM_FWD 0 tn5_1 GCACAGTACAGAGCTG 1 tn5_2 GTGCACAGTTCTAGAGTGTGCAG 2 tn5_3 CCTCTACACTGTGCAGAA 3 tn5_4 GCACAGTTCTAGACTGTGCAG 4 tn5_5 CTGCACAGTGTAGAGTTGTGC got the model Model: "model_1" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== sequence (InputLayer) [(None, 2114, 4)] 0 [] wo_bias_bpnet_1st_conv (Conv1D (None, 2094, 512) 43520 ['sequence[0][0]'] ) wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 ['wo_bias_bpnet_1st_conv[0][0]'] wo_bias_bpnet_1crop (Cropping1 (None, 2090, 512) 0 ['wo_bias_bpnet_1st_conv[0][0]'] D) add (Add) (None, 2090, 512) 0 ['wo_bias_bpnet_1conv[0][0]', 'wo_bias_bpnet_1crop[0][0]'] wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 ['add[0][0]'] wo_bias_bpnet_2crop (Cropping1 (None, 2082, 512) 0 ['add[0][0]'] D) add_1 (Add) (None, 2082, 512) 0 ['wo_bias_bpnet_2conv[0][0]', 'wo_bias_bpnet_2crop[0][0]'] wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 ['add_1[0][0]'] wo_bias_bpnet_3crop (Cropping1 (None, 2066, 512) 0 ['add_1[0][0]'] D) add_2 (Add) (None, 2066, 512) 0 ['wo_bias_bpnet_3conv[0][0]', 'wo_bias_bpnet_3crop[0][0]'] wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 ['add_2[0][0]'] wo_bias_bpnet_4crop (Cropping1 (None, 2034, 512) 0 ['add_2[0][0]'] D) add_3 (Add) (None, 2034, 512) 0 ['wo_bias_bpnet_4conv[0][0]', 'wo_bias_bpnet_4crop[0][0]'] wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 ['add_3[0][0]'] wo_bias_bpnet_5crop (Cropping1 (None, 1970, 512) 0 ['add_3[0][0]'] D) add_4 (Add) (None, 1970, 512) 0 ['wo_bias_bpnet_5conv[0][0]', 'wo_bias_bpnet_5crop[0][0]'] wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 ['add_4[0][0]'] wo_bias_bpnet_6crop (Cropping1 (None, 1842, 512) 0 ['add_4[0][0]'] D) add_5 (Add) (None, 1842, 512) 0 ['wo_bias_bpnet_6conv[0][0]', 'wo_bias_bpnet_6crop[0][0]'] wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 ['add_5[0][0]'] wo_bias_bpnet_7crop (Cropping1 (None, 1586, 512) 0 ['add_5[0][0]'] D) add_6 (Add) (None, 1586, 512) 0 ['wo_bias_bpnet_7conv[0][0]', 'wo_bias_bpnet_7crop[0][0]'] wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 ['add_6[0][0]'] wo_bias_bpnet_8crop (Cropping1 (None, 1074, 512) 0 ['add_6[0][0]'] D) add_7 (Add) (None, 1074, 512) 0 ['wo_bias_bpnet_8conv[0][0]', 'wo_bias_bpnet_8crop[0][0]'] wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 ['add_7[0][0]'] (Conv1D) wo_bias_bpnet_logitt_before_fl (None, 1000, 1) 0 ['wo_bias_bpnet_prof_out_precrop[ atten (Cropping1D) 0][0]'] gap (GlobalAveragePooling1D) (None, 512) 0 ['add_7[0][0]'] wo_bias_bpnet_logits_profile_p (None, 1000) 0 ['wo_bias_bpnet_logitt_before_fla redictions (Flatten) tten[0][0]'] wo_bias_bpnet_logcount_predict (None, 1) 513 ['gap[0][0]'] ions (Dense) ================================================================================================== Total params: 6,377,986 Trainable params: 6,377,986 Non-trainable params: 0 __________________________________________________________________________________________________ inferred model inputlen: 2114 inferred model outputlen: 1000 inserting motif: control 1/171 [..............................] - ETA: 49s 2/171 [..............................] - ETA: 38s 3/171 [..............................] - ETA: 38s 4/171 [..............................] - ETA: 37s 5/171 [..............................] - ETA: 37s 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[==============================] - 40s 236ms/step Saving marginal footprints got the model Model: "model_1" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== sequence (InputLayer) [(None, 2114, 4)] 0 [] wo_bias_bpnet_1st_conv (Conv1D (None, 2094, 512) 43520 ['sequence[0][0]'] ) wo_bias_bpnet_1conv (Conv1D) (None, 2090, 512) 786944 ['wo_bias_bpnet_1st_conv[0][0]'] wo_bias_bpnet_1crop (Cropping1 (None, 2090, 512) 0 ['wo_bias_bpnet_1st_conv[0][0]'] D) add (Add) (None, 2090, 512) 0 ['wo_bias_bpnet_1conv[0][0]', 'wo_bias_bpnet_1crop[0][0]'] wo_bias_bpnet_2conv (Conv1D) (None, 2082, 512) 786944 ['add[0][0]'] wo_bias_bpnet_2crop (Cropping1 (None, 2082, 512) 0 ['add[0][0]'] D) add_1 (Add) (None, 2082, 512) 0 ['wo_bias_bpnet_2conv[0][0]', 'wo_bias_bpnet_2crop[0][0]'] wo_bias_bpnet_3conv (Conv1D) (None, 2066, 512) 786944 ['add_1[0][0]'] wo_bias_bpnet_3crop (Cropping1 (None, 2066, 512) 0 ['add_1[0][0]'] D) add_2 (Add) (None, 2066, 512) 0 ['wo_bias_bpnet_3conv[0][0]', 'wo_bias_bpnet_3crop[0][0]'] wo_bias_bpnet_4conv (Conv1D) (None, 2034, 512) 786944 ['add_2[0][0]'] wo_bias_bpnet_4crop (Cropping1 (None, 2034, 512) 0 ['add_2[0][0]'] D) add_3 (Add) (None, 2034, 512) 0 ['wo_bias_bpnet_4conv[0][0]', 'wo_bias_bpnet_4crop[0][0]'] wo_bias_bpnet_5conv (Conv1D) (None, 1970, 512) 786944 ['add_3[0][0]'] wo_bias_bpnet_5crop (Cropping1 (None, 1970, 512) 0 ['add_3[0][0]'] D) add_4 (Add) (None, 1970, 512) 0 ['wo_bias_bpnet_5conv[0][0]', 'wo_bias_bpnet_5crop[0][0]'] wo_bias_bpnet_6conv (Conv1D) (None, 1842, 512) 786944 ['add_4[0][0]'] wo_bias_bpnet_6crop (Cropping1 (None, 1842, 512) 0 ['add_4[0][0]'] D) add_5 (Add) (None, 1842, 512) 0 ['wo_bias_bpnet_6conv[0][0]', 'wo_bias_bpnet_6crop[0][0]'] wo_bias_bpnet_7conv (Conv1D) (None, 1586, 512) 786944 ['add_5[0][0]'] wo_bias_bpnet_7crop (Cropping1 (None, 1586, 512) 0 ['add_5[0][0]'] D) add_6 (Add) (None, 1586, 512) 0 ['wo_bias_bpnet_7conv[0][0]', 'wo_bias_bpnet_7crop[0][0]'] wo_bias_bpnet_8conv (Conv1D) (None, 1074, 512) 786944 ['add_6[0][0]'] wo_bias_bpnet_8crop (Cropping1 (None, 1074, 512) 0 ['add_6[0][0]'] D) add_7 (Add) (None, 1074, 512) 0 ['wo_bias_bpnet_8conv[0][0]', 'wo_bias_bpnet_8crop[0][0]'] wo_bias_bpnet_prof_out_precrop (None, 1000, 1) 38401 ['add_7[0][0]'] (Conv1D) wo_bias_bpnet_logitt_before_fl (None, 1000, 1) 0 ['wo_bias_bpnet_prof_out_precrop[ atten (Cropping1D) 0][0]'] gap (GlobalAveragePooling1D) (None, 512) 0 ['add_7[0][0]'] wo_bias_bpnet_logits_profile_p (None, 1000) 0 ['wo_bias_bpnet_logitt_before_fla redictions (Flatten) tten[0][0]'] wo_bias_bpnet_logcount_predict (None, 1) 513 ['gap[0][0]'] ions (Dense) ================================================================================================== Total params: 6,377,986 Trainable params: 6,377,986 Non-trainable params: 0 __________________________________________________________________________________________________ inferred model inputlen: 2114 Seqs dimension : (30000, 2114, 4) Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: AddV2 used in model but handling of op is not specified by shap; will use original gradients Warning: StopGradient used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Warning: SpaceToBatchND used in model but handling of op is not specified by shap; will use original gradients Warning: BatchToSpaceND used in model but handling of op is not specified by shap; will use original gradients Generating 'profile' shap scores Done 0 examples of 30000 Done 100 examples of 30000 Done 200 examples of 30000 Done 300 examples of 30000 Done 400 examples of 30000 Done 500 examples of 30000 Done 600 examples of 30000 Done 700 examples of 30000 Done 800 examples of 30000 Done 900 examples of 30000 Done 1000 examples of 30000 Done 1100 examples of 30000 Done 1200 examples of 30000 Done 1300 examples of 30000 Done 1400 examples of 30000 Done 1500 examples of 30000 Done 1600 examples of 30000 Done 1700 examples of 30000 Done 1800 examples of 30000 Done 1900 examples of 30000 Done 2000 examples of 30000 Done 2100 examples of 30000 Done 2200 examples of 30000 Done 2300 examples of 30000 Done 2400 examples of 30000 Done 2500 examples of 30000 Done 2600 examples of 30000 Done 2700 examples of 30000 Done 2800 examples of 30000 Done 2900 examples of 30000 Done 3000 examples of 30000 Done 3100 examples of 30000 Done 3200 examples of 30000 Done 3300 examples of 30000 Done 3400 examples of 30000 Done 3500 examples of 30000 Done 3600 examples of 30000 Done 3700 examples of 30000 Done 3800 examples of 30000 Done 3900 examples of 30000 Done 4000 examples of 30000 Done 4100 examples of 30000 Done 4200 examples of 30000 Done 4300 examples of 30000 Done 4400 examples of 30000 Done 4500 examples of 30000 Done 4600 examples of 30000 Done 4700 examples of 30000 Done 4800 examples of 30000 Done 4900 examples of 30000 Done 5000 examples of 30000 Done 5100 examples of 30000 Done 5200 examples of 30000 Done 5300 examples of 30000 Done 5400 examples of 30000 Done 5500 examples of 30000 Done 5600 examples of 30000 Done 5700 examples of 30000 Done 5800 examples of 30000 Done 5900 examples of 30000 Done 6000 examples of 30000 Done 6100 examples of 30000 Done 6200 examples of 30000 Done 6300 examples of 30000 Done 6400 examples of 30000 Done 6500 examples of 30000 Done 6600 examples of 30000 Done 6700 examples of 30000 Done 6800 examples of 30000 Done 6900 examples of 30000 Done 7000 examples of 30000 Done 7100 examples of 30000 Done 7200 examples of 30000 Done 7300 examples of 30000 Done 7400 examples of 30000 Done 7500 examples of 30000 Done 7600 examples of 30000 Done 7700 examples of 30000 Done 7800 examples of 30000 Done 7900 examples of 30000 Done 8000 examples of 30000 Done 8100 examples of 30000 Done 8200 examples of 30000 Done 8300 examples of 30000 Done 8400 examples of 30000 Done 8500 examples of 30000 Done 8600 examples of 30000 Done 8700 examples of 30000 Done 8800 examples of 30000 Done 8900 examples of 30000 Done 9000 examples of 30000 Done 9100 examples of 30000 Done 9200 examples of 30000 Done 9300 examples of 30000 Done 9400 examples of 30000 Done 9500 examples of 30000 Done 9600 examples of 30000 Done 9700 examples of 30000 Done 9800 examples of 30000 Done 9900 examples of 30000 Done 10000 examples of 30000 Done 10100 examples of 30000 Done 10200 examples of 30000 Done 10300 examples of 30000 Done 10400 examples of 30000 Done 10500 examples of 30000 Done 10600 examples of 30000 Done 10700 examples of 30000 Done 10800 examples of 30000 Done 10900 examples of 30000 Done 11000 examples of 30000 Done 11100 examples of 30000 Done 11200 examples of 30000 Done 11300 examples of 30000 Done 11400 examples of 30000 Done 11500 examples of 30000 Done 11600 examples of 30000 Done 11700 examples of 30000 Done 11800 examples of 30000 Done 11900 examples of 30000 Done 12000 examples of 30000 Done 12100 examples of 30000 Done 12200 examples of 30000 Done 12300 examples of 30000 Done 12400 examples of 30000 Done 12500 examples of 30000 Done 12600 examples of 30000 Done 12700 examples of 30000 Done 12800 examples of 30000 Done 12900 examples of 30000 Done 13000 examples of 30000 Done 13100 examples of 30000 Done 13200 examples of 30000 Done 13300 examples of 30000 Done 13400 examples of 30000 Done 13500 examples of 30000 Done 13600 examples of 30000 Done 13700 examples of 30000 Done 13800 examples of 30000 Done 13900 examples of 30000 Done 14000 examples of 30000 Done 14100 examples of 30000 Done 14200 examples of 30000 Done 14300 examples of 30000 Done 14400 examples of 30000 Done 14500 examples of 30000 Done 14600 examples of 30000 Done 14700 examples of 30000 Done 14800 examples of 30000 Done 14900 examples of 30000 Done 15000 examples of 30000 Done 15100 examples of 30000 Done 15200 examples of 30000 Done 15300 examples of 30000 Done 15400 examples of 30000 Done 15500 examples of 30000 Done 15600 examples of 30000 Done 15700 examples of 30000 Done 15800 examples of 30000 Done 15900 examples of 30000 Done 16000 examples of 30000 Done 16100 examples of 30000 Done 16200 examples of 30000 Done 16300 examples of 30000 Done 16400 examples of 30000 Done 16500 examples of 30000 Done 16600 examples of 30000 Done 16700 examples of 30000 Done 16800 examples of 30000 Done 16900 examples of 30000 Done 17000 examples of 30000 Done 17100 examples of 30000 Done 17200 examples of 30000 Done 17300 examples of 30000 Done 17400 examples of 30000 Done 17500 examples of 30000 Done 17600 examples of 30000 Done 17700 examples of 30000 Done 17800 examples of 30000 Done 17900 examples of 30000 Done 18000 examples of 30000 Done 18100 examples of 30000 Done 18200 examples of 30000 Done 18300 examples of 30000 Done 18400 examples of 30000 Done 18500 examples of 30000 Done 18600 examples of 30000 Done 18700 examples of 30000 Done 18800 examples of 30000 Done 18900 examples of 30000 Done 19000 examples of 30000 Done 19100 examples of 30000 Done 19200 examples of 30000 Done 19300 examples of 30000 Done 19400 examples of 30000 Done 19500 examples of 30000 Done 19600 examples of 30000 Done 19700 examples of 30000 Done 19800 examples of 30000 Done 19900 examples of 30000 Done 20000 examples of 30000 Done 20100 examples of 30000 Done 20200 examples of 30000 Done 20300 examples of 30000 Done 20400 examples of 30000 Done 20500 examples of 30000 Done 20600 examples of 30000 Done 20700 examples of 30000 Done 20800 examples of 30000 Done 20900 examples of 30000 Done 21000 examples of 30000 Done 21100 examples of 30000 Done 21200 examples of 30000 Done 21300 examples of 30000 Done 21400 examples of 30000 Done 21500 examples of 30000 Done 21600 examples of 30000 Done 21700 examples of 30000 Done 21800 examples of 30000 Done 21900 examples of 30000 Done 22000 examples of 30000 Done 22100 examples of 30000 Done 22200 examples of 30000 Done 22300 examples of 30000 Done 22400 examples of 30000 Done 22500 examples of 30000 Done 22600 examples of 30000 Done 22700 examples of 30000 Done 22800 examples of 30000 Done 22900 examples of 30000 Done 23000 examples of 30000 Done 23100 examples of 30000 Done 23200 examples of 30000 Done 23300 examples of 30000 Done 23400 examples of 30000 Done 23500 examples of 30000 Done 23600 examples of 30000 Done 23700 examples of 30000 Done 23800 examples of 30000 Done 23900 examples of 30000 Done 24000 examples of 30000 Done 24100 examples of 30000 Done 24200 examples of 30000 Done 24300 examples of 30000 Done 24400 examples of 30000 Done 24500 examples of 30000 Done 24600 examples of 30000 Done 24700 examples of 30000 Done 24800 examples of 30000 Done 24900 examples of 30000 Done 25000 examples of 30000 Done 25100 examples of 30000 Done 25200 examples of 30000 Done 25300 examples of 30000 Done 25400 examples of 30000 Done 25500 examples of 30000 Done 25600 examples of 30000 Done 25700 examples of 30000 Done 25800 examples of 30000 Done 25900 examples of 30000 Done 26000 examples of 30000 Done 26100 examples of 30000 Done 26200 examples of 30000 Done 26300 examples of 30000 Done 26400 examples of 30000 Done 26500 examples of 30000 Done 26600 examples of 30000 Done 26700 examples of 30000 Done 26800 examples of 30000 Done 26900 examples of 30000 Done 27000 examples of 30000 Done 27100 examples of 30000 Done 27200 examples of 30000 Done 27300 examples of 30000 Done 27400 examples of 30000 Done 27500 examples of 30000 Done 27600 examples of 30000 Done 27700 examples of 30000 Done 27800 examples of 30000 Done 27900 examples of 30000 Done 28000 examples of 30000 Done 28100 examples of 30000 Done 28200 examples of 30000 Done 28300 examples of 30000 Done 28400 examples of 30000 Done 28500 examples of 30000 Done 28600 examples of 30000 Done 28700 examples of 30000 Done 28800 examples of 30000 Done 28900 examples of 30000 Done 29000 examples of 30000 Done 29100 examples of 30000 Done 29200 examples of 30000 Done 29300 examples of 30000 Done 29400 examples of 30000 Done 29500 examples of 30000 Done 29600 examples of 30000 Done 29700 examples of 30000 Done 29800 examples of 30000 Done 29900 examples of 30000 Saving 'profile' scores