WiGesture_CSI-BERT/notebook.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyNPpHnUKo9GLYA0wY+U8zPH"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1J9zDtHb0N-C","executionInfo":{"status":"ok","timestamp":1755448121484,"user_tz":-345,"elapsed":1750,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}},"outputId":"83b06b8d-c142-4252-eb19-0dab1dd9540f"},"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'CSI-BERT'...\n","remote: Enumerating objects: 176, done.\u001b[K\n","remote: Counting objects: 100% (176/176), done.\u001b[K\n","remote: Compressing objects: 100% (137/137), done.\u001b[K\n","remote: Total 176 (delta 97), reused 97 (delta 35), pack-reused 0 (from 0)\u001b[K\n","Receiving objects: 100% (176/176), 25.90 MiB | 35.74 MiB/s, done.\n","Resolving deltas: 100% (97/97), done.\n","/content/CSI-BERT\n"]}],"source":["!git clone https://github.com/RS2002/CSI-BERT.git\n","%cd CSI-BERT\n"]},{"cell_type":"code","source":["!unzip \"/content/WiGesture.zip\""],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"266fRIJR0pEh","executionInfo":{"status":"ok","timestamp":1755448230095,"user_tz":-345,"elapsed":1234,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}},"outputId":"7fe0b016-b042-4cf3-9042-04f84c3e127a"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["Archive:  /content/WiGesture.zip\n","   creating: dataset/\n","   creating: dataset/dynamic/\n","   creating: dataset/dynamic/ID1/\n","  inflating: dataset/dynamic/ID1/applause.csv  \n","  inflating: dataset/dynamic/ID1/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID1/frontandafter.csv  \n","  inflating: dataset/dynamic/ID1/leftandright.csv  \n","  inflating: dataset/dynamic/ID1/upanddown.csv  \n","  inflating: dataset/dynamic/ID1/waveright.csv  \n","   creating: dataset/dynamic/ID2/\n","  inflating: dataset/dynamic/ID2/applause.csv  \n","  inflating: dataset/dynamic/ID2/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID2/frontandafter.csv  \n","  inflating: dataset/dynamic/ID2/leftandright.csv  \n","  inflating: dataset/dynamic/ID2/upanddown.csv  \n","  inflating: dataset/dynamic/ID2/waveright.csv  \n","   creating: dataset/dynamic/ID3/\n","  inflating: dataset/dynamic/ID3/applause.csv  \n","  inflating: dataset/dynamic/ID3/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID3/frontandafter.csv  \n","  inflating: dataset/dynamic/ID3/leftandright.csv  \n","  inflating: dataset/dynamic/ID3/upanddown.csv  \n","  inflating: dataset/dynamic/ID3/waveright.csv  \n","   creating: dataset/dynamic/ID4/\n","  inflating: dataset/dynamic/ID4/applause.csv  \n","  inflating: dataset/dynamic/ID4/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID4/frontandafter.csv  \n","  inflating: dataset/dynamic/ID4/leftandright.csv  \n","  inflating: dataset/dynamic/ID4/upanddown.csv  \n","  inflating: dataset/dynamic/ID4/waveright.csv  \n","   creating: dataset/dynamic/ID5/\n","  inflating: dataset/dynamic/ID5/applause.csv  \n","  inflating: dataset/dynamic/ID5/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID5/frontandafter.csv  \n","  inflating: dataset/dynamic/ID5/leftandright.csv  \n","  inflating: dataset/dynamic/ID5/upanddown.csv  \n","   creating: dataset/dynamic/ID6/\n","  inflating: dataset/dynamic/ID6/applause.csv  \n","  inflating: dataset/dynamic/ID6/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID6/frontandafter.csv  \n","  inflating: dataset/dynamic/ID6/leftandright.csv  \n","  inflating: dataset/dynamic/ID6/upanddown.csv  \n","  inflating: dataset/dynamic/ID6/waveright.csv  \n","   creating: dataset/dynamic/ID7/\n","  inflating: dataset/dynamic/ID7/applause.csv  \n","  inflating: dataset/dynamic/ID7/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID7/frontandafter.csv  \n","  inflating: dataset/dynamic/ID7/leftandright.csv  \n","  inflating: dataset/dynamic/ID7/upanddown.csv  \n","  inflating: dataset/dynamic/ID7/waveright.csv  \n","   creating: dataset/dynamic/ID8/\n","  inflating: dataset/dynamic/ID8/applause.csv  \n","  inflating: dataset/dynamic/ID8/circleclockwise.csv  \n","  inflating: dataset/dynamic/ID8/frontandafter.csv  \n","  inflating: dataset/dynamic/ID8/leftandright.csv  \n","  inflating: dataset/dynamic/ID8/upanddown.csv  \n","  inflating: dataset/dynamic/ID8/waveright.csv  \n","   creating: dataset/static/\n","   creating: dataset/static/ID1/\n","  inflating: dataset/static/ID1/Gesture1.csv  \n","  inflating: dataset/static/ID1/Gesture2.csv  \n","  inflating: dataset/static/ID1/Gesture3.csv  \n","  inflating: dataset/static/ID1/Gesture4.csv  \n","  inflating: dataset/static/ID1/Gesture5.csv  \n","  inflating: dataset/static/ID1/Gesture6.csv  \n","  inflating: dataset/static/ID1/Gesture7.csv  \n","  inflating: dataset/static/ID1/Gesture8.csv  \n","  inflating: dataset/static/ID1/Gesture9.csv  \n","   creating: dataset/static/ID2/\n","  inflating: dataset/static/ID2/Gesture1.csv  \n","  inflating: dataset/static/ID2/Gesture2.csv  \n","  inflating: dataset/static/ID2/Gesture3.csv  \n","  inflating: dataset/static/ID2/Gesture4.csv  \n","  inflating: dataset/static/ID2/Gesture5.csv  \n","  inflating: dataset/static/ID2/Gesture6.csv  \n","  inflating: dataset/static/ID2/Gesture7.csv  \n","  inflating: dataset/static/ID2/Gesture8.csv  \n","  inflating: dataset/static/ID2/Gesture9.csv  \n","   creating: dataset/static/ID3/\n","  inflating: dataset/static/ID3/Gesture1.csv  \n","  inflating: dataset/static/ID3/Gesture2.csv  \n","  inflating: dataset/static/ID3/Gesture3.csv  \n","  inflating: dataset/static/ID3/Gesture4.csv  \n","  inflating: dataset/static/ID3/Gesture5.csv  \n","  inflating: dataset/static/ID3/Gesture6.csv  \n","  inflating: dataset/static/ID3/Gesture7.csv  \n","  inflating: dataset/static/ID3/Gesture8.csv  \n","  inflating: dataset/static/ID3/Gesture9.csv  \n","   creating: dataset/static/ID4/\n","  inflating: dataset/static/ID4/Gesture1.csv  \n","  inflating: dataset/static/ID4/Gesture2.csv  \n","  inflating: dataset/static/ID4/Gesture3.csv  \n","  inflating: dataset/static/ID4/Gesture4.csv  \n","  inflating: dataset/static/ID4/Gesture5.csv  \n","  inflating: dataset/static/ID4/Gesture6.csv  \n","  inflating: dataset/static/ID4/Gesture7.csv  \n","  inflating: dataset/static/ID4/Gesture8.csv  \n","  inflating: dataset/static/ID4/Gesture9.csv  \n","   creating: dataset/static/ID5/\n","  inflating: dataset/static/ID5/Gesture1.csv  \n","  inflating: dataset/static/ID5/Gesture2.csv  \n","  inflating: dataset/static/ID5/Gesture3.csv  \n","  inflating: dataset/static/ID5/Gesture4.csv  \n","  inflating: dataset/static/ID5/Gesture5.csv  \n","  inflating: dataset/static/ID5/Gesture6.csv  \n","  inflating: dataset/static/ID5/Gesture7.csv  \n","  inflating: dataset/static/ID5/Gesture8.csv  \n","  inflating: dataset/static/ID5/Gesture9.csv  \n","   creating: dataset/static/ID6/\n","  inflating: dataset/static/ID6/Gesture1.csv  \n","  inflating: dataset/static/ID6/Gesture2.csv  \n","  inflating: dataset/static/ID6/Gesture3.csv  \n","  inflating: dataset/static/ID6/Gesture4.csv  \n","  inflating: dataset/static/ID6/Gesture5.csv  \n","  inflating: dataset/static/ID6/Gesture6.csv  \n","  inflating: dataset/static/ID6/Gesture7.csv  \n","  inflating: dataset/static/ID6/Gesture8.csv  \n","  inflating: dataset/static/ID6/Gesture9.csv  \n","   creating: dataset/static/ID7/\n","  inflating: dataset/static/ID7/Gesture1.csv  \n","  inflating: dataset/static/ID7/Gesture2.csv  \n","  inflating: dataset/static/ID7/Gesture3.csv  \n","  inflating: dataset/static/ID7/Gesture4.csv  \n","  inflating: dataset/static/ID7/Gesture5.csv  \n","  inflating: dataset/static/ID7/Gesture6.csv  \n","  inflating: dataset/static/ID7/Gesture7.csv  \n","  inflating: dataset/static/ID7/Gesture8.csv  \n","  inflating: dataset/static/ID7/Gesture9.csv  \n","   creating: dataset/static/ID8/\n","  inflating: dataset/static/ID8/Gesture1.csv  \n","  inflating: dataset/static/ID8/Gesture2.csv  \n","  inflating: dataset/static/ID8/Gesture3.csv  \n","  inflating: dataset/static/ID8/Gesture4.csv  \n","  inflating: dataset/static/ID8/Gesture5.csv  \n","  inflating: dataset/static/ID8/Gesture6.csv  \n","  inflating: dataset/static/ID8/Gesture7.csv  \n","  inflating: dataset/static/ID8/Gesture8.csv  \n","  inflating: dataset/static/ID8/Gesture9.csv  \n"]}]},{"cell_type":"code","source":["#change line 6 of /content/CSI-BERT/WiGesture/data_process_example/process1.py\n","#root=\"/content/CSI-BERT/dataset\"  #dataset folder"],"metadata":{"id":"XuQlgszr4ygD"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!python /content/CSI-BERT/WiGesture/data_process_example/process1.py"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"rjWcfQr73oPs","executionInfo":{"status":"ok","timestamp":1755448657350,"user_tz":-345,"elapsed":51974,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}},"outputId":"ba8dcb19-8eb5-4bdb-fd14-70dbbabe097d"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["static\n","ID6\n","ID2\n","ID7\n","ID1\n","ID8\n","ID3\n","ID5\n","ID4\n","dynamic\n","ID6\n","ID2\n","ID7\n","ID1\n","ID8\n","ID3\n","ID5\n","ID4\n"]}]},{"cell_type":"code","source":["%mkdir data"],"metadata":{"id":"OgnAq_ux8UU0","executionInfo":{"status":"ok","timestamp":1755449493223,"user_tz":-345,"elapsed":104,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}}},"execution_count":14,"outputs":[]},{"cell_type":"code","source":["#chnage below lines for /content/CSI-BERT/WiGesture/data_process_example/process2-split.py\n","# np.save(\"/content/CSI-BERT/data/magnitude.npy\", np.array(magnitudes))\n","# np.save(\"/content/CSI-BERT/data/phase.npy\", np.array(phases))\n","# np.save(\"/content/CSI-BERT/data/action.npy\", np.array(action_list))\n","# np.save(\"/content/CSI-BERT/data/people.npy\", np.array(people_list))\n","# np.save(\"/content/CSI-BERT/data/timestamp.npy\", np.array(timestamp))"],"metadata":{"id":"qjzB2YXC9VvM"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!python ./WiGesture/data_process_example/process2-split.py"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UjvjR-C85Tj1","executionInfo":{"status":"ok","timestamp":1755449789239,"user_tz":-345,"elapsed":11534,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}},"outputId":"088d5e0a-c774-4781-cd39-f32f15a04d67"},"execution_count":17,"outputs":[{"output_type":"stream","name":"stdout","text":["(3416,)\n","(3416,)\n","(3416, 100)\n","(3416, 100, 52)\n","(3416, 100, 52)\n"]}]},{"cell_type":"code","source":["#change line 2 to of pretrain.py to\n","# from transformers import BertConfig\n","# from torch.optim import AdamW\n"],"metadata":{"id":"dUS6Il6Q9pgR"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["!python pretrain.py --normal --time_embedding --adversarial --random_mask_percent"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"N0veX3d56xI8","executionInfo":{"status":"ok","timestamp":1755450664092,"user_tz":-345,"elapsed":862160,"user":{"displayName":"Santosh Upreti","userId":"15542637101614503540"}},"outputId":"0b2349b8-d337-4489-9582-ce2681a4ec9e"},"execution_count":18,"outputs":[{"output_type":"stream","name":"stdout","text":["2025-08-17 16:56:55.229373: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n","E0000 00:00:1755449815.263219    7800 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","E0000 00:00:1755449815.272459    7800 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n","W0000 00:00:1755449815.295101    7800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n","W0000 00:00:1755449815.295140    7800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n","W0000 00:00:1755449815.295146    7800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n","W0000 00:00:1755449815.295149    7800 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n","2025-08-17 16:56:55.299924: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","total parameters: 2113204\n","/usr/local/lib/python3.11/dist-packages/torch/_compile.py:32: UserWarning: optimizer contains a parameter group with duplicate parameters; in future, this will cause an error; see github.com/pytorch/pytorch/issues/40967 for more information\n","  return disable_fn(*args, **kwargs)\n","  0% 0/49 [00:00<?, ?it/s]/content/CSI-BERT/pretrain.py:127: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n","  rand_word = torch.tensor(csibert.mask(batch_size, std=torch.tensor([1]).to(device), avg=torch.tensor([0]).to(device))).to(device)\n","100% 49/49 [00:15<00:00,  3.16it/s]\n","Epoch 1 | Train Loss 11.005060, Train MAPE 0.178796, Train MSE 4.405277, \n","Discrimination | Truth(Mask) 0.607143, Truth(Total) 0.608099, False(Mask) 0.584503, False(Total) 0.580357\n","  0% 0/6 [00:00<?, ?it/s]/content/CSI-BERT/pretrain.py:293: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n","  rand_word = torch.tensor(csibert.mask(batch_size, std=torch.tensor([1]).to(device), avg=torch.tensor([0]).to(device))).to(device)\n","100% 6/6 [00:01<00:00,  5.05it/s]\n","Test Loss 9.428445, Test MAPE 0.181834, Test MSE 4.630987 \n","Discrimination | Truth(Mask) 0.976562, Truth(Total) 0.976562, False(Mask) 0.036458, False(Total) 0.036458\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.58it/s]\n","Epoch 2 | Train Loss 8.660842, Train MAPE 0.177431, Train MSE 4.362842, \n","Discrimination | Truth(Mask) 0.354273, Truth(Total) 0.368941, False(Mask) 0.624043, False(Total) 0.576531\n","100% 6/6 [00:01<00:00,  5.09it/s]\n","Test Loss 8.193297, Test MAPE 0.171643, Test MSE 4.097055 \n","Discrimination | Truth(Mask) 0.253551, Truth(Total) 0.271780, False(Mask) 0.735085, False(Total) 0.641809\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.64it/s]\n","Epoch 3 | Train Loss 8.032029, Train MAPE 0.171286, Train MSE 4.073263, \n","Discrimination | Truth(Mask) 0.541135, Truth(Total) 0.545281, False(Mask) 0.427296, False(Total) 0.410077\n","100% 6/6 [00:01<00:00,  4.85it/s]\n","Test Loss 8.096573, Test MAPE 0.170152, Test MSE 3.984424 \n","Discrimination | Truth(Mask) 0.100616, Truth(Total) 0.103456, False(Mask) 0.896544, False(Total) 0.893939\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 4 | Train Loss 7.920666, Train MAPE 0.170779, Train MSE 3.995608, \n","Discrimination | Truth(Mask) 0.443878, Truth(Total) 0.435268, False(Mask) 0.565689, False(Total) 0.577806\n","100% 6/6 [00:01<00:00,  4.51it/s]\n","Test Loss 7.922985, Test MAPE 0.167395, Test MSE 3.854574 \n","Discrimination | Truth(Mask) 0.500237, Truth(Total) 0.510417, False(Mask) 0.488873, False(Total) 0.468040\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.60it/s]\n","Epoch 5 | Train Loss 8.844633, Train MAPE 0.173734, Train MSE 4.126168, \n","Discrimination | Truth(Mask) 0.536033, Truth(Total) 0.536990, False(Mask) 0.465242, False(Total) 0.468431\n","100% 6/6 [00:01<00:00,  4.26it/s]\n","Test Loss 8.780215, Test MAPE 0.177216, Test MSE 4.406494 \n","Discrimination | Truth(Mask) 0.466146, Truth(Total) 0.468750, False(Mask) 0.482008, False(Total) 0.520597\n","MAPE Epoch 1, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.70it/s]\n","Epoch 6 | Train Loss 9.305726, Train MAPE 0.181580, Train MSE 4.369817, \n","Discrimination | Truth(Mask) 0.522003, Truth(Total) 0.514349, False(Mask) 0.477679, False(Total) 0.488839\n","100% 6/6 [00:01<00:00,  4.68it/s]\n","Test Loss 12.218942, Test MAPE 0.193882, Test MSE 4.789214 \n","Discrimination | Truth(Mask) 0.544034, Truth(Total) 0.528409, False(Mask) 0.497396, False(Total) 0.502367\n","MAPE Epoch 2, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 7 | Train Loss 11.906787, Train MAPE 0.178065, Train MSE 4.456233, \n","Discrimination | Truth(Mask) 0.453763, Truth(Total) 0.458227, False(Mask) 0.522959, False(Total) 0.536033\n","100% 6/6 [00:01<00:00,  5.04it/s]\n","Test Loss 11.380759, Test MAPE 0.171538, Test MSE 4.225751 \n","Discrimination | Truth(Mask) 0.513021, Truth(Total) 0.549006, False(Mask) 0.502367, False(Total) 0.515388\n","MAPE Epoch 3, MSE Epoch 3, Loss Epcoh 3\n","100% 49/49 [00:13<00:00,  3.69it/s]\n","Epoch 8 | Train Loss 11.663557, Train MAPE 0.175609, Train MSE 4.138624, \n","Discrimination | Truth(Mask) 0.455676, Truth(Total) 0.476084, False(Mask) 0.521365, False(Total) 0.516901\n","100% 6/6 [00:01<00:00,  5.16it/s]\n","Test Loss 11.409364, Test MAPE 0.178252, Test MSE 4.192597 \n","Discrimination | Truth(Mask) 0.589962, Truth(Total) 0.629498, False(Mask) 0.365057, False(Total) 0.427320\n","MAPE Epoch 4, MSE Epoch 4, Loss Epcoh 4\n","100% 49/49 [00:13<00:00,  3.69it/s]\n","Epoch 9 | Train Loss 12.437167, Train MAPE 0.174810, Train MSE 4.104185, \n","Discrimination | Truth(Mask) 0.841837, Truth(Total) 0.855867, False(Mask) 0.132972, False(Total) 0.135204\n","100% 6/6 [00:01<00:00,  4.13it/s]\n","Test Loss 13.065337, Test MAPE 0.185100, Test MSE 4.644312 \n","Discrimination | Truth(Mask) 0.784328, Truth(Total) 0.902225, False(Mask) 0.160748, False(Total) 0.109375\n","MAPE Epoch 5, MSE Epoch 5, Loss Epcoh 5\n","100% 49/49 [00:13<00:00,  3.60it/s]\n","Epoch 10 | Train Loss 13.812995, Train MAPE 0.196194, Train MSE 5.625070, \n","Discrimination | Truth(Mask) 0.949298, Truth(Total) 0.959821, False(Mask) 0.037946, False(Total) 0.052615\n","100% 6/6 [00:01<00:00,  4.80it/s]\n","Test Loss 15.220143, Test MAPE 0.207293, Test MSE 6.319373 \n","Discrimination | Truth(Mask) 0.937737, Truth(Total) 0.937500, False(Mask) 0.090909, False(Total) 0.121922\n","MAPE Epoch 6, MSE Epoch 6, Loss Epcoh 6\n","100% 49/49 [00:13<00:00,  3.70it/s]\n","Epoch 11 | Train Loss 13.693644, Train MAPE 0.194502, Train MSE 5.555889, \n","Discrimination | Truth(Mask) 0.880740, Truth(Total) 0.863839, False(Mask) 0.133291, False(Total) 0.122449\n","100% 6/6 [00:01<00:00,  4.90it/s]\n","Test Loss 13.460375, Test MAPE 0.188676, Test MSE 5.166346 \n","Discrimination | Truth(Mask) 0.818655, Truth(Total) 0.774621, False(Mask) 0.036222, False(Total) 0.080019\n","MAPE Epoch 7, MSE Epoch 7, Loss Epcoh 7\n","100% 49/49 [00:13<00:00,  3.67it/s]\n","Epoch 12 | Train Loss 14.555648, Train MAPE 0.180816, Train MSE 4.681561, \n","Discrimination | Truth(Mask) 0.806441, Truth(Total) 0.819515, False(Mask) 0.179847, False(Total) 0.196429\n","100% 6/6 [00:01<00:00,  4.93it/s]\n","Test Loss 13.603325, Test MAPE 0.178297, Test MSE 4.421611 \n","Discrimination | Truth(Mask) 0.826705, Truth(Total) 0.862216, False(Mask) 0.020833, False(Total) 0.013021\n","MAPE Epoch 8, MSE Epoch 8, Loss Epcoh 8\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 13 | Train Loss 13.561468, Train MAPE 0.179924, Train MSE 4.500349, \n","Discrimination | Truth(Mask) 0.879145, Truth(Total) 0.896046, False(Mask) 0.118622, False(Total) 0.106505\n","100% 6/6 [00:01<00:00,  4.97it/s]\n","Test Loss 13.844969, Test MAPE 0.181906, Test MSE 4.407341 \n","Discrimination | Truth(Mask) 0.911932, Truth(Total) 0.912169, False(Mask) 0.054214, False(Total) 0.072680\n","MAPE Epoch 9, MSE Epoch 9, Loss Epcoh 9\n","100% 49/49 [00:13<00:00,  3.72it/s]\n","Epoch 14 | Train Loss 13.067368, Train MAPE 0.179909, Train MSE 4.378164, \n","Discrimination | Truth(Mask) 0.984694, Truth(Total) 0.980548, False(Mask) 0.019133, False(Total) 0.017857\n","100% 6/6 [00:01<00:00,  3.59it/s]\n","Test Loss 13.244925, Test MAPE 0.178720, Test MSE 4.192321 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.005208, False(Total) 0.005208\n","MAPE Epoch 10, MSE Epoch 10, Loss Epcoh 10\n","100% 49/49 [00:13<00:00,  3.63it/s]\n","Epoch 15 | Train Loss 12.849050, Train MAPE 0.181821, Train MSE 4.497544, \n","Discrimination | Truth(Mask) 0.239796, Truth(Total) 0.239158, False(Mask) 0.754783, False(Total) 0.757334\n","100% 6/6 [00:01<00:00,  4.86it/s]\n","Test Loss 12.614324, Test MAPE 0.182763, Test MSE 4.492870 \n","Discrimination | Truth(Mask) 0.026042, Truth(Total) 0.018229, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 11, MSE Epoch 11, Loss Epcoh 11\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 16 | Train Loss 11.846645, Train MAPE 0.186327, Train MSE 4.864153, \n","Discrimination | Truth(Mask) 0.000957, Truth(Total) 0.000319, False(Mask) 0.996811, False(Total) 0.994898\n","100% 6/6 [00:01<00:00,  4.76it/s]\n","Test Loss 11.312641, Test MAPE 0.185418, Test MSE 4.823002 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 0.997396\n","MAPE Epoch 12, MSE Epoch 12, Loss Epcoh 12\n","100% 49/49 [00:13<00:00,  3.67it/s]\n","Epoch 17 | Train Loss 9.929071, Train MAPE 0.180918, Train MSE 4.585052, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.74it/s]\n","Test Loss 8.333806, Test MAPE 0.171634, Test MSE 3.950632 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 13, MSE Epoch 13, Loss Epcoh 13\n","100% 49/49 [00:13<00:00,  3.67it/s]\n","Epoch 18 | Train Loss 7.765665, Train MAPE 0.167793, Train MSE 3.850450, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.79it/s]\n","Test Loss 7.510207, Test MAPE 0.164062, Test MSE 3.664626 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.59it/s]\n","Epoch 19 | Train Loss 7.284065, Train MAPE 0.163330, Train MSE 3.699514, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.00it/s]\n","Test Loss 7.321234, Test MAPE 0.164348, Test MSE 3.689699 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 1, MSE Epoch 1, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 20 | Train Loss 7.061384, Train MAPE 0.161799, Train MSE 3.626810, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.95it/s]\n","Test Loss 7.152836, Test MAPE 0.164440, Test MSE 3.624027 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 2, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 21 | Train Loss 6.934899, Train MAPE 0.161410, Train MSE 3.602281, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  5.05it/s]\n","Test Loss 7.109481, Test MAPE 0.160021, Test MSE 3.506414 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.74it/s]\n","Epoch 22 | Train Loss 6.882643, Train MAPE 0.161348, Train MSE 3.597463, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  5.08it/s]\n","Test Loss 7.062396, Test MAPE 0.161910, Test MSE 3.640150 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 1, MSE Epoch 1, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 23 | Train Loss 6.858944, Train MAPE 0.161460, Train MSE 3.596833, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.03it/s]\n","Test Loss 7.095455, Test MAPE 0.161964, Test MSE 3.565626 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 2, MSE Epoch 2, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.52it/s]\n","Epoch 24 | Train Loss 6.825081, Train MAPE 0.160331, Train MSE 3.595328, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.76it/s]\n","Test Loss 7.018500, Test MAPE 0.162186, Test MSE 3.662471 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 3, MSE Epoch 3, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.62it/s]\n","Epoch 25 | Train Loss 6.806957, Train MAPE 0.160974, Train MSE 3.605988, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.86it/s]\n","Test Loss 6.925331, Test MAPE 0.162291, Test MSE 3.597840 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 4, MSE Epoch 4, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.66it/s]\n","Epoch 26 | Train Loss 6.860983, Train MAPE 0.162719, Train MSE 3.656584, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.74it/s]\n","Test Loss 6.879826, Test MAPE 0.161834, Test MSE 3.567160 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 5, MSE Epoch 5, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 27 | Train Loss 6.577833, Train MAPE 0.158795, Train MSE 3.513165, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  3.06it/s]\n","Test Loss 6.781172, Test MAPE 0.159378, Test MSE 3.535473 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 0, MSE Epoch 6, Loss Epcoh 0\n","100% 49/49 [00:14<00:00,  3.29it/s]\n","Epoch 28 | Train Loss 6.730773, Train MAPE 0.159632, Train MSE 3.595032, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  5.00it/s]\n","Test Loss 6.765117, Test MAPE 0.157102, Test MSE 3.492762 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.67it/s]\n","Epoch 29 | Train Loss 6.608948, Train MAPE 0.158842, Train MSE 3.541919, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.83it/s]\n","Test Loss 6.785231, Test MAPE 0.161396, Test MSE 3.560785 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 1, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.64it/s]\n","Epoch 30 | Train Loss 6.745043, Train MAPE 0.160764, Train MSE 3.623251, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.87it/s]\n","Test Loss 6.716691, Test MAPE 0.160551, Test MSE 3.606746 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 2, MSE Epoch 2, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 31 | Train Loss 6.620182, Train MAPE 0.159249, Train MSE 3.568480, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.94it/s]\n","Test Loss 6.617472, Test MAPE 0.158070, Test MSE 3.461539 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 3, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.52it/s]\n","Epoch 32 | Train Loss 6.623040, Train MAPE 0.159128, Train MSE 3.561370, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.09it/s]\n","Test Loss 6.693816, Test MAPE 0.159216, Test MSE 3.560659 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 4, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.66it/s]\n","Epoch 33 | Train Loss 6.541475, Train MAPE 0.158347, Train MSE 3.536916, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.84it/s]\n","Test Loss 6.738721, Test MAPE 0.159421, Test MSE 3.470834 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 5, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.64it/s]\n","Epoch 34 | Train Loss 6.544289, Train MAPE 0.158784, Train MSE 3.524514, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  5.01it/s]\n","Test Loss 6.753030, Test MAPE 0.159769, Test MSE 3.516670 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 6, MSE Epoch 3, Loss Epcoh 3\n","100% 49/49 [00:13<00:00,  3.67it/s]\n","Epoch 35 | Train Loss 6.542264, Train MAPE 0.159373, Train MSE 3.549674, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.88it/s]\n","Test Loss 6.687797, Test MAPE 0.157645, Test MSE 3.481096 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 7, MSE Epoch 4, Loss Epcoh 4\n","100% 49/49 [00:13<00:00,  3.69it/s]\n","Epoch 36 | Train Loss 6.486976, Train MAPE 0.158153, Train MSE 3.508207, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.23it/s]\n","Test Loss 6.795205, Test MAPE 0.159539, Test MSE 3.605113 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 8, MSE Epoch 5, Loss Epcoh 5\n","100% 49/49 [00:13<00:00,  3.60it/s]\n","Epoch 37 | Train Loss 6.683177, Train MAPE 0.161641, Train MSE 3.658884, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  4.94it/s]\n","Test Loss 6.554651, Test MAPE 0.159398, Test MSE 3.459232 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 9, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 38 | Train Loss 6.557800, Train MAPE 0.159639, Train MSE 3.573117, \n","Discrimination | Truth(Mask) 0.938776, Truth(Total) 0.938776, False(Mask) 0.061224, False(Total) 0.061224\n","100% 6/6 [00:01<00:00,  4.94it/s]\n","Test Loss 6.704154, Test MAPE 0.161851, Test MSE 3.529773 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 10, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 39 | Train Loss 6.467421, Train MAPE 0.158556, Train MSE 3.515153, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.90it/s]\n","Test Loss 6.584444, Test MAPE 0.157308, Test MSE 3.479542 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 11, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.69it/s]\n","Epoch 40 | Train Loss 6.442259, Train MAPE 0.157537, Train MSE 3.483034, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.79it/s]\n","Test Loss 6.520898, Test MAPE 0.156342, Test MSE 3.439616 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 0, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 41 | Train Loss 6.448114, Train MAPE 0.158021, Train MSE 3.502719, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  3.64it/s]\n","Test Loss 6.598621, Test MAPE 0.159607, Test MSE 3.536551 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 1, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.63it/s]\n","Epoch 42 | Train Loss 6.418024, Train MAPE 0.157071, Train MSE 3.484231, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.78it/s]\n","Test Loss 6.730721, Test MAPE 0.160360, Test MSE 3.524068 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 2, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.68it/s]\n","Epoch 43 | Train Loss 6.408496, Train MAPE 0.157657, Train MSE 3.491925, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  5.14it/s]\n","Test Loss 6.482591, Test MAPE 0.158476, Test MSE 3.446784 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 3, MSE Epoch 3, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.66it/s]\n","Epoch 44 | Train Loss 6.412594, Train MAPE 0.157160, Train MSE 3.487565, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.92it/s]\n","Test Loss 6.550522, Test MAPE 0.157773, Test MSE 3.442513 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 4, MSE Epoch 4, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.61it/s]\n","Epoch 45 | Train Loss 6.645392, Train MAPE 0.161415, Train MSE 3.637845, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.91it/s]\n","Test Loss 6.640719, Test MAPE 0.158924, Test MSE 3.479298 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 5, MSE Epoch 5, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.52it/s]\n","Epoch 46 | Train Loss 6.412084, Train MAPE 0.157783, Train MSE 3.494703, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.20it/s]\n","Test Loss 6.686948, Test MAPE 0.160034, Test MSE 3.494103 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 6, MSE Epoch 6, Loss Epcoh 3\n","100% 49/49 [00:13<00:00,  3.59it/s]\n","Epoch 47 | Train Loss 6.329402, Train MAPE 0.156761, Train MSE 3.457702, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.90it/s]\n","Test Loss 6.471241, Test MAPE 0.156953, Test MSE 3.409154 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 7, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.63it/s]\n","Epoch 48 | Train Loss 6.304076, Train MAPE 0.155906, Train MSE 3.435979, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.68it/s]\n","Test Loss 6.429593, Test MAPE 0.156375, Test MSE 3.399698 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 8, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.57it/s]\n","Epoch 49 | Train Loss 6.488764, Train MAPE 0.159115, Train MSE 3.546714, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  4.94it/s]\n","Test Loss 6.536909, Test MAPE 0.159426, Test MSE 3.507443 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 9, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.54it/s]\n","Epoch 50 | Train Loss 6.331108, Train MAPE 0.157138, Train MSE 3.469665, \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","100% 6/6 [00:01<00:00,  3.67it/s]\n","Test Loss 6.513781, Test MAPE 0.158737, Test MSE 3.478470 \n","Discrimination | Truth(Mask) 0.000000, Truth(Total) 0.000000, False(Mask) 1.000000, False(Total) 1.000000\n","MAPE Epoch 10, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:14<00:00,  3.46it/s]\n","Epoch 51 | Train Loss 6.423665, Train MAPE 0.158423, Train MSE 3.532968, \n","Discrimination | Truth(Mask) 0.959184, Truth(Total) 0.959184, False(Mask) 0.040816, False(Total) 0.040816\n","100% 6/6 [00:01<00:00,  4.57it/s]\n","Test Loss 6.601719, Test MAPE 0.159114, Test MSE 3.511360 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 11, MSE Epoch 3, Loss Epcoh 3\n","100% 49/49 [00:14<00:00,  3.49it/s]\n","Epoch 52 | Train Loss 6.397731, Train MAPE 0.158693, Train MSE 3.512903, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000638, False(Total) 0.000000\n","100% 6/6 [00:01<00:00,  5.00it/s]\n","Test Loss 6.355390, Test MAPE 0.157992, Test MSE 3.360672 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 12, MSE Epoch 0, Loss Epcoh 0\n","100% 49/49 [00:13<00:00,  3.64it/s]\n","Epoch 53 | Train Loss 6.320285, Train MAPE 0.156646, Train MSE 3.470306, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.001276\n","100% 6/6 [00:01<00:00,  4.96it/s]\n","Test Loss 6.539511, Test MAPE 0.158734, Test MSE 3.473286 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 13, MSE Epoch 1, Loss Epcoh 1\n","100% 49/49 [00:13<00:00,  3.58it/s]\n","Epoch 54 | Train Loss 6.263258, Train MAPE 0.155945, Train MSE 3.421003, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.001276, False(Total) 0.000638\n","100% 6/6 [00:01<00:00,  3.84it/s]\n","Test Loss 6.531748, Test MAPE 0.159046, Test MSE 3.478808 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.012784, False(Total) 0.002604\n","MAPE Epoch 14, MSE Epoch 2, Loss Epcoh 2\n","100% 49/49 [00:13<00:00,  3.64it/s]\n","Epoch 55 | Train Loss 6.371356, Train MAPE 0.157416, Train MSE 3.492224, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.001276, False(Total) 0.001276\n","100% 6/6 [00:01<00:00,  4.92it/s]\n","Test Loss 6.421872, Test MAPE 0.158548, Test MSE 3.442433 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.000000, False(Total) 0.000000\n","MAPE Epoch 15, MSE Epoch 3, Loss Epcoh 3\n","100% 49/49 [00:13<00:00,  3.65it/s]\n","Epoch 56 | Train Loss 6.441554, Train MAPE 0.158731, Train MSE 3.516116, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.003189, False(Total) 0.002551\n","100% 6/6 [00:01<00:00,  5.02it/s]\n","Test Loss 6.473433, Test MAPE 0.159916, Test MSE 3.522178 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.005208, False(Total) 0.000000\n","MAPE Epoch 16, MSE Epoch 4, Loss Epcoh 4\n","100% 49/49 [00:13<00:00,  3.59it/s]\n","Epoch 57 | Train Loss 6.286231, Train MAPE 0.156370, Train MSE 3.439947, \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.001276, False(Total) 0.002551\n","100% 6/6 [00:01<00:00,  4.86it/s]\n","Test Loss 6.407263, Test MAPE 0.156864, Test MSE 3.354829 \n","Discrimination | Truth(Mask) 1.000000, Truth(Total) 1.000000, False(Mask) 0.005208, False(Total) 0.007576\n","MAPE Epoch 17, MSE Epoch 0, Loss Epcoh 5\n"," 22% 11/49 [00:03<00:12,  3.17it/s]\n","object address  : 0x143b991fdba0\n","object refcount : 2\n","object type     : 0x9d7580\n","object type name: KeyboardInterrupt\n","object repr     : KeyboardInterrupt()\n","lost sys.stderr\n"]}]}]}