From 09b4f07c27c05b43eef008f4da2fea36c5523234 Mon Sep 17 00:00:00 2001
From: liyong <liyong@honeycombtech.com>
Date: Tue, 21 Oct 2025 20:52:26 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E9=A2=84=E6=B5=8B=E8=84=9A?=
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Content-Type: text/plain; charset=UTF-8
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---
 .idea/encodings.xml                           |   6 +
 .../Data_Handle/forecast.json                 |   1 +
 .../FC_ML_Baseline_Test/Data_Handle/model.bin | Bin 0 -> 1804 bytes
 .../FC_ML_Baseline_Test/Data_Handle/model.pth | Bin 0 -> 3929 bytes
 .../Data_Handle/training.log                  | 272 ++++++++++++++++++
 5 files changed, 279 insertions(+)
 create mode 100644 .idea/encodings.xml
 create mode 100644 FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/forecast.json
 create mode 100644 FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/model.bin
 create mode 100644 FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/model.pth
 create mode 100644 FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/training.log

diff --git a/.idea/encodings.xml b/.idea/encodings.xml
new file mode 100644
index 0000000..c96602a
--- /dev/null
+++ b/.idea/encodings.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Encoding">
+    <file url="file://$PROJECT_DIR$/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/training.log" charset="UTF-8" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/forecast.json b/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/forecast.json
new file mode 100644
index 0000000..9f64f01
--- /dev/null
+++ b/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/forecast.json
@@ -0,0 +1 @@
+{"label1": -33.618247985839844, "label2": 0.769456148147583, "label3": 13.0462007522583, "label4": 4.485231399536133, "label5": -30.332216262817383, "label6": -30.264156341552734, "label7": 2.244447708129883, "label8": -15.965958595275879}
\ No newline at end of file
diff --git a/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/model.bin b/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/model.bin
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diff --git a/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/training.log b/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/training.log
new file mode 100644
index 0000000..4ce5177
--- /dev/null
+++ b/FC_ML_Baseline/FC_ML_Baseline_Test/Data_Handle/training.log
@@ -0,0 +1,272 @@
+Epoch 0 | Train Loss: 0.3691 | Test Loss: 0.3136 | 损失比: 1.18:1
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+Epoch 44 | Train Loss: 0.0714 | Test Loss: 0.1015 | 损失比: 0.70:1
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+Epoch 715 | Train Loss: 0.0617 | Test Loss: 0.1282 | 损失比: 0.48:1
+Epoch 726 | Train Loss: 0.0616 | Test Loss: 0.1282 | 损失比: 0.48:1
+Epoch 737 | Train Loss: 0.0616 | Test Loss: 0.1286 | 损失比: 0.48:1
+Epoch 748 | Train Loss: 0.0616 | Test Loss: 0.1290 | 损失比: 0.48:1
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+Epoch 781 | Train Loss: 0.0616 | Test Loss: 0.1298 | 损失比: 0.47:1
+Epoch 792 | Train Loss: 0.0616 | Test Loss: 0.1298 | 损失比: 0.47:1
+Epoch 803 | Train Loss: 0.0616 | Test Loss: 0.1298 | 损失比: 0.47:1
+Epoch 814 | Train Loss: 0.0616 | Test Loss: 0.1301 | 损失比: 0.47:1
+Epoch 825 | Train Loss: 0.0616 | Test Loss: 0.1302 | 损失比: 0.47:1
+Epoch 836 | Train Loss: 0.0616 | Test Loss: 0.1308 | 损失比: 0.47:1
+Epoch 847 | Train Loss: 0.0615 | Test Loss: 0.1308 | 损失比: 0.47:1
+Epoch 858 | Train Loss: 0.0615 | Test Loss: 0.1309 | 损失比: 0.47:1
+Epoch 869 | Train Loss: 0.0615 | Test Loss: 0.1311 | 损失比: 0.47:1
+Epoch 880 | Train Loss: 0.0615 | Test Loss: 0.1311 | 损失比: 0.47:1
+Epoch 891 | Train Loss: 0.0615 | Test Loss: 0.1317 | 损失比: 0.47:1
+Epoch 902 | Train Loss: 0.0615 | Test Loss: 0.1320 | 损失比: 0.47:1
+Epoch 913 | Train Loss: 0.0615 | Test Loss: 0.1318 | 损失比: 0.47:1
+Epoch 924 | Train Loss: 0.0615 | Test Loss: 0.1321 | 损失比: 0.47:1
+Epoch 935 | Train Loss: 0.0615 | Test Loss: 0.1322 | 损失比: 0.47:1
+Epoch 946 | Train Loss: 0.0615 | Test Loss: 0.1324 | 损失比: 0.46:1
+Epoch 957 | Train Loss: 0.0615 | Test Loss: 0.1329 | 损失比: 0.46:1
+Epoch 968 | Train Loss: 0.0615 | Test Loss: 0.1329 | 损失比: 0.46:1
+Epoch 979 | Train Loss: 0.0614 | Test Loss: 0.1331 | 损失比: 0.46:1
+Epoch 990 | Train Loss: 0.0614 | Test Loss: 0.1334 | 损失比: 0.46:1
+Epoch 0 | Train Loss: 0.3581 | Test Loss: 0.2541 | 损失比: 1.41:1
+Epoch 11 | Train Loss: 0.1363 | Test Loss: 0.1514 | 损失比: 0.90:1
+Epoch 22 | Train Loss: 0.1082 | Test Loss: 0.1258 | 损失比: 0.86:1
+Epoch 33 | Train Loss: 0.0906 | Test Loss: 0.1128 | 损失比: 0.80:1
+Epoch 44 | Train Loss: 0.0800 | Test Loss: 0.1113 | 损失比: 0.72:1
+Epoch 55 | Train Loss: 0.0733 | Test Loss: 0.1154 | 损失比: 0.64:1
+Epoch 66 | Train Loss: 0.0691 | Test Loss: 0.1190 | 损失比: 0.58:1
+Epoch 77 | Train Loss: 0.0663 | Test Loss: 0.1217 | 损失比: 0.54:1
+Epoch 88 | Train Loss: 0.0648 | Test Loss: 0.1244 | 损失比: 0.52:1
+Epoch 99 | Train Loss: 0.0640 | Test Loss: 0.1265 | 损失比: 0.51:1
+Epoch 110 | Train Loss: 0.0636 | Test Loss: 0.1284 | 损失比: 0.49:1
+Epoch 121 | Train Loss: 0.0633 | Test Loss: 0.1298 | 损失比: 0.49:1
+Epoch 132 | Train Loss: 0.0631 | Test Loss: 0.1306 | 损失比: 0.48:1
+Epoch 143 | Train Loss: 0.0630 | Test Loss: 0.1310 | 损失比: 0.48:1
+Epoch 154 | Train Loss: 0.0629 | Test Loss: 0.1315 | 损失比: 0.48:1
+Epoch 165 | Train Loss: 0.0628 | Test Loss: 0.1318 | 损失比: 0.48:1
+Epoch 176 | Train Loss: 0.0627 | Test Loss: 0.1322 | 损失比: 0.47:1
+Epoch 187 | Train Loss: 0.0626 | Test Loss: 0.1324 | 损失比: 0.47:1
+Epoch 198 | Train Loss: 0.0626 | Test Loss: 0.1329 | 损失比: 0.47:1
+Epoch 209 | Train Loss: 0.0625 | Test Loss: 0.1328 | 损失比: 0.47:1
+Epoch 220 | Train Loss: 0.0625 | Test Loss: 0.1331 | 损失比: 0.47:1
+Epoch 231 | Train Loss: 0.0624 | Test Loss: 0.1332 | 损失比: 0.47:1
+Epoch 242 | Train Loss: 0.0624 | Test Loss: 0.1333 | 损失比: 0.47:1
+Epoch 253 | Train Loss: 0.0623 | Test Loss: 0.1333 | 损失比: 0.47:1
+Epoch 264 | Train Loss: 0.0623 | Test Loss: 0.1335 | 损失比: 0.47:1
+Epoch 275 | Train Loss: 0.0623 | Test Loss: 0.1338 | 损失比: 0.47:1
+Epoch 286 | Train Loss: 0.0622 | Test Loss: 0.1338 | 损失比: 0.47:1
+Epoch 297 | Train Loss: 0.0622 | Test Loss: 0.1338 | 损失比: 0.46:1
+Epoch 308 | Train Loss: 0.0622 | Test Loss: 0.1340 | 损失比: 0.46:1
+Epoch 319 | Train Loss: 0.0621 | Test Loss: 0.1341 | 损失比: 0.46:1
+Epoch 330 | Train Loss: 0.0621 | Test Loss: 0.1344 | 损失比: 0.46:1
+Epoch 341 | Train Loss: 0.0621 | Test Loss: 0.1345 | 损失比: 0.46:1
+Epoch 352 | Train Loss: 0.0621 | Test Loss: 0.1345 | 损失比: 0.46:1
+Epoch 363 | Train Loss: 0.0620 | Test Loss: 0.1344 | 损失比: 0.46:1
+Epoch 374 | Train Loss: 0.0620 | Test Loss: 0.1346 | 损失比: 0.46:1
+Epoch 385 | Train Loss: 0.0620 | Test Loss: 0.1345 | 损失比: 0.46:1
+Epoch 396 | Train Loss: 0.0620 | Test Loss: 0.1347 | 损失比: 0.46:1
+Epoch 407 | Train Loss: 0.0619 | Test Loss: 0.1346 | 损失比: 0.46:1
+Epoch 418 | Train Loss: 0.0619 | Test Loss: 0.1347 | 损失比: 0.46:1
+Epoch 429 | Train Loss: 0.0619 | Test Loss: 0.1350 | 损失比: 0.46:1
+Epoch 440 | Train Loss: 0.0619 | Test Loss: 0.1345 | 损失比: 0.46:1
+Epoch 451 | Train Loss: 0.0619 | Test Loss: 0.1348 | 损失比: 0.46:1
+Epoch 462 | Train Loss: 0.0618 | Test Loss: 0.1349 | 损失比: 0.46:1
+Epoch 473 | Train Loss: 0.0618 | Test Loss: 0.1351 | 损失比: 0.46:1
+Epoch 484 | Train Loss: 0.0618 | Test Loss: 0.1351 | 损失比: 0.46:1
+Epoch 495 | Train Loss: 0.0618 | Test Loss: 0.1354 | 损失比: 0.46:1
+Epoch 506 | Train Loss: 0.0618 | Test Loss: 0.1353 | 损失比: 0.46:1
+Epoch 517 | Train Loss: 0.0618 | Test Loss: 0.1353 | 损失比: 0.46:1
+Epoch 528 | Train Loss: 0.0617 | Test Loss: 0.1356 | 损失比: 0.46:1
+Epoch 539 | Train Loss: 0.0617 | Test Loss: 0.1357 | 损失比: 0.45:1
+Epoch 550 | Train Loss: 0.0617 | Test Loss: 0.1356 | 损失比: 0.46:1
+Epoch 561 | Train Loss: 0.0617 | Test Loss: 0.1356 | 损失比: 0.45:1
+Epoch 572 | Train Loss: 0.0617 | Test Loss: 0.1358 | 损失比: 0.45:1
+Epoch 583 | Train Loss: 0.0617 | Test Loss: 0.1355 | 损失比: 0.45:1
+Epoch 594 | Train Loss: 0.0616 | Test Loss: 0.1358 | 损失比: 0.45:1
+Epoch 605 | Train Loss: 0.0616 | Test Loss: 0.1361 | 损失比: 0.45:1
+Epoch 616 | Train Loss: 0.0616 | Test Loss: 0.1363 | 损失比: 0.45:1
+Epoch 627 | Train Loss: 0.0616 | Test Loss: 0.1361 | 损失比: 0.45:1
+Epoch 638 | Train Loss: 0.0616 | Test Loss: 0.1366 | 损失比: 0.45:1
+Epoch 649 | Train Loss: 0.0616 | Test Loss: 0.1366 | 损失比: 0.45:1
+Epoch 660 | Train Loss: 0.0616 | Test Loss: 0.1365 | 损失比: 0.45:1
+Epoch 671 | Train Loss: 0.0615 | Test Loss: 0.1367 | 损失比: 0.45:1
+Epoch 682 | Train Loss: 0.0615 | Test Loss: 0.1367 | 损失比: 0.45:1
+Epoch 693 | Train Loss: 0.0615 | Test Loss: 0.1368 | 损失比: 0.45:1
+Epoch 704 | Train Loss: 0.0615 | Test Loss: 0.1372 | 损失比: 0.45:1
+Epoch 715 | Train Loss: 0.0615 | Test Loss: 0.1371 | 损失比: 0.45:1
+Epoch 726 | Train Loss: 0.0615 | Test Loss: 0.1371 | 损失比: 0.45:1
+Epoch 737 | Train Loss: 0.0615 | Test Loss: 0.1371 | 损失比: 0.45:1
+Epoch 748 | Train Loss: 0.0615 | Test Loss: 0.1372 | 损失比: 0.45:1
+Epoch 759 | Train Loss: 0.0615 | Test Loss: 0.1376 | 损失比: 0.45:1
+Epoch 770 | Train Loss: 0.0614 | Test Loss: 0.1373 | 损失比: 0.45:1
+Epoch 781 | Train Loss: 0.0614 | Test Loss: 0.1376 | 损失比: 0.45:1
+Epoch 792 | Train Loss: 0.0614 | Test Loss: 0.1377 | 损失比: 0.45:1
+Epoch 803 | Train Loss: 0.0614 | Test Loss: 0.1378 | 损失比: 0.45:1
+Epoch 814 | Train Loss: 0.0614 | Test Loss: 0.1378 | 损失比: 0.45:1
+Epoch 825 | Train Loss: 0.0614 | Test Loss: 0.1384 | 损失比: 0.44:1
+Epoch 836 | Train Loss: 0.0614 | Test Loss: 0.1383 | 损失比: 0.44:1
+Epoch 847 | Train Loss: 0.0614 | Test Loss: 0.1382 | 损失比: 0.44:1
+Epoch 858 | Train Loss: 0.0614 | Test Loss: 0.1384 | 损失比: 0.44:1
+Epoch 869 | Train Loss: 0.0614 | Test Loss: 0.1385 | 损失比: 0.44:1
+Epoch 880 | Train Loss: 0.0613 | Test Loss: 0.1385 | 损失比: 0.44:1
+Epoch 891 | Train Loss: 0.0613 | Test Loss: 0.1384 | 损失比: 0.44:1
+Epoch 902 | Train Loss: 0.0613 | Test Loss: 0.1389 | 损失比: 0.44:1
+Epoch 913 | Train Loss: 0.0613 | Test Loss: 0.1388 | 损失比: 0.44:1
+Epoch 924 | Train Loss: 0.0613 | Test Loss: 0.1391 | 损失比: 0.44:1
+Epoch 935 | Train Loss: 0.0613 | Test Loss: 0.1392 | 损失比: 0.44:1
+Epoch 946 | Train Loss: 0.0613 | Test Loss: 0.1393 | 损失比: 0.44:1
+Epoch 957 | Train Loss: 0.0613 | Test Loss: 0.1390 | 损失比: 0.44:1
+Epoch 968 | Train Loss: 0.0613 | Test Loss: 0.1391 | 损失比: 0.44:1
+Epoch 979 | Train Loss: 0.0613 | Test Loss: 0.1395 | 损失比: 0.44:1
+Epoch 990 | Train Loss: 0.0613 | Test Loss: 0.1396 | 损失比: 0.44:1
+Epoch 0 | Train Loss: 0.3120 | Test Loss: 0.2047 | 损失比: 1.52:1
+Epoch 10 | Train Loss: 0.1209 | Test Loss: 0.1715 | 损失比: 0.71:1
+Epoch 20 | Train Loss: 0.0993 | Test Loss: 0.1597 | 损失比: 0.62:1
+Epoch 30 | Train Loss: 0.0858 | Test Loss: 0.1510 | 损失比: 0.57:1
+Epoch 40 | Train Loss: 0.0773 | Test Loss: 0.1464 | 损失比: 0.53:1
+Epoch 50 | Train Loss: 0.0723 | Test Loss: 0.1442 | 损失比: 0.50:1
+Epoch 60 | Train Loss: 0.0691 | Test Loss: 0.1434 | 损失比: 0.48:1
+Epoch 70 | Train Loss: 0.0672 | Test Loss: 0.1422 | 损失比: 0.47:1
+Epoch 80 | Train Loss: 0.0658 | Test Loss: 0.1421 | 损失比: 0.46:1
+Epoch 90 | Train Loss: 0.0649 | Test Loss: 0.1416 | 损失比: 0.46:1
+Epoch 100 | Train Loss: 0.0643 | Test Loss: 0.1409 | 损失比: 0.46:1
+Epoch 110 | Train Loss: 0.0639 | Test Loss: 0.1409 | 损失比: 0.45:1
+Epoch 120 | Train Loss: 0.0637 | Test Loss: 0.1400 | 损失比: 0.45:1
+Epoch 130 | Train Loss: 0.0635 | Test Loss: 0.1394 | 损失比: 0.46:1
+Epoch 140 | Train Loss: 0.0633 | Test Loss: 0.1388 | 损失比: 0.46:1
+Epoch 150 | Train Loss: 0.0632 | Test Loss: 0.1386 | 损失比: 0.46:1
+Epoch 160 | Train Loss: 0.0630 | Test Loss: 0.1380 | 损失比: 0.46:1
+Epoch 170 | Train Loss: 0.0629 | Test Loss: 0.1374 | 损失比: 0.46:1
+Epoch 180 | Train Loss: 0.0629 | Test Loss: 0.1368 | 损失比: 0.46:1
+Epoch 190 | Train Loss: 0.0628 | Test Loss: 0.1364 | 损失比: 0.46:1
+Epoch 200 | Train Loss: 0.0627 | Test Loss: 0.1359 | 损失比: 0.46:1
+Epoch 210 | Train Loss: 0.0627 | Test Loss: 0.1355 | 损失比: 0.46:1
+Epoch 220 | Train Loss: 0.0626 | Test Loss: 0.1353 | 损失比: 0.46:1
+Epoch 230 | Train Loss: 0.0625 | Test Loss: 0.1346 | 损失比: 0.46:1
+Epoch 240 | Train Loss: 0.0625 | Test Loss: 0.1341 | 损失比: 0.47:1
+Epoch 250 | Train Loss: 0.0624 | Test Loss: 0.1338 | 损失比: 0.47:1
+Epoch 260 | Train Loss: 0.0624 | Test Loss: 0.1333 | 损失比: 0.47:1
+Epoch 270 | Train Loss: 0.0624 | Test Loss: 0.1331 | 损失比: 0.47:1
+Epoch 280 | Train Loss: 0.0623 | Test Loss: 0.1328 | 损失比: 0.47:1
+Epoch 290 | Train Loss: 0.0623 | Test Loss: 0.1324 | 损失比: 0.47:1
+Epoch 0 | Train Loss: 0.3257 | Test Loss: 0.2338 | 损失比: 1.39:1
+Epoch 10 | Train Loss: 0.1292 | Test Loss: 0.1531 | 损失比: 0.84:1
+Epoch 20 | Train Loss: 0.1048 | Test Loss: 0.1526 | 损失比: 0.69:1
+Epoch 30 | Train Loss: 0.0880 | Test Loss: 0.1500 | 损失比: 0.59:1
+Epoch 40 | Train Loss: 0.0775 | Test Loss: 0.1463 | 损失比: 0.53:1
+Epoch 50 | Train Loss: 0.0715 | Test Loss: 0.1437 | 损失比: 0.50:1
+Epoch 60 | Train Loss: 0.0683 | Test Loss: 0.1424 | 损失比: 0.48:1
+Epoch 70 | Train Loss: 0.0664 | Test Loss: 0.1409 | 损失比: 0.47:1
+Epoch 80 | Train Loss: 0.0653 | Test Loss: 0.1392 | 损失比: 0.47:1
+Epoch 90 | Train Loss: 0.0645 | Test Loss: 0.1381 | 损失比: 0.47:1
+Epoch 100 | Train Loss: 0.0640 | Test Loss: 0.1369 | 损失比: 0.47:1
+Epoch 110 | Train Loss: 0.0637 | Test Loss: 0.1361 | 损失比: 0.47:1
+Epoch 120 | Train Loss: 0.0634 | Test Loss: 0.1355 | 损失比: 0.47:1
+Epoch 130 | Train Loss: 0.0632 | Test Loss: 0.1352 | 损失比: 0.47:1
+Epoch 140 | Train Loss: 0.0630 | Test Loss: 0.1342 | 损失比: 0.47:1
+Epoch 150 | Train Loss: 0.0629 | Test Loss: 0.1338 | 损失比: 0.47:1
+Epoch 160 | Train Loss: 0.0628 | Test Loss: 0.1334 | 损失比: 0.47:1
+Epoch 170 | Train Loss: 0.0627 | Test Loss: 0.1330 | 损失比: 0.47:1
+Epoch 180 | Train Loss: 0.0626 | Test Loss: 0.1322 | 损失比: 0.47:1
+Epoch 190 | Train Loss: 0.0625 | Test Loss: 0.1319 | 损失比: 0.47:1
+Epoch 200 | Train Loss: 0.0624 | Test Loss: 0.1315 | 损失比: 0.47:1
+Epoch 210 | Train Loss: 0.0624 | Test Loss: 0.1310 | 损失比: 0.48:1
+Epoch 220 | Train Loss: 0.0623 | Test Loss: 0.1310 | 损失比: 0.48:1
+Epoch 230 | Train Loss: 0.0623 | Test Loss: 0.1303 | 损失比: 0.48:1
+Epoch 240 | Train Loss: 0.0622 | Test Loss: 0.1301 | 损失比: 0.48:1
+Epoch 250 | Train Loss: 0.0622 | Test Loss: 0.1300 | 损失比: 0.48:1
+Epoch 260 | Train Loss: 0.0621 | Test Loss: 0.1298 | 损失比: 0.48:1
+Epoch 270 | Train Loss: 0.0621 | Test Loss: 0.1301 | 损失比: 0.48:1
+Epoch 280 | Train Loss: 0.0621 | Test Loss: 0.1296 | 损失比: 0.48:1
+Epoch 290 | Train Loss: 0.0620 | Test Loss: 0.1297 | 损失比: 0.48:1
+Epoch 0 | Train Loss: 0.3614 | Test Loss: 0.2802 | Loss Factor: 1.29:1
+Epoch 10 | Train Loss: 0.1415 | Test Loss: 0.1612 | Loss Factor: 0.88:1
+Epoch 20 | Train Loss: 0.1115 | Test Loss: 0.1352 | Loss Factor: 0.82:1
+Epoch 30 | Train Loss: 0.0916 | Test Loss: 0.1180 | Loss Factor: 0.78:1
+Epoch 40 | Train Loss: 0.0795 | Test Loss: 0.1090 | Loss Factor: 0.73:1
+Epoch 50 | Train Loss: 0.0722 | Test Loss: 0.1074 | Loss Factor: 0.67:1
+Epoch 60 | Train Loss: 0.0687 | Test Loss: 0.1098 | Loss Factor: 0.63:1
+Epoch 70 | Train Loss: 0.0667 | Test Loss: 0.1129 | Loss Factor: 0.59:1
+Epoch 80 | Train Loss: 0.0655 | Test Loss: 0.1164 | Loss Factor: 0.56:1
+Epoch 90 | Train Loss: 0.0646 | Test Loss: 0.1188 | Loss Factor: 0.54:1
+Epoch 100 | Train Loss: 0.0641 | Test Loss: 0.1212 | Loss Factor: 0.53:1
+Epoch 110 | Train Loss: 0.0637 | Test Loss: 0.1227 | Loss Factor: 0.52:1
+Epoch 120 | Train Loss: 0.0635 | Test Loss: 0.1237 | Loss Factor: 0.51:1
+Epoch 130 | Train Loss: 0.0633 | Test Loss: 0.1245 | Loss Factor: 0.51:1
+Epoch 140 | Train Loss: 0.0631 | Test Loss: 0.1249 | Loss Factor: 0.51:1
+Epoch 150 | Train Loss: 0.0630 | Test Loss: 0.1255 | Loss Factor: 0.50:1
+Epoch 160 | Train Loss: 0.0629 | Test Loss: 0.1254 | Loss Factor: 0.50:1
+Epoch 170 | Train Loss: 0.0628 | Test Loss: 0.1259 | Loss Factor: 0.50:1
+Epoch 180 | Train Loss: 0.0627 | Test Loss: 0.1258 | Loss Factor: 0.50:1
+Epoch 190 | Train Loss: 0.0627 | Test Loss: 0.1260 | Loss Factor: 0.50:1
+Epoch 200 | Train Loss: 0.0626 | Test Loss: 0.1263 | Loss Factor: 0.50:1
+Epoch 210 | Train Loss: 0.0625 | Test Loss: 0.1262 | Loss Factor: 0.50:1
+Epoch 220 | Train Loss: 0.0625 | Test Loss: 0.1262 | Loss Factor: 0.50:1
+Epoch 230 | Train Loss: 0.0624 | Test Loss: 0.1268 | Loss Factor: 0.49:1
+Epoch 240 | Train Loss: 0.0624 | Test Loss: 0.1267 | Loss Factor: 0.49:1
+Epoch 250 | Train Loss: 0.0623 | Test Loss: 0.1268 | Loss Factor: 0.49:1
+Epoch 260 | Train Loss: 0.0623 | Test Loss: 0.1268 | Loss Factor: 0.49:1
+Epoch 270 | Train Loss: 0.0623 | Test Loss: 0.1269 | Loss Factor: 0.49:1
+Epoch 280 | Train Loss: 0.0622 | Test Loss: 0.1271 | Loss Factor: 0.49:1
+Epoch 290 | Train Loss: 0.0622 | Test Loss: 0.1271 | Loss Factor: 0.49:1