tensorflow TF slim Inception V3训练损耗曲线很奇怪

TF超薄接收V3列车从头开始

我使用slim/train_image_classifier.py在我自己的数据集上训练inception_v3模型： python train\u image\u classifier.py--train\u dir=${train\u dir}--dataset\u name=mydataset--dataset\u split\u name=train--dataset\u dir=${dataset\u dir}--model\u name=inception\u v3--num\u clones=2

损耗曲线很奇怪，如张力板所示，它是一条线性递减的直线，有一点凸起。

以下是最后的输出，损耗每20或30步降低0.0001：

INFO:tensorflow:global step 34590: loss = 0.5359 (1.17 sec/step)
INFO:tensorflow:global step 34600: loss = 0.5358 (1.15 sec/step)
INFO:tensorflow:global step 34590: loss = 0.5359 (1.17 sec/step)
INFO:tensorflow:global step 34600: loss = 0.5358 (1.15 sec/step)
INFO:tensorflow:global step 34610: loss = 0.5358 (1.17 sec/step)
INFO:tensorflow:global step 34620: loss = 0.5357 (1.12 sec/step)
INFO:tensorflow:global step 34630: loss = 0.5357 (1.16 sec/step)
INFO:tensorflow:global step 34640: loss = 0.5356 (1.16 sec/step)
INFO:tensorflow:global step 34650: loss = 0.5356 (1.16 sec/step)
INFO:tensorflow:global step 34660: loss = 0.5355 (1.15 sec/step)
INFO:tensorflow:global step 34670: loss = 0.5355 (1.15 sec/step)
INFO:tensorflow:global step 34680: loss = 0.5355 (1.18 sec/step)
INFO:tensorflow:global step 34690: loss = 0.5354 (1.17 sec/step)
INFO:tensorflow:global step 34700: loss = 0.5354 (1.15 sec/step)
INFO:tensorflow:global step 34710: loss = 0.5353 (1.15 sec/step)
INFO:tensorflow:global step 34720: loss = 0.5353 (2.25 sec/step)
INFO:tensorflow:global step 34730: loss = 0.5353 (2.22 sec/step)
INFO:tensorflow:global step 34740: loss = 0.5352 (1.16 sec/step)
INFO:tensorflow:global step 34750: loss = 0.5352 (1.16 sec/step)
INFO:tensorflow:global step 34760: loss = 0.5351 (1.18 sec/step)
INFO:tensorflow:global step 34770: loss = 0.5351 (1.15 sec/step)
INFO:tensorflow:global step 34780: loss = 0.5350 (1.17 sec/step)
INFO:tensorflow:global step 34790: loss = 0.5350 (1.15 sec/step)
INFO:tensorflow:global step 34800: loss = 0.5349 (1.12 sec/step)
INFO:tensorflow:global step 34810: loss = 0.5349 (1.12 sec/step)
INFO:tensorflow:global step 34820: loss = 0.5349 (1.16 sec/step)
INFO:tensorflow:global step 34830: loss = 0.5348 (1.16 sec/step)
INFO:tensorflow:global step 34840: loss = 0.5348 (1.18 sec/step)
INFO:tensorflow:global step 34850: loss = 0.5347 (1.12 sec/step)
INFO:tensorflow:global step 34860: loss = 0.5347 (1.12 sec/step)
INFO:tensorflow:global step 34870: loss = 0.5347 (1.18 sec/step)
INFO:tensorflow:global step 34880: loss = 0.5346 (1.13 sec/step)
INFO:tensorflow:global step 34890: loss = 0.5346 (1.18 sec/step)
INFO:tensorflow:global step 34900: loss = 0.5345 (1.16 sec/step)
INFO:tensorflow:global step 34910: loss = 0.5345 (1.15 sec/step)
INFO:tensorflow:global step 34920: loss = 0.5344 (1.17 sec/step)
INFO:tensorflow:global step 34930: loss = 0.5344 (1.14 sec/step)
INFO:tensorflow:global step 34940: loss = 0.5344 (1.15 sec/step)
INFO:tensorflow:global step 34950: loss = 0.5343 (1.14 sec/step)
INFO:tensorflow:global step 34960: loss = 0.5343 (1.17 sec/step)  

mydataset.py与flowers.py相同，只是：

SPLITS_TO_SIZES = {'train': 18000000, 'validation': 400000}
 _NUM_CLASSES = 4

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这正常吗？感谢您的帮助。

您正在绘制培训中n步之后的总损耗图（如果您使用tf.contrib.slim train方法，这可能是步骤数），而记录的损耗为每10步。

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希望这有帮助

您正在绘制训练中n步（如果使用tf.contrib.slim train方法，可能是步数）后的总损耗图，而记录的损耗是每10步一次。 希望这有帮助