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  1. Batch size: 8
  2. Epochs: 10
  3. Save to: models/maskrcnn-nonorm-nopre-24x40
  4. MaskRCNN(
  5. (transform): GeneralizedRCNNTransform(
  6. Normalize(mean=(0, 0, 0), std=(1, 1, 1))
  7. Resize(min_size=(800,), max_size=1333, mode='bilinear')
  8. )
  9. (backbone): BackboneWithFPN(
  10. (body): IntermediateLayerGetter(
  11. (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
  12. (bn1): FrozenBatchNorm2d(64, eps=1e-05)
  13. (relu): ReLU(inplace=True)
  14. (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
  15. (layer1): Sequential(
  16. (0): Bottleneck(
  17. (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  18. (bn1): FrozenBatchNorm2d(64, eps=1e-05)
  19. (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  20. (bn2): FrozenBatchNorm2d(64, eps=1e-05)
  21. (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  22. (bn3): FrozenBatchNorm2d(256, eps=1e-05)
  23. (relu): ReLU(inplace=True)
  24. (downsample): Sequential(
  25. (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  26. (1): FrozenBatchNorm2d(256, eps=1e-05)
  27. )
  28. )
  29. (1): Bottleneck(
  30. (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  31. (bn1): FrozenBatchNorm2d(64, eps=1e-05)
  32. (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  33. (bn2): FrozenBatchNorm2d(64, eps=1e-05)
  34. (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  35. (bn3): FrozenBatchNorm2d(256, eps=1e-05)
  36. (relu): ReLU(inplace=True)
  37. )
  38. (2): Bottleneck(
  39. (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
  40. (bn1): FrozenBatchNorm2d(64, eps=1e-05)
  41. (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  42. (bn2): FrozenBatchNorm2d(64, eps=1e-05)
  43. (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  44. (bn3): FrozenBatchNorm2d(256, eps=1e-05)
  45. (relu): ReLU(inplace=True)
  46. )
  47. )
  48. (layer2): Sequential(
  49. (0): Bottleneck(
  50. (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  51. (bn1): FrozenBatchNorm2d(128, eps=1e-05)
  52. (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  53. (bn2): FrozenBatchNorm2d(128, eps=1e-05)
  54. (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  55. (bn3): FrozenBatchNorm2d(512, eps=1e-05)
  56. (relu): ReLU(inplace=True)
  57. (downsample): Sequential(
  58. (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
  59. (1): FrozenBatchNorm2d(512, eps=1e-05)
  60. )
  61. )
  62. (1): Bottleneck(
  63. (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  64. (bn1): FrozenBatchNorm2d(128, eps=1e-05)
  65. (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  66. (bn2): FrozenBatchNorm2d(128, eps=1e-05)
  67. (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  68. (bn3): FrozenBatchNorm2d(512, eps=1e-05)
  69. (relu): ReLU(inplace=True)
  70. )
  71. (2): Bottleneck(
  72. (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  73. (bn1): FrozenBatchNorm2d(128, eps=1e-05)
  74. (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  75. (bn2): FrozenBatchNorm2d(128, eps=1e-05)
  76. (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  77. (bn3): FrozenBatchNorm2d(512, eps=1e-05)
  78. (relu): ReLU(inplace=True)
  79. )
  80. (3): Bottleneck(
  81. (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
  82. (bn1): FrozenBatchNorm2d(128, eps=1e-05)
  83. (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  84. (bn2): FrozenBatchNorm2d(128, eps=1e-05)
  85. (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  86. (bn3): FrozenBatchNorm2d(512, eps=1e-05)
  87. (relu): ReLU(inplace=True)
  88. )
  89. )
  90. (layer3): Sequential(
  91. (0): Bottleneck(
  92. (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  93. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  94. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  95. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  96. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  97. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  98. (relu): ReLU(inplace=True)
  99. (downsample): Sequential(
  100. (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
  101. (1): FrozenBatchNorm2d(1024, eps=1e-05)
  102. )
  103. )
  104. (1): Bottleneck(
  105. (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  106. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  107. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  108. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  109. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  110. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  111. (relu): ReLU(inplace=True)
  112. )
  113. (2): Bottleneck(
  114. (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  115. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  116. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  117. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  118. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  119. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  120. (relu): ReLU(inplace=True)
  121. )
  122. (3): Bottleneck(
  123. (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  124. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  125. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  126. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  127. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  128. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  129. (relu): ReLU(inplace=True)
  130. )
  131. (4): Bottleneck(
  132. (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  133. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  134. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  135. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  136. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  137. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  138. (relu): ReLU(inplace=True)
  139. )
  140. (5): Bottleneck(
  141. (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
  142. (bn1): FrozenBatchNorm2d(256, eps=1e-05)
  143. (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  144. (bn2): FrozenBatchNorm2d(256, eps=1e-05)
  145. (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
  146. (bn3): FrozenBatchNorm2d(1024, eps=1e-05)
  147. (relu): ReLU(inplace=True)
  148. )
  149. )
  150. (layer4): Sequential(
  151. (0): Bottleneck(
  152. (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  153. (bn1): FrozenBatchNorm2d(512, eps=1e-05)
  154. (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  155. (bn2): FrozenBatchNorm2d(512, eps=1e-05)
  156. (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
  157. (bn3): FrozenBatchNorm2d(2048, eps=1e-05)
  158. (relu): ReLU(inplace=True)
  159. (downsample): Sequential(
  160. (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
  161. (1): FrozenBatchNorm2d(2048, eps=1e-05)
  162. )
  163. )
  164. (1): Bottleneck(
  165. (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  166. (bn1): FrozenBatchNorm2d(512, eps=1e-05)
  167. (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  168. (bn2): FrozenBatchNorm2d(512, eps=1e-05)
  169. (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
  170. (bn3): FrozenBatchNorm2d(2048, eps=1e-05)
  171. (relu): ReLU(inplace=True)
  172. )
  173. (2): Bottleneck(
  174. (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
  175. (bn1): FrozenBatchNorm2d(512, eps=1e-05)
  176. (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  177. (bn2): FrozenBatchNorm2d(512, eps=1e-05)
  178. (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
  179. (bn3): FrozenBatchNorm2d(2048, eps=1e-05)
  180. (relu): ReLU(inplace=True)
  181. )
  182. )
  183. )
  184. (fpn): FeaturePyramidNetwork(
  185. (inner_blocks): ModuleList(
  186. (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))
  187. (1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))
  188. (2): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1))
  189. (3): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))
  190. )
  191. (layer_blocks): ModuleList(
  192. (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  193. (1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  194. (2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  195. (3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  196. )
  197. (extra_blocks): LastLevelMaxPool()
  198. )
  199. )
  200. (rpn): RegionProposalNetwork(
  201. (anchor_generator): AnchorGenerator()
  202. (head): RPNHead(
  203. (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  204. (cls_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))
  205. (bbox_pred): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))
  206. )
  207. )
  208. (roi_heads): RoIHeads(
  209. (box_roi_pool): MultiScaleRoIAlign(featmap_names=['0', '1', '2', '3'], output_size=(7, 7), sampling_ratio=2)
  210. (box_head): TwoMLPHead(
  211. (fc6): Linear(in_features=12544, out_features=1024, bias=True)
  212. (fc7): Linear(in_features=1024, out_features=1024, bias=True)
  213. )
  214. (box_predictor): FastRCNNPredictor(
  215. (cls_score): Linear(in_features=1024, out_features=3, bias=True)
  216. (bbox_pred): Linear(in_features=1024, out_features=12, bias=True)
  217. )
  218. (mask_roi_pool): MultiScaleRoIAlign(featmap_names=['0', '1', '2', '3'], output_size=(14, 14), sampling_ratio=2)
  219. (mask_head): MaskRCNNHeads(
  220. (mask_fcn1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  221. (relu1): ReLU(inplace=True)
  222. (mask_fcn2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  223. (relu2): ReLU(inplace=True)
  224. (mask_fcn3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  225. (relu3): ReLU(inplace=True)
  226. (mask_fcn4): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  227. (relu4): ReLU(inplace=True)
  228. )
  229. (mask_predictor): MaskRCNNPredictor(
  230. (conv5_mask): ConvTranspose2d(256, 256, kernel_size=(2, 2), stride=(2, 2))
  231. (relu): ReLU(inplace=True)
  232. (mask_fcn_logits): Conv2d(256, 3, kernel_size=(1, 1), stride=(1, 1))
  233. )
  234. )
  235. )
  236. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  237. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  238. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  239. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  240. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  241. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  242. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  243. ['C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\python39.zip', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\DLLs', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39\\lib', 'C:\\Users\\cjo\\AppData\\Local\\Programs\\Python\\Python39', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\venv\\lib\\site-packages', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external', 'C:\\Users\\cjo\\PycharmProjects\\sunshaine-ai\\external']
  244. Epoch: [0] [ 0/2000] eta: 3:55:24 lr: 0.000010 loss: 5.0055 (5.0055) loss_classifier: 1.1087 (1.1087) loss_box_reg: 0.0002 (0.0002) loss_mask: 2.8781 (2.8781) loss_objectness: 0.6854 (0.6854) loss_rpn_box_reg: 0.3332 (0.3332) time: 7.0623 data: 2.3752 max mem: 8237
  245. Epoch: [0] [ 10/2000] eta: 0:49:02 lr: 0.000060 loss: 3.4765 (3.6642) loss_classifier: 1.1009 (1.0983) loss_box_reg: 0.0001 (0.0001) loss_mask: 1.3545 (1.5481) loss_objectness: 0.6872 (0.6870) loss_rpn_box_reg: 0.3315 (0.3307) time: 1.4787 data: 0.2203 max mem: 8508
  246. Epoch: [0] [ 20/2000] eta: 0:39:30 lr: 0.000110 loss: 2.8087 (3.1113) loss_classifier: 1.0726 (1.0652) loss_box_reg: 0.0001 (0.0001) loss_mask: 0.7226 (1.0326) loss_objectness: 0.6857 (0.6853) loss_rpn_box_reg: 0.3274 (0.3281) time: 0.9039 data: 0.0024 max mem: 8508
  247. Epoch: [0] [ 30/2000] eta: 0:35:46 lr: 0.000160 loss: 2.1517 (2.7415) loss_classifier: 0.9557 (1.0013) loss_box_reg: 0.0001 (0.0001) loss_mask: 0.1968 (0.7363) loss_objectness: 0.6802 (0.6815) loss_rpn_box_reg: 0.3189 (0.3223) time: 0.8758 data: 0.0000 max mem: 8508
  248. Epoch: [0] [ 40/2000] eta: 0:33:57 lr: 0.000210 loss: 1.7182 (2.4092) loss_classifier: 0.7205 (0.8717) loss_box_reg: 0.0002 (0.0026) loss_mask: 0.0435 (0.5625) loss_objectness: 0.6618 (0.6695) loss_rpn_box_reg: 0.2922 (0.3030) time: 0.8742 data: 0.0016 max mem: 8508
  249. Epoch: [0] [ 50/2000] eta: 0:32:40 lr: 0.000260 loss: 1.0061 (2.0859) loss_classifier: 0.1969 (0.7182) loss_box_reg: 0.0463 (0.0154) loss_mask: 0.0084 (0.4530) loss_objectness: 0.5571 (0.6223) loss_rpn_box_reg: 0.1896 (0.2770) time: 0.8750 data: 0.0024 max mem: 8508
  250. Epoch: [0] [ 60/2000] eta: 0:31:58 lr: 0.000310 loss: 0.5213 (1.8054) loss_classifier: 0.0526 (0.6087) loss_box_reg: 0.0562 (0.0221) loss_mask: 0.0003 (0.3787) loss_objectness: 0.2736 (0.5428) loss_rpn_box_reg: 0.1444 (0.2531) time: 0.8844 data: 0.0016 max mem: 8508
  251. Epoch: [0] [ 70/2000] eta: 0:31:38 lr: 0.000360 loss: 0.3108 (1.5926) loss_classifier: 0.0498 (0.5300) loss_box_reg: 0.0562 (0.0271) loss_mask: 0.0000 (0.3256) loss_objectness: 0.0550 (0.4718) loss_rpn_box_reg: 0.1400 (0.2381) time: 0.9274 data: 0.0008 max mem: 8508
  252. Epoch: [0] [ 80/2000] eta: 0:31:21 lr: 0.000410 loss: 0.2690 (1.4273) loss_classifier: 0.0541 (0.4712) loss_box_reg: 0.0580 (0.0310) loss_mask: 0.0000 (0.2854) loss_objectness: 0.0308 (0.4171) loss_rpn_box_reg: 0.1276 (0.2226) time: 0.9531 data: 0.0000 max mem: 8508
  253. Epoch: [0] [ 90/2000] eta: 0:30:57 lr: 0.000460 loss: 0.2427 (1.2961) loss_classifier: 0.0547 (0.4255) loss_box_reg: 0.0600 (0.0342) loss_mask: 0.0000 (0.2540) loss_objectness: 0.0278 (0.3742) loss_rpn_box_reg: 0.0950 (0.2082) time: 0.9328 data: 0.0016 max mem: 8508
  254. Epoch: [0] [ 100/2000] eta: 0:30:29 lr: 0.000509 loss: 0.2254 (1.1897) loss_classifier: 0.0535 (0.3887) loss_box_reg: 0.0588 (0.0366) loss_mask: 0.0000 (0.2289) loss_objectness: 0.0229 (0.3392) loss_rpn_box_reg: 0.0887 (0.1963) time: 0.8946 data: 0.0016 max mem: 8508
  255. Epoch: [0] [ 110/2000] eta: 0:30:05 lr: 0.000559 loss: 0.2167 (1.1020) loss_classifier: 0.0524 (0.3584) loss_box_reg: 0.0564 (0.0382) loss_mask: 0.0000 (0.2083) loss_objectness: 0.0211 (0.3105) loss_rpn_box_reg: 0.0881 (0.1866) time: 0.8789 data: 0.0008 max mem: 8508
  256. Epoch: [0] [ 120/2000] eta: 0:29:54 lr: 0.000609 loss: 0.2165 (1.0289) loss_classifier: 0.0520 (0.3332) loss_box_reg: 0.0555 (0.0394) loss_mask: 0.0000 (0.1910) loss_objectness: 0.0201 (0.2864) loss_rpn_box_reg: 0.0881 (0.1789) time: 0.9117 data: 0.0008 max mem: 8508
  257. Epoch: [0] [ 130/2000] eta: 0:29:36 lr: 0.000659 loss: 0.2163 (0.9668) loss_classifier: 0.0518 (0.3117) loss_box_reg: 0.0497 (0.0401) loss_mask: 0.0000 (0.1765) loss_objectness: 0.0201 (0.2660) loss_rpn_box_reg: 0.0888 (0.1725) time: 0.9180 data: 0.0023 max mem: 8508
  258. Epoch: [0] [ 140/2000] eta: 0:29:17 lr: 0.000709 loss: 0.2188 (0.9138) loss_classifier: 0.0502 (0.2931) loss_box_reg: 0.0480 (0.0408) loss_mask: 0.0000 (0.1640) loss_objectness: 0.0196 (0.2484) loss_rpn_box_reg: 0.0956 (0.1676) time: 0.8875 data: 0.0031 max mem: 8508
  259. Epoch: [0] [ 150/2000] eta: 0:28:56 lr: 0.000759 loss: 0.2188 (0.8674) loss_classifier: 0.0502 (0.2770) loss_box_reg: 0.0478 (0.0412) loss_mask: 0.0000 (0.1531) loss_objectness: 0.0191 (0.2331) loss_rpn_box_reg: 0.0990 (0.1630) time: 0.8665 data: 0.0016 max mem: 8508
  260. Epoch: [0] [ 160/2000] eta: 0:28:37 lr: 0.000809 loss: 0.2193 (0.8282) loss_classifier: 0.0490 (0.2628) loss_box_reg: 0.0475 (0.0416) loss_mask: 0.0000 (0.1436) loss_objectness: 0.0194 (0.2199) loss_rpn_box_reg: 0.1035 (0.1603) time: 0.8502 data: 0.0023 max mem: 8508
  261. Epoch: [0] [ 170/2000] eta: 0:28:18 lr: 0.000859 loss: 0.2137 (0.7919) loss_classifier: 0.0483 (0.2503) loss_box_reg: 0.0471 (0.0419) loss_mask: 0.0000 (0.1352) loss_objectness: 0.0202 (0.2082) loss_rpn_box_reg: 0.0928 (0.1563) time: 0.8503 data: 0.0031 max mem: 8508
  262. Epoch: [0] [ 180/2000] eta: 0:28:01 lr: 0.000909 loss: 0.2021 (0.7592) loss_classifier: 0.0478 (0.2390) loss_box_reg: 0.0433 (0.0419) loss_mask: 0.0000 (0.1279) loss_objectness: 0.0199 (0.1978) loss_rpn_box_reg: 0.0912 (0.1527) time: 0.8496 data: 0.0031 max mem: 8508
  263. Epoch: [0] [ 190/2000] eta: 0:27:45 lr: 0.000959 loss: 0.2016 (0.7304) loss_classifier: 0.0470 (0.2290) loss_box_reg: 0.0409 (0.0419) loss_mask: 0.0000 (0.1212) loss_objectness: 0.0184 (0.1883) loss_rpn_box_reg: 0.0926 (0.1499) time: 0.8495 data: 0.0039 max mem: 8508
  264. Epoch: [0] [ 200/2000] eta: 0:27:30 lr: 0.001009 loss: 0.1994 (0.7038) loss_classifier: 0.0470 (0.2200) loss_box_reg: 0.0416 (0.0419) loss_mask: 0.0000 (0.1152) loss_objectness: 0.0165 (0.1798) loss_rpn_box_reg: 0.0926 (0.1470) time: 0.8502 data: 0.0031 max mem: 8508
  265. Epoch: [0] [ 210/2000] eta: 0:27:15 lr: 0.001059 loss: 0.1944 (0.6798) loss_classifier: 0.0470 (0.2118) loss_box_reg: 0.0412 (0.0419) loss_mask: 0.0000 (0.1097) loss_objectness: 0.0159 (0.1721) loss_rpn_box_reg: 0.0899 (0.1443) time: 0.8494 data: 0.0016 max mem: 8508
  266. Epoch: [0] [ 220/2000] eta: 0:27:00 lr: 0.001109 loss: 0.2080 (0.6594) loss_classifier: 0.0479 (0.2045) loss_box_reg: 0.0415 (0.0421) loss_mask: 0.0000 (0.1054) loss_objectness: 0.0178 (0.1652) loss_rpn_box_reg: 0.0906 (0.1422) time: 0.8487 data: 0.0016 max mem: 8508
  267. Epoch: [0] [ 230/2000] eta: 0:26:46 lr: 0.001159 loss: 0.2058 (0.6395) loss_classifier: 0.0485 (0.1977) loss_box_reg: 0.0449 (0.0421) loss_mask: 0.0000 (0.1008) loss_objectness: 0.0200 (0.1589) loss_rpn_box_reg: 0.0902 (0.1399) time: 0.8495 data: 0.0023 max mem: 8508
  268. Epoch: [0] [ 240/2000] eta: 0:26:33 lr: 0.001209 loss: 0.1962 (0.6209) loss_classifier: 0.0473 (0.1914) loss_box_reg: 0.0393 (0.0419) loss_mask: 0.0000 (0.0966) loss_objectness: 0.0173 (0.1530) loss_rpn_box_reg: 0.0883 (0.1379) time: 0.8494 data: 0.0023 max mem: 8508
  269. Epoch: [0] [ 250/2000] eta: 0:26:20 lr: 0.001259 loss: 0.1902 (0.6036) loss_classifier: 0.0449 (0.1855) loss_box_reg: 0.0369 (0.0417) loss_mask: 0.0000 (0.0928) loss_objectness: 0.0158 (0.1476) loss_rpn_box_reg: 0.0899 (0.1361) time: 0.8495 data: 0.0016 max mem: 8508
  270. Epoch: [0] [ 260/2000] eta: 0:26:08 lr: 0.001309 loss: 0.1870 (0.5879) loss_classifier: 0.0424 (0.1800) loss_box_reg: 0.0342 (0.0414) loss_mask: 0.0000 (0.0892) loss_objectness: 0.0155 (0.1425) loss_rpn_box_reg: 0.0909 (0.1346) time: 0.8494 data: 0.0031 max mem: 8508
  271. Epoch: [0] [ 270/2000] eta: 0:25:55 lr: 0.001359 loss: 0.1971 (0.5749) loss_classifier: 0.0424 (0.1750) loss_box_reg: 0.0349 (0.0414) loss_mask: 0.0000 (0.0867) loss_objectness: 0.0179 (0.1380) loss_rpn_box_reg: 0.1050 (0.1339) time: 0.8501 data: 0.0046 max mem: 8508
  272. Epoch: [0] [ 280/2000] eta: 0:25:46 lr: 0.001409 loss: 0.2371 (0.5629) loss_classifier: 0.0448 (0.1705) loss_box_reg: 0.0430 (0.0415) loss_mask: 0.0002 (0.0836) loss_objectness: 0.0215 (0.1340) loss_rpn_box_reg: 0.1177 (0.1333) time: 0.8689 data: 0.0023 max mem: 8508
  273. Epoch: [0] [ 290/2000] eta: 0:25:36 lr: 0.001459 loss: 0.2167 (0.5507) loss_classifier: 0.0491 (0.1663) loss_box_reg: 0.0412 (0.0415) loss_mask: 0.0001 (0.0807) loss_objectness: 0.0232 (0.1301) loss_rpn_box_reg: 0.0990 (0.1321) time: 0.8881 data: 0.0016 max mem: 8508
  274. Epoch: [0] [ 300/2000] eta: 0:25:27 lr: 0.001508 loss: 0.1945 (0.5386) loss_classifier: 0.0453 (0.1622) loss_box_reg: 0.0380 (0.0413) loss_mask: 0.0000 (0.0780) loss_objectness: 0.0202 (0.1264) loss_rpn_box_reg: 0.0935 (0.1307) time: 0.8914 data: 0.0031 max mem: 8508
  275. Epoch: [0] [ 310/2000] eta: 0:25:16 lr: 0.001558 loss: 0.1848 (0.5271) loss_classifier: 0.0431 (0.1584) loss_box_reg: 0.0345 (0.0410) loss_mask: 0.0000 (0.0755) loss_objectness: 0.0165 (0.1228) loss_rpn_box_reg: 0.0892 (0.1294) time: 0.8760 data: 0.0023 max mem: 8508
  276. Epoch: [0] [ 320/2000] eta: 0:25:05 lr: 0.001608 loss: 0.1790 (0.5164) loss_classifier: 0.0424 (0.1548) loss_box_reg: 0.0337 (0.0408) loss_mask: 0.0000 (0.0732) loss_objectness: 0.0163 (0.1195) loss_rpn_box_reg: 0.0887 (0.1281) time: 0.8601 data: 0.0014 max mem: 8508
  277. Epoch: [0] [ 330/2000] eta: 0:24:54 lr: 0.001658 loss: 0.1798 (0.5062) loss_classifier: 0.0405 (0.1513) loss_box_reg: 0.0318 (0.0405) loss_mask: 0.0000 (0.0710) loss_objectness: 0.0163 (0.1164) loss_rpn_box_reg: 0.0877 (0.1270) time: 0.8617 data: 0.0014 max mem: 8508
  278. Epoch: [0] [ 340/2000] eta: 0:24:43 lr: 0.001708 loss: 0.1823 (0.4975) loss_classifier: 0.0391 (0.1480) loss_box_reg: 0.0309 (0.0402) loss_mask: 0.0000 (0.0689) loss_objectness: 0.0156 (0.1135) loss_rpn_box_reg: 0.0911 (0.1269) time: 0.8618 data: 0.0016 max mem: 8508
  279. Epoch: [0] [ 350/2000] eta: 0:24:33 lr: 0.001758 loss: 0.2260 (0.4909) loss_classifier: 0.0391 (0.1450) loss_box_reg: 0.0339 (0.0401) loss_mask: 0.0000 (0.0669) loss_objectness: 0.0200 (0.1110) loss_rpn_box_reg: 0.1328 (0.1280) time: 0.8656 data: 0.0023 max mem: 8508
  280. Epoch: [0] [ 360/2000] eta: 0:24:24 lr: 0.001808 loss: 0.2171 (0.4830) loss_classifier: 0.0409 (0.1422) loss_box_reg: 0.0346 (0.0399) loss_mask: 0.0000 (0.0651) loss_objectness: 0.0224 (0.1085) loss_rpn_box_reg: 0.1216 (0.1274) time: 0.8797 data: 0.0024 max mem: 8508
  281. Epoch: [0] [ 370/2000] eta: 0:24:15 lr: 0.001858 loss: 0.1994 (0.4752) loss_classifier: 0.0415 (0.1394) loss_box_reg: 0.0323 (0.0397) loss_mask: 0.0000 (0.0633) loss_objectness: 0.0216 (0.1061) loss_rpn_box_reg: 0.1028 (0.1266) time: 0.8891 data: 0.0016 max mem: 8508
  282. Epoch: [0] [ 380/2000] eta: 0:24:06 lr: 0.001908 loss: 0.1994 (0.4682) loss_classifier: 0.0380 (0.1367) loss_box_reg: 0.0290 (0.0394) loss_mask: 0.0000 (0.0616) loss_objectness: 0.0216 (0.1039) loss_rpn_box_reg: 0.1077 (0.1265) time: 0.8820 data: 0.0031 max mem: 8508
  283. Epoch: [0] [ 390/2000] eta: 0:23:56 lr: 0.001958 loss: 0.2003 (0.4611) loss_classifier: 0.0369 (0.1342) loss_box_reg: 0.0289 (0.0392) loss_mask: 0.0000 (0.0601) loss_objectness: 0.0202 (0.1018) loss_rpn_box_reg: 0.1067 (0.1259) time: 0.8711 data: 0.0039 max mem: 8508
  284. Epoch: [0] [ 400/2000] eta: 0:23:46 lr: 0.002008 loss: 0.1879 (0.4546) loss_classifier: 0.0369 (0.1317) loss_box_reg: 0.0279 (0.0389) loss_mask: 0.0000 (0.0586) loss_objectness: 0.0194 (0.0997) loss_rpn_box_reg: 0.1047 (0.1257) time: 0.8734 data: 0.0023 max mem: 8508
  285. Epoch: [0] [ 410/2000] eta: 0:23:36 lr: 0.002058 loss: 0.2070 (0.4487) loss_classifier: 0.0377 (0.1294) loss_box_reg: 0.0246 (0.0386) loss_mask: 0.0000 (0.0572) loss_objectness: 0.0189 (0.0977) loss_rpn_box_reg: 0.1225 (0.1258) time: 0.8720 data: 0.0023 max mem: 8508
  286. Epoch: [0] [ 420/2000] eta: 0:23:26 lr: 0.002108 loss: 0.2216 (0.4430) loss_classifier: 0.0364 (0.1272) loss_box_reg: 0.0242 (0.0383) loss_mask: 0.0001 (0.0558) loss_objectness: 0.0208 (0.0959) loss_rpn_box_reg: 0.1384 (0.1259) time: 0.8590 data: 0.0039 max mem: 8508
  287. Epoch: [0] [ 430/2000] eta: 0:23:16 lr: 0.002158 loss: 0.2116 (0.4377) loss_classifier: 0.0365 (0.1251) loss_box_reg: 0.0269 (0.0381) loss_mask: 0.0001 (0.0545) loss_objectness: 0.0208 (0.0942) loss_rpn_box_reg: 0.1260 (0.1258) time: 0.8543 data: 0.0046 max mem: 8508
  288. Epoch: [0] [ 440/2000] eta: 0:23:06 lr: 0.002208 loss: 0.1962 (0.4318) loss_classifier: 0.0349 (0.1230) loss_box_reg: 0.0281 (0.0378) loss_mask: 0.0001 (0.0533) loss_objectness: 0.0187 (0.0925) loss_rpn_box_reg: 0.1077 (0.1252) time: 0.8557 data: 0.0038 max mem: 8508
  289. Epoch: [0] [ 450/2000] eta: 0:22:56 lr: 0.002258 loss: 0.1780 (0.4265) loss_classifier: 0.0333 (0.1210) loss_box_reg: 0.0266 (0.0376) loss_mask: 0.0001 (0.0522) loss_objectness: 0.0179 (0.0908) loss_rpn_box_reg: 0.1064 (0.1250) time: 0.8550 data: 0.0023 max mem: 8508
  290. Epoch: [0] [ 460/2000] eta: 0:22:46 lr: 0.002308 loss: 0.1864 (0.4212) loss_classifier: 0.0323 (0.1191) loss_box_reg: 0.0259 (0.0373) loss_mask: 0.0001 (0.0510) loss_objectness: 0.0183 (0.0893) loss_rpn_box_reg: 0.1036 (0.1245) time: 0.8542 data: 0.0024 max mem: 8508
  291. Epoch: [0] [ 470/2000] eta: 0:22:36 lr: 0.002358 loss: 0.1673 (0.4157) loss_classifier: 0.0326 (0.1172) loss_box_reg: 0.0259 (0.0371) loss_mask: 0.0000 (0.0500) loss_objectness: 0.0174 (0.0877) loss_rpn_box_reg: 0.0915 (0.1237) time: 0.8550 data: 0.0031 max mem: 8508
  292. Epoch: [0] [ 480/2000] eta: 0:22:26 lr: 0.002408 loss: 0.1609 (0.4104) loss_classifier: 0.0308 (0.1154) loss_box_reg: 0.0244 (0.0368) loss_mask: 0.0000 (0.0489) loss_objectness: 0.0159 (0.0862) loss_rpn_box_reg: 0.0890 (0.1230) time: 0.8558 data: 0.0039 max mem: 8508
  293. Epoch: [0] [ 490/2000] eta: 0:22:16 lr: 0.002458 loss: 0.1574 (0.4052) loss_classifier: 0.0303 (0.1137) loss_box_reg: 0.0230 (0.0365) loss_mask: 0.0000 (0.0479) loss_objectness: 0.0149 (0.0848) loss_rpn_box_reg: 0.0880 (0.1223) time: 0.8550 data: 0.0039 max mem: 8508
  294. Epoch: [0] [ 500/2000] eta: 0:22:06 lr: 0.002507 loss: 0.1543 (0.4003) loss_classifier: 0.0293 (0.1120) loss_box_reg: 0.0220 (0.0362) loss_mask: 0.0000 (0.0470) loss_objectness: 0.0154 (0.0834) loss_rpn_box_reg: 0.0892 (0.1218) time: 0.8551 data: 0.0031 max mem: 8508
  295. Epoch: [0] [ 510/2000] eta: 0:21:57 lr: 0.002557 loss: 0.1543 (0.3956) loss_classifier: 0.0281 (0.1104) loss_box_reg: 0.0198 (0.0359) loss_mask: 0.0000 (0.0461) loss_objectness: 0.0170 (0.0821) loss_rpn_box_reg: 0.0899 (0.1212) time: 0.8563 data: 0.0031 max mem: 8508
  296. Epoch: [0] [ 520/2000] eta: 0:21:47 lr: 0.002607 loss: 0.1643 (0.3915) loss_classifier: 0.0261 (0.1088) loss_box_reg: 0.0199 (0.0356) loss_mask: 0.0000 (0.0452) loss_objectness: 0.0166 (0.0809) loss_rpn_box_reg: 0.0953 (0.1211) time: 0.8563 data: 0.0046 max mem: 8508
  297. Epoch: [0] [ 530/2000] eta: 0:21:37 lr: 0.002657 loss: 0.1893 (0.3886) loss_classifier: 0.0285 (0.1073) loss_box_reg: 0.0220 (0.0354) loss_mask: 0.0000 (0.0443) loss_objectness: 0.0168 (0.0797) loss_rpn_box_reg: 0.1200 (0.1219) time: 0.8551 data: 0.0031 max mem: 8508
  298. Epoch: [0] [ 540/2000] eta: 0:21:28 lr: 0.002707 loss: 0.2481 (0.3860) loss_classifier: 0.0356 (0.1061) loss_box_reg: 0.0283 (0.0354) loss_mask: 0.0001 (0.0435) loss_objectness: 0.0185 (0.0786) loss_rpn_box_reg: 0.1673 (0.1225) time: 0.8551 data: 0.0016 max mem: 8508
  299. Epoch: [0] [ 550/2000] eta: 0:21:18 lr: 0.002757 loss: 0.2174 (0.3827) loss_classifier: 0.0349 (0.1048) loss_box_reg: 0.0330 (0.0353) loss_mask: 0.0002 (0.0427) loss_objectness: 0.0185 (0.0775) loss_rpn_box_reg: 0.1338 (0.1224) time: 0.8558 data: 0.0016 max mem: 8508
  300. Epoch: [0] [ 560/2000] eta: 0:21:09 lr: 0.002807 loss: 0.1789 (0.3789) loss_classifier: 0.0326 (0.1035) loss_box_reg: 0.0259 (0.0351) loss_mask: 0.0001 (0.0420) loss_objectness: 0.0163 (0.0764) loss_rpn_box_reg: 0.1044 (0.1220) time: 0.8550 data: 0.0016 max mem: 8508
  301. Epoch: [0] [ 570/2000] eta: 0:20:59 lr: 0.002857 loss: 0.1647 (0.3751) loss_classifier: 0.0302 (0.1022) loss_box_reg: 0.0242 (0.0349) loss_mask: 0.0000 (0.0412) loss_objectness: 0.0141 (0.0754) loss_rpn_box_reg: 0.0929 (0.1214) time: 0.8558 data: 0.0023 max mem: 8508
  302. Epoch: [0] [ 580/2000] eta: 0:20:50 lr: 0.002907 loss: 0.1572 (0.3713) loss_classifier: 0.0281 (0.1009) loss_box_reg: 0.0232 (0.0347) loss_mask: 0.0000 (0.0405) loss_objectness: 0.0144 (0.0743) loss_rpn_box_reg: 0.0907 (0.1209) time: 0.8566 data: 0.0023 max mem: 8508
  303. Epoch: [0] [ 590/2000] eta: 0:20:41 lr: 0.002957 loss: 0.1516 (0.3676) loss_classifier: 0.0265 (0.0996) loss_box_reg: 0.0214 (0.0345) loss_mask: 0.0000 (0.0398) loss_objectness: 0.0137 (0.0733) loss_rpn_box_reg: 0.0880 (0.1203) time: 0.8566 data: 0.0039 max mem: 8508
  304. Epoch: [0] [ 600/2000] eta: 0:20:31 lr: 0.003007 loss: 0.1456 (0.3638) loss_classifier: 0.0239 (0.0983) loss_box_reg: 0.0192 (0.0342) loss_mask: 0.0000 (0.0392) loss_objectness: 0.0137 (0.0723) loss_rpn_box_reg: 0.0876 (0.1198) time: 0.8566 data: 0.0031 max mem: 8508
  305. Epoch: [0] [ 610/2000] eta: 0:20:22 lr: 0.003057 loss: 0.1413 (0.3602) loss_classifier: 0.0230 (0.0971) loss_box_reg: 0.0162 (0.0339) loss_mask: 0.0000 (0.0385) loss_objectness: 0.0126 (0.0713) loss_rpn_box_reg: 0.0877 (0.1193) time: 0.8558 data: 0.0023 max mem: 8508
  306. Epoch: [0] [ 620/2000] eta: 0:20:13 lr: 0.003107 loss: 0.1416 (0.3567) loss_classifier: 0.0231 (0.0959) loss_box_reg: 0.0152 (0.0336) loss_mask: 0.0000 (0.0379) loss_objectness: 0.0136 (0.0704) loss_rpn_box_reg: 0.0890 (0.1188) time: 0.8566 data: 0.0039 max mem: 8508
  307. Epoch: [0] [ 630/2000] eta: 0:20:03 lr: 0.003157 loss: 0.1383 (0.3532) loss_classifier: 0.0228 (0.0948) loss_box_reg: 0.0152 (0.0333) loss_mask: 0.0000 (0.0373) loss_objectness: 0.0107 (0.0695) loss_rpn_box_reg: 0.0879 (0.1183) time: 0.8566 data: 0.0023 max mem: 8508
  308. Epoch: [0] [ 640/2000] eta: 0:19:54 lr: 0.003207 loss: 0.1346 (0.3498) loss_classifier: 0.0216 (0.0936) loss_box_reg: 0.0138 (0.0330) loss_mask: 0.0000 (0.0367) loss_objectness: 0.0097 (0.0686) loss_rpn_box_reg: 0.0870 (0.1179) time: 0.8558 data: 0.0016 max mem: 8508
  309. Epoch: [0] [ 650/2000] eta: 0:19:45 lr: 0.003257 loss: 0.1403 (0.3470) loss_classifier: 0.0214 (0.0926) loss_box_reg: 0.0138 (0.0328) loss_mask: 0.0000 (0.0362) loss_objectness: 0.0118 (0.0677) loss_rpn_box_reg: 0.0899 (0.1178) time: 0.8551 data: 0.0031 max mem: 8508
  310. Epoch: [0] [ 660/2000] eta: 0:19:35 lr: 0.003307 loss: 0.1739 (0.3446) loss_classifier: 0.0332 (0.0917) loss_box_reg: 0.0257 (0.0328) loss_mask: 0.0000 (0.0356) loss_objectness: 0.0165 (0.0670) loss_rpn_box_reg: 0.0969 (0.1175) time: 0.8543 data: 0.0030 max mem: 8508
  311. Epoch: [0] [ 670/2000] eta: 0:19:26 lr: 0.003357 loss: 0.1745 (0.3421) loss_classifier: 0.0305 (0.0908) loss_box_reg: 0.0257 (0.0326) loss_mask: 0.0001 (0.0351) loss_objectness: 0.0172 (0.0662) loss_rpn_box_reg: 0.0969 (0.1174) time: 0.8542 data: 0.0030 max mem: 8508
  312. Epoch: [0] [ 680/2000] eta: 0:19:17 lr: 0.003407 loss: 0.1609 (0.3395) loss_classifier: 0.0262 (0.0898) loss_box_reg: 0.0220 (0.0325) loss_mask: 0.0000 (0.0346) loss_objectness: 0.0146 (0.0655) loss_rpn_box_reg: 0.0995 (0.1171) time: 0.8542 data: 0.0031 max mem: 8508
  313. Epoch: [0] [ 690/2000] eta: 0:19:08 lr: 0.003457 loss: 0.1632 (0.3371) loss_classifier: 0.0261 (0.0889) loss_box_reg: 0.0214 (0.0323) loss_mask: 0.0000 (0.0341) loss_objectness: 0.0162 (0.0648) loss_rpn_box_reg: 0.0995 (0.1171) time: 0.8543 data: 0.0023 max mem: 8508
  314. Epoch: [0] [ 700/2000] eta: 0:18:59 lr: 0.003506 loss: 0.1840 (0.3351) loss_classifier: 0.0263 (0.0880) loss_box_reg: 0.0208 (0.0322) loss_mask: 0.0001 (0.0336) loss_objectness: 0.0180 (0.0641) loss_rpn_box_reg: 0.1152 (0.1172) time: 0.8536 data: 0.0023 max mem: 8508
  315. Epoch: [0] [ 710/2000] eta: 0:18:49 lr: 0.003556 loss: 0.1852 (0.3329) loss_classifier: 0.0297 (0.0873) loss_box_reg: 0.0236 (0.0320) loss_mask: 0.0001 (0.0331) loss_objectness: 0.0174 (0.0635) loss_rpn_box_reg: 0.1152 (0.1170) time: 0.8543 data: 0.0039 max mem: 8508
  316. Epoch: [0] [ 720/2000] eta: 0:18:40 lr: 0.003606 loss: 0.1636 (0.3305) loss_classifier: 0.0299 (0.0865) loss_box_reg: 0.0224 (0.0319) loss_mask: 0.0000 (0.0327) loss_objectness: 0.0168 (0.0628) loss_rpn_box_reg: 0.0924 (0.1167) time: 0.8558 data: 0.0031 max mem: 8508
  317. Epoch: [0] [ 730/2000] eta: 0:18:31 lr: 0.003656 loss: 0.1530 (0.3280) loss_classifier: 0.0271 (0.0856) loss_box_reg: 0.0200 (0.0317) loss_mask: 0.0000 (0.0322) loss_objectness: 0.0156 (0.0622) loss_rpn_box_reg: 0.0881 (0.1163) time: 0.8543 data: 0.0016 max mem: 8508
  318. Epoch: [0] [ 740/2000] eta: 0:18:22 lr: 0.003706 loss: 0.1453 (0.3255) loss_classifier: 0.0268 (0.0848) loss_box_reg: 0.0174 (0.0315) loss_mask: 0.0000 (0.0318) loss_objectness: 0.0127 (0.0615) loss_rpn_box_reg: 0.0871 (0.1159) time: 0.8535 data: 0.0015 max mem: 8508
  319. Epoch: [0] [ 750/2000] eta: 0:18:13 lr: 0.003756 loss: 0.1435 (0.3231) loss_classifier: 0.0244 (0.0840) loss_box_reg: 0.0174 (0.0313) loss_mask: 0.0000 (0.0314) loss_objectness: 0.0129 (0.0608) loss_rpn_box_reg: 0.0864 (0.1155) time: 0.8550 data: 0.0023 max mem: 8508
  320. Epoch: [0] [ 760/2000] eta: 0:18:04 lr: 0.003806 loss: 0.1422 (0.3207) loss_classifier: 0.0223 (0.0832) loss_box_reg: 0.0157 (0.0311) loss_mask: 0.0000 (0.0310) loss_objectness: 0.0103 (0.0602) loss_rpn_box_reg: 0.0880 (0.1152) time: 0.8551 data: 0.0023 max mem: 8508
  321. Epoch: [0] [ 770/2000] eta: 0:17:55 lr: 0.003856 loss: 0.1430 (0.3185) loss_classifier: 0.0213 (0.0824) loss_box_reg: 0.0141 (0.0309) loss_mask: 0.0000 (0.0306) loss_objectness: 0.0100 (0.0596) loss_rpn_box_reg: 0.0931 (0.1150) time: 0.8551 data: 0.0016 max mem: 8508
  322. Epoch: [0] [ 780/2000] eta: 0:17:46 lr: 0.003906 loss: 0.1539 (0.3165) loss_classifier: 0.0213 (0.0816) loss_box_reg: 0.0152 (0.0307) loss_mask: 0.0001 (0.0302) loss_objectness: 0.0117 (0.0589) loss_rpn_box_reg: 0.1026 (0.1150) time: 0.8550 data: 0.0023 max mem: 8508
  323. Epoch: [0] [ 790/2000] eta: 0:17:37 lr: 0.003956 loss: 0.1577 (0.3145) loss_classifier: 0.0226 (0.0809) loss_box_reg: 0.0152 (0.0305) loss_mask: 0.0001 (0.0299) loss_objectness: 0.0134 (0.0584) loss_rpn_box_reg: 0.1035 (0.1148) time: 0.8534 data: 0.0031 max mem: 8508
  324. Epoch: [0] [ 800/2000] eta: 0:17:28 lr: 0.004006 loss: 0.1409 (0.3122) loss_classifier: 0.0220 (0.0801) loss_box_reg: 0.0133 (0.0303) loss_mask: 0.0001 (0.0295) loss_objectness: 0.0120 (0.0578) loss_rpn_box_reg: 0.0983 (0.1145) time: 0.8526 data: 0.0039 max mem: 8508
  325. Epoch: [0] [ 810/2000] eta: 0:17:19 lr: 0.004056 loss: 0.1351 (0.3101) loss_classifier: 0.0173 (0.0794) loss_box_reg: 0.0104 (0.0300) loss_mask: 0.0000 (0.0291) loss_objectness: 0.0107 (0.0572) loss_rpn_box_reg: 0.0927 (0.1143) time: 0.8519 data: 0.0046 max mem: 8508
  326. Epoch: [0] [ 820/2000] eta: 0:17:10 lr: 0.004106 loss: 0.1350 (0.3080) loss_classifier: 0.0168 (0.0786) loss_box_reg: 0.0096 (0.0298) loss_mask: 0.0000 (0.0288) loss_objectness: 0.0118 (0.0567) loss_rpn_box_reg: 0.0953 (0.1142) time: 0.8512 data: 0.0039 max mem: 8508
  327. Epoch: [0] [ 830/2000] eta: 0:17:01 lr: 0.004156 loss: 0.1361 (0.3060) loss_classifier: 0.0170 (0.0779) loss_box_reg: 0.0095 (0.0296) loss_mask: 0.0000 (0.0284) loss_objectness: 0.0124 (0.0561) loss_rpn_box_reg: 0.0976 (0.1140) time: 0.8512 data: 0.0015 max mem: 8508
  328. Epoch: [0] [ 840/2000] eta: 0:16:52 lr: 0.004206 loss: 0.1354 (0.3039) loss_classifier: 0.0174 (0.0772) loss_box_reg: 0.0107 (0.0293) loss_mask: 0.0000 (0.0281) loss_objectness: 0.0114 (0.0556) loss_rpn_box_reg: 0.0929 (0.1137) time: 0.8512 data: 0.0015 max mem: 8508
  329. Epoch: [0] [ 850/2000] eta: 0:16:43 lr: 0.004256 loss: 0.1260 (0.3018) loss_classifier: 0.0176 (0.0765) loss_box_reg: 0.0103 (0.0291) loss_mask: 0.0000 (0.0278) loss_objectness: 0.0103 (0.0551) loss_rpn_box_reg: 0.0879 (0.1134) time: 0.8512 data: 0.0031 max mem: 8508
  330. Epoch: [0] [ 860/2000] eta: 0:16:33 lr: 0.004306 loss: 0.1194 (0.2997) loss_classifier: 0.0159 (0.0758) loss_box_reg: 0.0075 (0.0288) loss_mask: 0.0000 (0.0274) loss_objectness: 0.0092 (0.0546) loss_rpn_box_reg: 0.0862 (0.1131) time: 0.8504 data: 0.0038 max mem: 8508
  331. Epoch: [0] [ 870/2000] eta: 0:16:24 lr: 0.004356 loss: 0.1184 (0.2976) loss_classifier: 0.0144 (0.0750) loss_box_reg: 0.0050 (0.0286) loss_mask: 0.0000 (0.0271) loss_objectness: 0.0111 (0.0540) loss_rpn_box_reg: 0.0860 (0.1128) time: 0.8495 data: 0.0031 max mem: 8508
  332. Epoch: [0] [ 880/2000] eta: 0:16:15 lr: 0.004406 loss: 0.1154 (0.2955) loss_classifier: 0.0138 (0.0743) loss_box_reg: 0.0038 (0.0283) loss_mask: 0.0000 (0.0268) loss_objectness: 0.0091 (0.0535) loss_rpn_box_reg: 0.0863 (0.1125) time: 0.8496 data: 0.0023 max mem: 8508
  333. Epoch: [0] [ 890/2000] eta: 0:16:07 lr: 0.004456 loss: 0.1255 (0.2940) loss_classifier: 0.0138 (0.0738) loss_box_reg: 0.0048 (0.0281) loss_mask: 0.0001 (0.0265) loss_objectness: 0.0102 (0.0531) loss_rpn_box_reg: 0.0896 (0.1125) time: 0.8512 data: 0.0031 max mem: 8508
  334. Epoch: [0] [ 900/2000] eta: 0:15:58 lr: 0.004505 loss: 0.1602 (0.2925) loss_classifier: 0.0246 (0.0732) loss_box_reg: 0.0153 (0.0280) loss_mask: 0.0001 (0.0262) loss_objectness: 0.0133 (0.0527) loss_rpn_box_reg: 0.1061 (0.1124) time: 0.8528 data: 0.0031 max mem: 8508
  335. Epoch: [0] [ 910/2000] eta: 0:15:49 lr: 0.004555 loss: 0.1551 (0.2909) loss_classifier: 0.0229 (0.0726) loss_box_reg: 0.0121 (0.0278) loss_mask: 0.0001 (0.0260) loss_objectness: 0.0143 (0.0523) loss_rpn_box_reg: 0.1006 (0.1123) time: 0.8527 data: 0.0039 max mem: 8508
  336. Epoch: [0] [ 920/2000] eta: 0:15:40 lr: 0.004605 loss: 0.1385 (0.2893) loss_classifier: 0.0203 (0.0721) loss_box_reg: 0.0101 (0.0276) loss_mask: 0.0001 (0.0257) loss_objectness: 0.0127 (0.0518) loss_rpn_box_reg: 0.0943 (0.1121) time: 0.8534 data: 0.0039 max mem: 8508
  337. Epoch: [0] [ 930/2000] eta: 0:15:31 lr: 0.004655 loss: 0.1354 (0.2876) loss_classifier: 0.0205 (0.0715) loss_box_reg: 0.0084 (0.0274) loss_mask: 0.0000 (0.0254) loss_objectness: 0.0125 (0.0514) loss_rpn_box_reg: 0.0916 (0.1119) time: 0.8542 data: 0.0031 max mem: 8508
  338. Epoch: [0] [ 940/2000] eta: 0:15:22 lr: 0.004705 loss: 0.1294 (0.2859) loss_classifier: 0.0206 (0.0710) loss_box_reg: 0.0072 (0.0272) loss_mask: 0.0000 (0.0251) loss_objectness: 0.0097 (0.0509) loss_rpn_box_reg: 0.0871 (0.1116) time: 0.8534 data: 0.0023 max mem: 8508
  339. Epoch: [0] [ 950/2000] eta: 0:15:13 lr: 0.004755 loss: 0.1264 (0.2842) loss_classifier: 0.0212 (0.0705) loss_box_reg: 0.0065 (0.0269) loss_mask: 0.0000 (0.0249) loss_objectness: 0.0099 (0.0505) loss_rpn_box_reg: 0.0863 (0.1114) time: 0.8527 data: 0.0015 max mem: 8508
  340. Epoch: [0] [ 960/2000] eta: 0:15:04 lr: 0.004805 loss: 0.1271 (0.2826) loss_classifier: 0.0232 (0.0700) loss_box_reg: 0.0062 (0.0267) loss_mask: 0.0000 (0.0246) loss_objectness: 0.0084 (0.0501) loss_rpn_box_reg: 0.0860 (0.1111) time: 0.8527 data: 0.0015 max mem: 8508
  341. Epoch: [0] [ 970/2000] eta: 0:14:55 lr: 0.004855 loss: 0.1293 (0.2810) loss_classifier: 0.0237 (0.0695) loss_box_reg: 0.0059 (0.0265) loss_mask: 0.0000 (0.0244) loss_objectness: 0.0072 (0.0497) loss_rpn_box_reg: 0.0860 (0.1109) time: 0.8536 data: 0.0023 max mem: 8508
  342. Epoch: [0] [ 980/2000] eta: 0:14:46 lr: 0.004905 loss: 0.1352 (0.2797) loss_classifier: 0.0221 (0.0690) loss_box_reg: 0.0090 (0.0264) loss_mask: 0.0000 (0.0241) loss_objectness: 0.0088 (0.0493) loss_rpn_box_reg: 0.0942 (0.1109) time: 0.8535 data: 0.0015 max mem: 8508
  343. Epoch: [0] [ 990/2000] eta: 0:14:38 lr: 0.004955 loss: 0.1382 (0.2783) loss_classifier: 0.0195 (0.0685) loss_box_reg: 0.0092 (0.0262) loss_mask: 0.0000 (0.0239) loss_objectness: 0.0101 (0.0489) loss_rpn_box_reg: 0.0983 (0.1108) time: 0.8519 data: 0.0008 max mem: 8508
  344. Epoch: [0] [1000/2000] eta: 0:14:29 lr: 0.005000 loss: 0.1293 (0.2767) loss_classifier: 0.0181 (0.0680) loss_box_reg: 0.0079 (0.0260) loss_mask: 0.0000 (0.0237) loss_objectness: 0.0101 (0.0485) loss_rpn_box_reg: 0.0911 (0.1106) time: 0.8512 data: 0.0015 max mem: 8508
  345. Epoch: [0] [1010/2000] eta: 0:14:20 lr: 0.005000 loss: 0.1271 (0.2753) loss_classifier: 0.0182 (0.0675) loss_box_reg: 0.0078 (0.0259) loss_mask: 0.0000 (0.0234) loss_objectness: 0.0079 (0.0481) loss_rpn_box_reg: 0.0894 (0.1104) time: 0.8518 data: 0.0023 max mem: 8508
  346. Epoch: [0] [1020/2000] eta: 0:14:11 lr: 0.005000 loss: 0.1271 (0.2738) loss_classifier: 0.0200 (0.0671) loss_box_reg: 0.0081 (0.0257) loss_mask: 0.0000 (0.0232) loss_objectness: 0.0079 (0.0477) loss_rpn_box_reg: 0.0865 (0.1101) time: 0.8526 data: 0.0031 max mem: 8508
  347. Epoch: [0] [1030/2000] eta: 0:14:02 lr: 0.005000 loss: 0.1205 (0.2723) loss_classifier: 0.0200 (0.0666) loss_box_reg: 0.0078 (0.0255) loss_mask: 0.0000 (0.0230) loss_objectness: 0.0092 (0.0473) loss_rpn_box_reg: 0.0850 (0.1099) time: 0.8512 data: 0.0032 max mem: 8508
  348. Epoch: [0] [1040/2000] eta: 0:13:53 lr: 0.005000 loss: 0.1249 (0.2709) loss_classifier: 0.0190 (0.0662) loss_box_reg: 0.0072 (0.0253) loss_mask: 0.0000 (0.0227) loss_objectness: 0.0092 (0.0470) loss_rpn_box_reg: 0.0854 (0.1097) time: 0.8511 data: 0.0039 max mem: 8508
  349. Epoch: [0] [1050/2000] eta: 0:13:44 lr: 0.005000 loss: 0.1275 (0.2695) loss_classifier: 0.0172 (0.0657) loss_box_reg: 0.0072 (0.0252) loss_mask: 0.0000 (0.0225) loss_objectness: 0.0091 (0.0466) loss_rpn_box_reg: 0.0899 (0.1095) time: 0.8510 data: 0.0031 max mem: 8508
  350. Epoch: [0] [1060/2000] eta: 0:13:36 lr: 0.005000 loss: 0.1173 (0.2681) loss_classifier: 0.0165 (0.0652) loss_box_reg: 0.0066 (0.0250) loss_mask: 0.0000 (0.0223) loss_objectness: 0.0075 (0.0462) loss_rpn_box_reg: 0.0851 (0.1093) time: 0.8495 data: 0.0015 max mem: 8508
  351. Epoch: [0] [1070/2000] eta: 0:13:27 lr: 0.005000 loss: 0.1101 (0.2666) loss_classifier: 0.0152 (0.0648) loss_box_reg: 0.0059 (0.0248) loss_mask: 0.0000 (0.0221) loss_objectness: 0.0077 (0.0459) loss_rpn_box_reg: 0.0806 (0.1090) time: 0.8494 data: 0.0015 max mem: 8508
  352. Epoch: [0] [1080/2000] eta: 0:13:18 lr: 0.005000 loss: 0.1095 (0.2651) loss_classifier: 0.0157 (0.0643) loss_box_reg: 0.0055 (0.0246) loss_mask: 0.0000 (0.0219) loss_objectness: 0.0077 (0.0455) loss_rpn_box_reg: 0.0792 (0.1087) time: 0.8495 data: 0.0031 max mem: 8508
  353. Epoch: [0] [1090/2000] eta: 0:13:09 lr: 0.005000 loss: 0.1084 (0.2637) loss_classifier: 0.0162 (0.0639) loss_box_reg: 0.0056 (0.0245) loss_mask: 0.0000 (0.0217) loss_objectness: 0.0069 (0.0452) loss_rpn_box_reg: 0.0783 (0.1084) time: 0.8503 data: 0.0031 max mem: 8508
  354. Epoch: [0] [1100/2000] eta: 0:13:00 lr: 0.005000 loss: 0.1099 (0.2623) loss_classifier: 0.0161 (0.0634) loss_box_reg: 0.0059 (0.0243) loss_mask: 0.0000 (0.0215) loss_objectness: 0.0076 (0.0449) loss_rpn_box_reg: 0.0787 (0.1082) time: 0.8503 data: 0.0016 max mem: 8508
  355. Epoch: [0] [1110/2000] eta: 0:12:51 lr: 0.005000 loss: 0.1127 (0.2611) loss_classifier: 0.0144 (0.0630) loss_box_reg: 0.0051 (0.0241) loss_mask: 0.0000 (0.0215) loss_objectness: 0.0073 (0.0445) loss_rpn_box_reg: 0.0812 (0.1080) time: 0.8495 data: 0.0016 max mem: 8508
  356. Epoch: [0] [1120/2000] eta: 0:12:43 lr: 0.005000 loss: 0.1127 (0.2598) loss_classifier: 0.0149 (0.0626) loss_box_reg: 0.0043 (0.0240) loss_mask: 0.0003 (0.0213) loss_objectness: 0.0092 (0.0442) loss_rpn_box_reg: 0.0802 (0.1077) time: 0.8495 data: 0.0016 max mem: 8508
  357. Epoch: [0] [1130/2000] eta: 0:12:34 lr: 0.005000 loss: 0.1091 (0.2584) loss_classifier: 0.0155 (0.0622) loss_box_reg: 0.0033 (0.0238) loss_mask: 0.0001 (0.0211) loss_objectness: 0.0092 (0.0439) loss_rpn_box_reg: 0.0792 (0.1075) time: 0.8495 data: 0.0023 max mem: 8508
  358. Epoch: [0] [1140/2000] eta: 0:12:25 lr: 0.005000 loss: 0.1029 (0.2571) loss_classifier: 0.0150 (0.0618) loss_box_reg: 0.0028 (0.0236) loss_mask: 0.0000 (0.0209) loss_objectness: 0.0055 (0.0436) loss_rpn_box_reg: 0.0786 (0.1072) time: 0.8495 data: 0.0023 max mem: 8508
  359. Epoch: [0] [1150/2000] eta: 0:12:16 lr: 0.005000 loss: 0.1031 (0.2557) loss_classifier: 0.0157 (0.0614) loss_box_reg: 0.0032 (0.0234) loss_mask: 0.0000 (0.0207) loss_objectness: 0.0053 (0.0433) loss_rpn_box_reg: 0.0785 (0.1070) time: 0.8495 data: 0.0008 max mem: 8508
  360. Epoch: [0] [1160/2000] eta: 0:12:07 lr: 0.005000 loss: 0.1021 (0.2544) loss_classifier: 0.0150 (0.0610) loss_box_reg: 0.0032 (0.0232) loss_mask: 0.0000 (0.0205) loss_objectness: 0.0051 (0.0429) loss_rpn_box_reg: 0.0785 (0.1067) time: 0.8495 data: 0.0016 max mem: 8508
  361. Epoch: [0] [1170/2000] eta: 0:11:59 lr: 0.005000 loss: 0.1030 (0.2532) loss_classifier: 0.0147 (0.0606) loss_box_reg: 0.0030 (0.0231) loss_mask: 0.0000 (0.0204) loss_objectness: 0.0074 (0.0426) loss_rpn_box_reg: 0.0784 (0.1065) time: 0.8503 data: 0.0023 max mem: 8508
  362. Epoch: [0] [1180/2000] eta: 0:11:50 lr: 0.005000 loss: 0.1055 (0.2519) loss_classifier: 0.0153 (0.0602) loss_box_reg: 0.0030 (0.0229) loss_mask: 0.0000 (0.0202) loss_objectness: 0.0074 (0.0423) loss_rpn_box_reg: 0.0783 (0.1063) time: 0.8495 data: 0.0023 max mem: 8508
  363. Epoch: [0] [1190/2000] eta: 0:11:41 lr: 0.005000 loss: 0.1063 (0.2507) loss_classifier: 0.0149 (0.0598) loss_box_reg: 0.0030 (0.0228) loss_mask: 0.0000 (0.0200) loss_objectness: 0.0074 (0.0421) loss_rpn_box_reg: 0.0782 (0.1060) time: 0.8495 data: 0.0031 max mem: 8508
  364. Epoch: [0] [1200/2000] eta: 0:11:32 lr: 0.005000 loss: 0.1046 (0.2495) loss_classifier: 0.0146 (0.0595) loss_box_reg: 0.0026 (0.0226) loss_mask: 0.0000 (0.0199) loss_objectness: 0.0081 (0.0418) loss_rpn_box_reg: 0.0784 (0.1058) time: 0.8495 data: 0.0031 max mem: 8508
  365. Epoch: [0] [1210/2000] eta: 0:11:24 lr: 0.005000 loss: 0.0987 (0.2482) loss_classifier: 0.0134 (0.0591) loss_box_reg: 0.0018 (0.0224) loss_mask: 0.0000 (0.0197) loss_objectness: 0.0057 (0.0415) loss_rpn_box_reg: 0.0781 (0.1056) time: 0.8487 data: 0.0031 max mem: 8508
  366. Epoch: [0] [1220/2000] eta: 0:11:15 lr: 0.005000 loss: 0.0985 (0.2470) loss_classifier: 0.0123 (0.0587) loss_box_reg: 0.0019 (0.0223) loss_mask: 0.0000 (0.0195) loss_objectness: 0.0059 (0.0412) loss_rpn_box_reg: 0.0781 (0.1054) time: 0.8495 data: 0.0038 max mem: 8508
  367. Epoch: [0] [1230/2000] eta: 0:11:06 lr: 0.005000 loss: 0.1041 (0.2459) loss_classifier: 0.0122 (0.0583) loss_box_reg: 0.0027 (0.0221) loss_mask: 0.0000 (0.0194) loss_objectness: 0.0066 (0.0409) loss_rpn_box_reg: 0.0786 (0.1052) time: 0.8496 data: 0.0046 max mem: 8508
  368. Epoch: [0] [1240/2000] eta: 0:10:57 lr: 0.005000 loss: 0.1060 (0.2448) loss_classifier: 0.0153 (0.0580) loss_box_reg: 0.0057 (0.0220) loss_mask: 0.0000 (0.0192) loss_objectness: 0.0067 (0.0406) loss_rpn_box_reg: 0.0783 (0.1049) time: 0.8496 data: 0.0039 max mem: 8508
  369. Epoch: [0] [1250/2000] eta: 0:10:49 lr: 0.005000 loss: 0.1098 (0.2437) loss_classifier: 0.0160 (0.0577) loss_box_reg: 0.0080 (0.0219) loss_mask: 0.0000 (0.0191) loss_objectness: 0.0066 (0.0404) loss_rpn_box_reg: 0.0782 (0.1047) time: 0.8502 data: 0.0015 max mem: 8508
  370. Epoch: [0] [1260/2000] eta: 0:10:40 lr: 0.005000 loss: 0.1069 (0.2426) loss_classifier: 0.0155 (0.0573) loss_box_reg: 0.0046 (0.0217) loss_mask: 0.0000 (0.0189) loss_objectness: 0.0074 (0.0401) loss_rpn_box_reg: 0.0780 (0.1045) time: 0.8495 data: 0.0023 max mem: 8508
  371. Epoch: [0] [1270/2000] eta: 0:10:31 lr: 0.005000 loss: 0.1045 (0.2415) loss_classifier: 0.0145 (0.0570) loss_box_reg: 0.0042 (0.0216) loss_mask: 0.0000 (0.0188) loss_objectness: 0.0068 (0.0399) loss_rpn_box_reg: 0.0778 (0.1043) time: 0.8487 data: 0.0031 max mem: 8508
  372. Epoch: [0] [1280/2000] eta: 0:10:22 lr: 0.005000 loss: 0.1085 (0.2444) loss_classifier: 0.0168 (0.0571) loss_box_reg: 0.0062 (0.0216) loss_mask: 0.0000 (0.0186) loss_objectness: 0.0066 (0.0423) loss_rpn_box_reg: 0.0779 (0.1047) time: 0.8495 data: 0.0015 max mem: 8508
  373. Epoch: [0] [1290/2000] eta: 0:10:14 lr: 0.005000 loss: 0.3095 (0.2457) loss_classifier: 0.0342 (0.0572) loss_box_reg: 0.0172 (0.0218) loss_mask: 0.0001 (0.0185) loss_objectness: 0.0303 (0.0425) loss_rpn_box_reg: 0.1920 (0.1057) time: 0.8503 data: 0.0023 max mem: 8508
  374. Epoch: [0] [1300/2000] eta: 0:10:05 lr: 0.005000 loss: 0.4288 (0.2487) loss_classifier: 0.0407 (0.0572) loss_box_reg: 0.0395 (0.0219) loss_mask: 0.0002 (0.0184) loss_objectness: 0.0302 (0.0424) loss_rpn_box_reg: 0.2869 (0.1088) time: 0.8472 data: 0.0038 max mem: 8508
  375. Epoch: [0] [1310/2000] eta: 0:09:56 lr: 0.005000 loss: 0.3875 (0.2498) loss_classifier: 0.0439 (0.0571) loss_box_reg: 0.0341 (0.0221) loss_mask: 0.0001 (0.0182) loss_objectness: 0.0302 (0.0426) loss_rpn_box_reg: 0.2903 (0.1099) time: 0.8457 data: 0.0038 max mem: 8508
  376. Epoch: [0] [1320/2000] eta: 0:09:47 lr: 0.005000 loss: 0.2804 (0.2499) loss_classifier: 0.0502 (0.0570) loss_box_reg: 0.0533 (0.0223) loss_mask: 0.0000 (0.0181) loss_objectness: 0.0273 (0.0424) loss_rpn_box_reg: 0.1550 (0.1100) time: 0.8518 data: 0.0031 max mem: 8508
  377. Epoch: [0] [1330/2000] eta: 0:09:39 lr: 0.005000 loss: 0.2482 (0.2499) loss_classifier: 0.0556 (0.0570) loss_box_reg: 0.0580 (0.0226) loss_mask: 0.0000 (0.0179) loss_objectness: 0.0234 (0.0423) loss_rpn_box_reg: 0.1145 (0.1100) time: 0.8565 data: 0.0023 max mem: 8508
  378. Epoch: [0] [1340/2000] eta: 0:09:30 lr: 0.005000 loss: 0.2391 (0.2498) loss_classifier: 0.0577 (0.0570) loss_box_reg: 0.0623 (0.0229) loss_mask: 0.0000 (0.0178) loss_objectness: 0.0242 (0.0421) loss_rpn_box_reg: 0.0925 (0.1098) time: 0.8572 data: 0.0023 max mem: 8508
  379. Epoch: [0] [1350/2000] eta: 0:09:21 lr: 0.005000 loss: 0.2333 (0.2496) loss_classifier: 0.0571 (0.0570) loss_box_reg: 0.0623 (0.0232) loss_mask: 0.0000 (0.0177) loss_objectness: 0.0242 (0.0420) loss_rpn_box_reg: 0.0880 (0.1097) time: 0.8581 data: 0.0023 max mem: 8508
  380. Epoch: [0] [1360/2000] eta: 0:09:13 lr: 0.005000 loss: 0.2304 (0.2495) loss_classifier: 0.0560 (0.0571) loss_box_reg: 0.0610 (0.0235) loss_mask: 0.0000 (0.0176) loss_objectness: 0.0218 (0.0419) loss_rpn_box_reg: 0.0865 (0.1095) time: 0.8558 data: 0.0023 max mem: 8508
  381. Epoch: [0] [1370/2000] eta: 0:09:04 lr: 0.005000 loss: 0.2243 (0.2493) loss_classifier: 0.0565 (0.0570) loss_box_reg: 0.0607 (0.0238) loss_mask: 0.0000 (0.0175) loss_objectness: 0.0196 (0.0417) loss_rpn_box_reg: 0.0860 (0.1093) time: 0.8542 data: 0.0031 max mem: 8508
  382. Epoch: [0] [1380/2000] eta: 0:08:55 lr: 0.005000 loss: 0.2213 (0.2491) loss_classifier: 0.0555 (0.0570) loss_box_reg: 0.0590 (0.0240) loss_mask: 0.0000 (0.0173) loss_objectness: 0.0192 (0.0415) loss_rpn_box_reg: 0.0859 (0.1091) time: 0.8535 data: 0.0031 max mem: 8508
  383. Epoch: [0] [1390/2000] eta: 0:08:47 lr: 0.005000 loss: 0.2119 (0.2488) loss_classifier: 0.0531 (0.0570) loss_box_reg: 0.0549 (0.0243) loss_mask: 0.0000 (0.0172) loss_objectness: 0.0169 (0.0413) loss_rpn_box_reg: 0.0865 (0.1090) time: 0.8510 data: 0.0031 max mem: 8508
  384. Epoch: [0] [1400/2000] eta: 0:08:38 lr: 0.005000 loss: 0.2107 (0.2486) loss_classifier: 0.0510 (0.0569) loss_box_reg: 0.0528 (0.0244) loss_mask: 0.0000 (0.0171) loss_objectness: 0.0175 (0.0412) loss_rpn_box_reg: 0.0889 (0.1089) time: 0.8510 data: 0.0031 max mem: 8508
  385. Epoch: [0] [1410/2000] eta: 0:08:29 lr: 0.005000 loss: 0.2131 (0.2484) loss_classifier: 0.0484 (0.0569) loss_box_reg: 0.0460 (0.0246) loss_mask: 0.0000 (0.0170) loss_objectness: 0.0198 (0.0411) loss_rpn_box_reg: 0.0894 (0.1089) time: 0.8503 data: 0.0023 max mem: 8508
  386. Epoch: [0] [1420/2000] eta: 0:08:20 lr: 0.005000 loss: 0.2402 (0.2484) loss_classifier: 0.0480 (0.0568) loss_box_reg: 0.0452 (0.0247) loss_mask: 0.0000 (0.0169) loss_objectness: 0.0236 (0.0410) loss_rpn_box_reg: 0.1132 (0.1090) time: 0.8503 data: 0.0038 max mem: 8508
  387. Epoch: [0] [1430/2000] eta: 0:08:12 lr: 0.005000 loss: 0.2316 (0.2482) loss_classifier: 0.0552 (0.0568) loss_box_reg: 0.0521 (0.0249) loss_mask: 0.0000 (0.0167) loss_objectness: 0.0210 (0.0408) loss_rpn_box_reg: 0.0959 (0.1089) time: 0.8527 data: 0.0031 max mem: 8508
  388. Epoch: [0] [1440/2000] eta: 0:08:03 lr: 0.005000 loss: 0.2133 (0.2479) loss_classifier: 0.0536 (0.0568) loss_box_reg: 0.0506 (0.0251) loss_mask: 0.0000 (0.0166) loss_objectness: 0.0174 (0.0406) loss_rpn_box_reg: 0.0916 (0.1088) time: 0.8535 data: 0.0015 max mem: 8508
  389. Epoch: [0] [1450/2000] eta: 0:07:54 lr: 0.005000 loss: 0.2004 (0.2476) loss_classifier: 0.0485 (0.0567) loss_box_reg: 0.0454 (0.0252) loss_mask: 0.0000 (0.0165) loss_objectness: 0.0174 (0.0405) loss_rpn_box_reg: 0.0881 (0.1086) time: 0.8527 data: 0.0023 max mem: 8508
  390. Epoch: [0] [1460/2000] eta: 0:07:46 lr: 0.005000 loss: 0.1971 (0.2473) loss_classifier: 0.0455 (0.0567) loss_box_reg: 0.0415 (0.0253) loss_mask: 0.0000 (0.0164) loss_objectness: 0.0186 (0.0403) loss_rpn_box_reg: 0.0871 (0.1085) time: 0.8519 data: 0.0023 max mem: 8508
  391. Epoch: [0] [1470/2000] eta: 0:07:37 lr: 0.005000 loss: 0.2001 (0.2469) loss_classifier: 0.0440 (0.0566) loss_box_reg: 0.0387 (0.0254) loss_mask: 0.0000 (0.0163) loss_objectness: 0.0186 (0.0402) loss_rpn_box_reg: 0.0914 (0.1085) time: 0.8512 data: 0.0031 max mem: 8508
  392. Epoch: [0] [1480/2000] eta: 0:07:28 lr: 0.005000 loss: 0.2043 (0.2467) loss_classifier: 0.0440 (0.0565) loss_box_reg: 0.0389 (0.0255) loss_mask: 0.0000 (0.0162) loss_objectness: 0.0164 (0.0400) loss_rpn_box_reg: 0.1033 (0.1085) time: 0.8527 data: 0.0023 max mem: 8508
  393. Epoch: [0] [1490/2000] eta: 0:07:20 lr: 0.005000 loss: 0.2039 (0.2465) loss_classifier: 0.0491 (0.0565) loss_box_reg: 0.0410 (0.0256) loss_mask: 0.0000 (0.0161) loss_objectness: 0.0158 (0.0399) loss_rpn_box_reg: 0.0965 (0.1084) time: 0.8534 data: 0.0015 max mem: 8508
  394. Epoch: [0] [1500/2000] eta: 0:07:11 lr: 0.005000 loss: 0.1976 (0.2461) loss_classifier: 0.0448 (0.0564) loss_box_reg: 0.0410 (0.0257) loss_mask: 0.0000 (0.0160) loss_objectness: 0.0163 (0.0398) loss_rpn_box_reg: 0.0890 (0.1082) time: 0.8519 data: 0.0039 max mem: 8508
  395. Epoch: [0] [1510/2000] eta: 0:07:02 lr: 0.005000 loss: 0.1874 (0.2457) loss_classifier: 0.0408 (0.0563) loss_box_reg: 0.0381 (0.0258) loss_mask: 0.0000 (0.0159) loss_objectness: 0.0170 (0.0396) loss_rpn_box_reg: 0.0874 (0.1081) time: 0.8511 data: 0.0039 max mem: 8508
  396. Epoch: [0] [1520/2000] eta: 0:06:54 lr: 0.005000 loss: 0.1755 (0.2452) loss_classifier: 0.0368 (0.0561) loss_box_reg: 0.0354 (0.0259) loss_mask: 0.0000 (0.0158) loss_objectness: 0.0151 (0.0395) loss_rpn_box_reg: 0.0878 (0.1080) time: 0.8511 data: 0.0015 max mem: 8508
  397. Epoch: [0] [1530/2000] eta: 0:06:45 lr: 0.005000 loss: 0.1776 (0.2448) loss_classifier: 0.0352 (0.0560) loss_box_reg: 0.0338 (0.0259) loss_mask: 0.0000 (0.0157) loss_objectness: 0.0145 (0.0393) loss_rpn_box_reg: 0.0899 (0.1079) time: 0.8512 data: 0.0015 max mem: 8508
  398. Epoch: [0] [1540/2000] eta: 0:06:36 lr: 0.005000 loss: 0.1813 (0.2444) loss_classifier: 0.0348 (0.0559) loss_box_reg: 0.0323 (0.0260) loss_mask: 0.0000 (0.0156) loss_objectness: 0.0177 (0.0392) loss_rpn_box_reg: 0.0913 (0.1078) time: 0.8528 data: 0.0031 max mem: 8508
  399. Epoch: [0] [1550/2000] eta: 0:06:28 lr: 0.005000 loss: 0.1810 (0.2440) loss_classifier: 0.0342 (0.0557) loss_box_reg: 0.0321 (0.0260) loss_mask: 0.0000 (0.0155) loss_objectness: 0.0183 (0.0390) loss_rpn_box_reg: 0.0911 (0.1077) time: 0.8535 data: 0.0023 max mem: 8508
  400. Epoch: [0] [1560/2000] eta: 0:06:19 lr: 0.005000 loss: 0.1776 (0.2436) loss_classifier: 0.0328 (0.0556) loss_box_reg: 0.0318 (0.0260) loss_mask: 0.0000 (0.0154) loss_objectness: 0.0177 (0.0389) loss_rpn_box_reg: 0.0941 (0.1077) time: 0.8542 data: 0.0015 max mem: 8508
  401. Epoch: [0] [1570/2000] eta: 0:06:10 lr: 0.005000 loss: 0.1773 (0.2431) loss_classifier: 0.0311 (0.0554) loss_box_reg: 0.0312 (0.0260) loss_mask: 0.0000 (0.0153) loss_objectness: 0.0165 (0.0388) loss_rpn_box_reg: 0.1001 (0.1076) time: 0.8550 data: 0.0031 max mem: 8508
  402. Epoch: [0] [1580/2000] eta: 0:06:02 lr: 0.005000 loss: 0.1757 (0.2427) loss_classifier: 0.0321 (0.0553) loss_box_reg: 0.0312 (0.0261) loss_mask: 0.0000 (0.0152) loss_objectness: 0.0172 (0.0386) loss_rpn_box_reg: 0.0909 (0.1075) time: 0.8543 data: 0.0039 max mem: 8508
  403. Epoch: [0] [1590/2000] eta: 0:05:53 lr: 0.005000 loss: 0.1700 (0.2422) loss_classifier: 0.0298 (0.0551) loss_box_reg: 0.0304 (0.0261) loss_mask: 0.0000 (0.0151) loss_objectness: 0.0177 (0.0385) loss_rpn_box_reg: 0.0878 (0.1074) time: 0.8550 data: 0.0039 max mem: 8508
  404. Epoch: [0] [1600/2000] eta: 0:05:45 lr: 0.005000 loss: 0.1597 (0.2417) loss_classifier: 0.0277 (0.0549) loss_box_reg: 0.0272 (0.0261) loss_mask: 0.0000 (0.0150) loss_objectness: 0.0176 (0.0384) loss_rpn_box_reg: 0.0871 (0.1073) time: 0.8550 data: 0.0016 max mem: 8508
  405. Epoch: [0] [1610/2000] eta: 0:05:36 lr: 0.005000 loss: 0.1591 (0.2412) loss_classifier: 0.0277 (0.0548) loss_box_reg: 0.0267 (0.0261) loss_mask: 0.0000 (0.0149) loss_objectness: 0.0176 (0.0383) loss_rpn_box_reg: 0.0865 (0.1071) time: 0.8558 data: 0.0015 max mem: 8508
  406. Epoch: [0] [1620/2000] eta: 0:05:27 lr: 0.005000 loss: 0.1599 (0.2407) loss_classifier: 0.0274 (0.0546) loss_box_reg: 0.0265 (0.0261) loss_mask: 0.0000 (0.0148) loss_objectness: 0.0175 (0.0381) loss_rpn_box_reg: 0.0869 (0.1070) time: 0.8551 data: 0.0023 max mem: 8508
  407. Epoch: [0] [1630/2000] eta: 0:05:19 lr: 0.005000 loss: 0.1748 (0.2406) loss_classifier: 0.0309 (0.0545) loss_box_reg: 0.0276 (0.0262) loss_mask: 0.0000 (0.0147) loss_objectness: 0.0177 (0.0380) loss_rpn_box_reg: 0.1001 (0.1071) time: 0.8527 data: 0.0023 max mem: 8508
  408. Epoch: [0] [1640/2000] eta: 0:05:10 lr: 0.005000 loss: 0.2237 (0.2405) loss_classifier: 0.0450 (0.0545) loss_box_reg: 0.0469 (0.0263) loss_mask: 0.0001 (0.0146) loss_objectness: 0.0214 (0.0379) loss_rpn_box_reg: 0.1090 (0.1072) time: 0.8535 data: 0.0031 max mem: 8508
  409. Epoch: [0] [1650/2000] eta: 0:05:01 lr: 0.005000 loss: 0.2115 (0.2403) loss_classifier: 0.0427 (0.0544) loss_box_reg: 0.0464 (0.0264) loss_mask: 0.0001 (0.0146) loss_objectness: 0.0214 (0.0378) loss_rpn_box_reg: 0.0942 (0.1071) time: 0.8543 data: 0.0023 max mem: 8508
  410. Epoch: [0] [1660/2000] eta: 0:04:53 lr: 0.005000 loss: 0.1825 (0.2399) loss_classifier: 0.0381 (0.0543) loss_box_reg: 0.0392 (0.0265) loss_mask: 0.0000 (0.0145) loss_objectness: 0.0175 (0.0377) loss_rpn_box_reg: 0.0874 (0.1070) time: 0.8542 data: 0.0015 max mem: 8508
  411. Epoch: [0] [1670/2000] eta: 0:04:44 lr: 0.005000 loss: 0.1707 (0.2395) loss_classifier: 0.0316 (0.0541) loss_box_reg: 0.0335 (0.0265) loss_mask: 0.0000 (0.0144) loss_objectness: 0.0166 (0.0376) loss_rpn_box_reg: 0.0866 (0.1068) time: 0.8549 data: 0.0023 max mem: 8508
  412. Epoch: [0] [1680/2000] eta: 0:04:35 lr: 0.005000 loss: 0.1638 (0.2390) loss_classifier: 0.0290 (0.0540) loss_box_reg: 0.0280 (0.0265) loss_mask: 0.0000 (0.0143) loss_objectness: 0.0167 (0.0374) loss_rpn_box_reg: 0.0866 (0.1068) time: 0.8542 data: 0.0023 max mem: 8508
  413. Epoch: [0] [1690/2000] eta: 0:04:27 lr: 0.005000 loss: 0.1639 (0.2387) loss_classifier: 0.0294 (0.0539) loss_box_reg: 0.0266 (0.0265) loss_mask: 0.0000 (0.0142) loss_objectness: 0.0195 (0.0374) loss_rpn_box_reg: 0.0949 (0.1068) time: 0.8529 data: 0.0023 max mem: 8508
  414. Epoch: [0] [1700/2000] eta: 0:04:18 lr: 0.005000 loss: 0.1981 (0.2385) loss_classifier: 0.0327 (0.0537) loss_box_reg: 0.0288 (0.0266) loss_mask: 0.0000 (0.0142) loss_objectness: 0.0207 (0.0373) loss_rpn_box_reg: 0.1050 (0.1068) time: 0.8543 data: 0.0015 max mem: 8508
  415. Epoch: [0] [1710/2000] eta: 0:04:09 lr: 0.005000 loss: 0.1830 (0.2381) loss_classifier: 0.0303 (0.0536) loss_box_reg: 0.0311 (0.0266) loss_mask: 0.0000 (0.0141) loss_objectness: 0.0198 (0.0372) loss_rpn_box_reg: 0.0954 (0.1067) time: 0.8550 data: 0.0023 max mem: 8508
  416. Epoch: [0] [1720/2000] eta: 0:04:01 lr: 0.005000 loss: 0.1646 (0.2377) loss_classifier: 0.0275 (0.0534) loss_box_reg: 0.0298 (0.0266) loss_mask: 0.0000 (0.0140) loss_objectness: 0.0179 (0.0370) loss_rpn_box_reg: 0.0887 (0.1066) time: 0.8536 data: 0.0031 max mem: 8508
  417. Epoch: [0] [1730/2000] eta: 0:03:52 lr: 0.005000 loss: 0.1552 (0.2372) loss_classifier: 0.0265 (0.0533) loss_box_reg: 0.0226 (0.0265) loss_mask: 0.0000 (0.0139) loss_objectness: 0.0177 (0.0369) loss_rpn_box_reg: 0.0870 (0.1065) time: 0.8521 data: 0.0023 max mem: 8508
  418. Epoch: [0] [1740/2000] eta: 0:03:44 lr: 0.005000 loss: 0.1550 (0.2368) loss_classifier: 0.0275 (0.0532) loss_box_reg: 0.0210 (0.0265) loss_mask: 0.0000 (0.0139) loss_objectness: 0.0169 (0.0368) loss_rpn_box_reg: 0.0868 (0.1064) time: 0.8519 data: 0.0031 max mem: 8508
  419. Epoch: [0] [1750/2000] eta: 0:03:35 lr: 0.005000 loss: 0.1523 (0.2363) loss_classifier: 0.0294 (0.0530) loss_box_reg: 0.0197 (0.0265) loss_mask: 0.0000 (0.0138) loss_objectness: 0.0152 (0.0367) loss_rpn_box_reg: 0.0866 (0.1063) time: 0.8535 data: 0.0023 max mem: 8508
  420. Epoch: [0] [1760/2000] eta: 0:03:26 lr: 0.005000 loss: 0.1508 (0.2358) loss_classifier: 0.0288 (0.0529) loss_box_reg: 0.0174 (0.0264) loss_mask: 0.0001 (0.0137) loss_objectness: 0.0167 (0.0366) loss_rpn_box_reg: 0.0863 (0.1062) time: 0.8535 data: 0.0015 max mem: 8508
  421. Epoch: [0] [1770/2000] eta: 0:03:18 lr: 0.005000 loss: 0.1504 (0.2353) loss_classifier: 0.0276 (0.0527) loss_box_reg: 0.0163 (0.0264) loss_mask: 0.0001 (0.0136) loss_objectness: 0.0181 (0.0365) loss_rpn_box_reg: 0.0859 (0.1061) time: 0.8534 data: 0.0015 max mem: 8508
  422. Epoch: [0] [1780/2000] eta: 0:03:09 lr: 0.005000 loss: 0.1482 (0.2348) loss_classifier: 0.0275 (0.0526) loss_box_reg: 0.0159 (0.0263) loss_mask: 0.0001 (0.0136) loss_objectness: 0.0164 (0.0364) loss_rpn_box_reg: 0.0866 (0.1060) time: 0.8534 data: 0.0023 max mem: 8508
  423. Epoch: [0] [1790/2000] eta: 0:03:00 lr: 0.005000 loss: 0.1461 (0.2343) loss_classifier: 0.0313 (0.0525) loss_box_reg: 0.0146 (0.0262) loss_mask: 0.0000 (0.0135) loss_objectness: 0.0131 (0.0362) loss_rpn_box_reg: 0.0870 (0.1059) time: 0.8534 data: 0.0015 max mem: 8508
  424. Epoch: [0] [1800/2000] eta: 0:02:52 lr: 0.005000 loss: 0.1445 (0.2338) loss_classifier: 0.0283 (0.0524) loss_box_reg: 0.0132 (0.0262) loss_mask: 0.0000 (0.0134) loss_objectness: 0.0118 (0.0361) loss_rpn_box_reg: 0.0880 (0.1058) time: 0.8542 data: 0.0023 max mem: 8508
  425. Epoch: [0] [1810/2000] eta: 0:02:43 lr: 0.005000 loss: 0.1413 (0.2333) loss_classifier: 0.0224 (0.0522) loss_box_reg: 0.0105 (0.0261) loss_mask: 0.0000 (0.0133) loss_objectness: 0.0144 (0.0360) loss_rpn_box_reg: 0.0914 (0.1057) time: 0.8527 data: 0.0046 max mem: 8508
  426. Epoch: [0] [1820/2000] eta: 0:02:35 lr: 0.005000 loss: 0.1342 (0.2327) loss_classifier: 0.0189 (0.0520) loss_box_reg: 0.0093 (0.0260) loss_mask: 0.0000 (0.0133) loss_objectness: 0.0156 (0.0359) loss_rpn_box_reg: 0.0868 (0.1056) time: 0.8520 data: 0.0031 max mem: 8508
  427. Epoch: [0] [1830/2000] eta: 0:02:26 lr: 0.005000 loss: 0.1349 (0.2322) loss_classifier: 0.0223 (0.0519) loss_box_reg: 0.0102 (0.0259) loss_mask: 0.0000 (0.0132) loss_objectness: 0.0148 (0.0358) loss_rpn_box_reg: 0.0860 (0.1055) time: 0.8512 data: 0.0023 max mem: 8508
  428. Epoch: [0] [1840/2000] eta: 0:02:17 lr: 0.005000 loss: 0.1386 (0.2317) loss_classifier: 0.0258 (0.0517) loss_box_reg: 0.0131 (0.0258) loss_mask: 0.0000 (0.0131) loss_objectness: 0.0141 (0.0357) loss_rpn_box_reg: 0.0859 (0.1054) time: 0.8519 data: 0.0031 max mem: 8508
  429. Epoch: [0] [1850/2000] eta: 0:02:09 lr: 0.005000 loss: 0.1381 (0.2312) loss_classifier: 0.0247 (0.0516) loss_box_reg: 0.0127 (0.0258) loss_mask: 0.0000 (0.0130) loss_objectness: 0.0120 (0.0355) loss_rpn_box_reg: 0.0865 (0.1053) time: 0.8534 data: 0.0031 max mem: 8508
  430. Epoch: [0] [1860/2000] eta: 0:02:00 lr: 0.005000 loss: 0.1384 (0.2307) loss_classifier: 0.0243 (0.0515) loss_box_reg: 0.0116 (0.0257) loss_mask: 0.0000 (0.0130) loss_objectness: 0.0117 (0.0354) loss_rpn_box_reg: 0.0883 (0.1052) time: 0.8519 data: 0.0031 max mem: 8508
  431. Epoch: [0] [1870/2000] eta: 0:01:51 lr: 0.005000 loss: 0.1409 (0.2303) loss_classifier: 0.0252 (0.0513) loss_box_reg: 0.0141 (0.0256) loss_mask: 0.0000 (0.0129) loss_objectness: 0.0131 (0.0353) loss_rpn_box_reg: 0.0870 (0.1051) time: 0.8519 data: 0.0031 max mem: 8508
  432. Epoch: [0] [1880/2000] eta: 0:01:43 lr: 0.005000 loss: 0.1446 (0.2298) loss_classifier: 0.0260 (0.0512) loss_box_reg: 0.0151 (0.0256) loss_mask: 0.0000 (0.0128) loss_objectness: 0.0131 (0.0352) loss_rpn_box_reg: 0.0872 (0.1050) time: 0.8527 data: 0.0031 max mem: 8508
  433. Epoch: [0] [1890/2000] eta: 0:01:34 lr: 0.005000 loss: 0.1485 (0.2294) loss_classifier: 0.0264 (0.0511) loss_box_reg: 0.0152 (0.0255) loss_mask: 0.0000 (0.0128) loss_objectness: 0.0163 (0.0351) loss_rpn_box_reg: 0.0913 (0.1050) time: 0.8527 data: 0.0023 max mem: 8508
  434. Epoch: [0] [1900/2000] eta: 0:01:26 lr: 0.005000 loss: 0.1483 (0.2290) loss_classifier: 0.0250 (0.0509) loss_box_reg: 0.0139 (0.0255) loss_mask: 0.0000 (0.0127) loss_objectness: 0.0180 (0.0350) loss_rpn_box_reg: 0.0913 (0.1049) time: 0.8526 data: 0.0015 max mem: 8508
  435. Epoch: [0] [1910/2000] eta: 0:01:17 lr: 0.005000 loss: 0.1445 (0.2286) loss_classifier: 0.0246 (0.0508) loss_box_reg: 0.0128 (0.0254) loss_mask: 0.0000 (0.0127) loss_objectness: 0.0137 (0.0349) loss_rpn_box_reg: 0.0880 (0.1048) time: 0.8527 data: 0.0015 max mem: 8508
  436. Epoch: [0] [1920/2000] eta: 0:01:08 lr: 0.005000 loss: 0.1449 (0.2281) loss_classifier: 0.0261 (0.0507) loss_box_reg: 0.0144 (0.0254) loss_mask: 0.0000 (0.0126) loss_objectness: 0.0137 (0.0348) loss_rpn_box_reg: 0.0861 (0.1047) time: 0.8519 data: 0.0031 max mem: 8508
  437. Epoch: [0] [1930/2000] eta: 0:01:00 lr: 0.005000 loss: 0.1453 (0.2277) loss_classifier: 0.0290 (0.0506) loss_box_reg: 0.0153 (0.0253) loss_mask: 0.0001 (0.0125) loss_objectness: 0.0136 (0.0347) loss_rpn_box_reg: 0.0859 (0.1046) time: 0.8535 data: 0.0039 max mem: 8508
  438. Epoch: [0] [1940/2000] eta: 0:00:51 lr: 0.005000 loss: 0.1466 (0.2273) loss_classifier: 0.0318 (0.0505) loss_box_reg: 0.0152 (0.0252) loss_mask: 0.0001 (0.0125) loss_objectness: 0.0132 (0.0346) loss_rpn_box_reg: 0.0860 (0.1045) time: 0.8550 data: 0.0023 max mem: 8508
  439. Epoch: [0] [1950/2000] eta: 0:00:43 lr: 0.005000 loss: 0.1503 (0.2308) loss_classifier: 0.0340 (0.0509) loss_box_reg: 0.0150 (0.0254) loss_mask: 0.0001 (0.0126) loss_objectness: 0.0157 (0.0352) loss_rpn_box_reg: 0.0876 (0.1067) time: 0.8519 data: 0.0023 max mem: 8508
  440. Epoch: [0] [1960/2000] eta: 0:00:34 lr: 0.005000 loss: 0.4206 (0.2319) loss_classifier: 0.0459 (0.0509) loss_box_reg: 0.0436 (0.0255) loss_mask: 0.0003 (0.0126) loss_objectness: 0.0260 (0.0352) loss_rpn_box_reg: 0.1728 (0.1078) time: 0.8473 data: 0.0023 max mem: 8508
  441. Epoch: [0] [1970/2000] eta: 0:00:25 lr: 0.005000 loss: 0.3346 (0.2323) loss_classifier: 0.0580 (0.0509) loss_box_reg: 0.0487 (0.0256) loss_mask: 0.0002 (0.0125) loss_objectness: 0.0325 (0.0353) loss_rpn_box_reg: 0.1728 (0.1080) time: 0.8465 data: 0.0008 max mem: 8508
  442. Epoch: [0] [1980/2000] eta: 0:00:17 lr: 0.005000 loss: 0.2608 (0.2324) loss_classifier: 0.0586 (0.0509) loss_box_reg: 0.0579 (0.0258) loss_mask: 0.0000 (0.0124) loss_objectness: 0.0309 (0.0352) loss_rpn_box_reg: 0.1044 (0.1080) time: 0.8488 data: 0.0008 max mem: 8508
  443. Epoch: [0] [1990/2000] eta: 0:00:08 lr: 0.005000 loss: 0.2417 (0.2324) loss_classifier: 0.0574 (0.0510) loss_box_reg: 0.0604 (0.0260) loss_mask: 0.0000 (0.0124) loss_objectness: 0.0196 (0.0351) loss_rpn_box_reg: 0.0940 (0.1079) time: 0.8496 data: 0.0015 max mem: 8508
  444. Epoch: [0] [1999/2000] eta: 0:00:00 lr: 0.005000 loss: 0.2187 (0.2323) loss_classifier: 0.0559 (0.0510) loss_box_reg: 0.0576 (0.0261) loss_mask: 0.0000 (0.0123) loss_objectness: 0.0187 (0.0351) loss_rpn_box_reg: 0.0889 (0.1078) time: 0.8487 data: 0.0015 max mem: 8508
  445. Epoch: [0] Total time: 0:28:41 (0.8607 s / it)
  446. creating index...
  447. index created!
  448. Test: [ 0/500] eta: 0:12:53 model_time: 0.7975 (0.7975) evaluator_time: 0.0313 (0.0313) time: 1.5480 data: 0.7192 max mem: 8508
  449. Test: [100/500] eta: 0:03:47 model_time: 0.5313 (0.5277) evaluator_time: 0.0313 (0.0312) time: 0.5581 data: 0.0016 max mem: 8508
  450. Test: [200/500] eta: 0:02:49 model_time: 0.5313 (0.5276) evaluator_time: 0.0313 (0.0309) time: 0.5658 data: 0.0023 max mem: 8508
  451. Test: [300/500] eta: 0:01:52 model_time: 0.5314 (0.5277) evaluator_time: 0.0313 (0.0309) time: 0.5613 data: 0.0023 max mem: 8508
  452. Test: [400/500] eta: 0:00:56 model_time: 0.5313 (0.5279) evaluator_time: 0.0313 (0.0309) time: 0.5604 data: 0.0016 max mem: 8508
  453. Test: [499/500] eta: 0:00:00 model_time: 0.5313 (0.5282) evaluator_time: 0.0312 (0.0312) time: 0.5675 data: 0.0031 max mem: 8508
  454. Test: Total time: 0:04:42 (0.5640 s / it)
  455. Averaged stats: model_time: 0.5313 (0.5282) evaluator_time: 0.0312 (0.0312)
  456. Accumulating evaluation results...
  457. DONE (t=1.00s).
  458. Accumulating evaluation results...
  459. DONE (t=1.02s).
  460. IoU metric: bbox
  461. Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.018
  462. Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.092
  463. Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000
  464. Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.018
  465. Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
  466. Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
  467. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000
  468. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.291
  469. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.357
  470. Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.357
  471. Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
  472. Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
  473. IoU metric: segm
  474. Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.013
  475. Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.060
  476. Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.001
  477. Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.013
  478. Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
  479. Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
  480. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000
  481. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.250
  482. Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.387
  483. Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.387
  484. Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
  485. Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = -1.000
  486. Epoch: [1] [ 0/2000] eta: 2:10:14 lr: 0.005000 loss: 0.2224 (0.2224) loss_classifier: 0.0528 (0.0528) loss_box_reg: 0.0568 (0.0568) loss_mask: 0.0000 (0.0000) loss_objectness: 0.0257 (0.0257) loss_rpn_box_reg: 0.0871 (0.0871) time: 3.9073 data: 2.8444 max mem: 8508
  487. Epoch: [1] [ 10/2000] eta: 0:37:25 lr: 0.005000 loss: 0.2151 (0.2161) loss_classifier: 0.0538 (0.0547) loss_box_reg: 0.0568 (0.0561) loss_mask: 0.0000 (0.0000) loss_objectness: 0.0194 (0.0187) loss_rpn_box_reg: 0.0866 (0.0866) time: 1.1283 data: 0.2614 max mem: 8508
  488. Epoch: [1] [ 20/2000] eta: 0:32:50 lr: 0.005000 loss: 0.2155 (0.2165) loss_classifier: 0.0555 (0.0549) loss_box_reg: 0.0573 (0.0561) loss_mask: 0.0000 (0.0000) loss_objectness: 0.0190 (0.0190) loss_rpn_box_reg: 0.0863 (0.0864) time: 0.8496 data: 0.0023 max mem: 8508
  489. Epoch: [1] [ 30/2000] eta: 0:31:08 lr: 0.005000 loss: 0.2227 (0.2185) loss_classifier: 0.0559 (0.0555) loss_box_reg: 0.0573 (0.0560) loss_mask: 0.0000 (0.0006) loss_objectness: 0.0205 (0.0196) loss_rpn_box_reg: 0.0863 (0.0867) time: 0.8496 data: 0.0028 max mem: 8508
  490. Epoch: [1] [ 40/2000] eta: 0:30:12 lr: 0.005000 loss: 0.2194 (0.2177) loss_classifier: 0.0560 (0.0556) loss_box_reg: 0.0533 (0.0549) loss_mask: 0.0000 (0.0017) loss_objectness: 0.0173 (0.0186) loss_rpn_box_reg: 0.0870 (0.0869) time: 0.8512 data: 0.0036 max mem: 8508
  491. Epoch: [1] [ 50/2000] eta: 0:29:35 lr: 0.005000 loss: 0.2149 (0.2235) loss_classifier: 0.0525 (0.0542) loss_box_reg: 0.0510 (0.0529) loss_mask: 0.0000 (0.0014) loss_objectness: 0.0162 (0.0203) loss_rpn_box_reg: 0.0877 (0.0947) time: 0.8512 data: 0.0016 max mem: 8508
  492. Epoch: [1] [ 60/2000] eta: 0:29:07 lr: 0.005000 loss: 0.2573 (0.2313) loss_classifier: 0.0530 (0.0547) loss_box_reg: 0.0513 (0.0535) loss_mask: 0.0000 (0.0012) loss_objectness: 0.0277 (0.0237) loss_rpn_box_reg: 0.1021 (0.0982) time: 0.8519 data: 0.0000 max mem: 8508
  493. Epoch: [1] [ 70/2000] eta: 0:28:46 lr: 0.005000 loss: 0.2422 (0.2311) loss_classifier: 0.0587 (0.0553) loss_box_reg: 0.0556 (0.0538) loss_mask: 0.0001 (0.0010) loss_objectness: 0.0239 (0.0233) loss_rpn_box_reg: 0.0951 (0.0976) time: 0.8534 data: 0.0008 max mem: 8508
  494. Epoch: [1] [ 80/2000] eta: 0:28:27 lr: 0.005000 loss: 0.2266 (0.2361) loss_classifier: 0.0577 (0.0557) loss_box_reg: 0.0561 (0.0545) loss_mask: 0.0001 (0.0060) loss_objectness: 0.0194 (0.0230) loss_rpn_box_reg: 0.0910 (0.0968) time: 0.8542 data: 0.0031 max mem: 8508
  495. Epoch: [1] [ 90/2000] eta: 0:28:11 lr: 0.005000 loss: 0.2398 (0.2378) loss_classifier: 0.0577 (0.0563) loss_box_reg: 0.0590 (0.0553) loss_mask: 0.0009 (0.0055) loss_objectness: 0.0212 (0.0231) loss_rpn_box_reg: 0.0923 (0.0976) time: 0.8543 data: 0.0039 max mem: 8508
  496. Epoch: [1] [ 100/2000] eta: 0:27:57 lr: 0.005000 loss: 0.2391 (0.2376) loss_classifier: 0.0588 (0.0564) loss_box_reg: 0.0601 (0.0562) loss_mask: 0.0007 (0.0050) loss_objectness: 0.0212 (0.0228) loss_rpn_box_reg: 0.0967 (0.0972) time: 0.8550 data: 0.0023 max mem: 8508
  497. Epoch: [1] [ 110/2000] eta: 0:27:43 lr: 0.005000 loss: 0.2232 (0.2359) loss_classifier: 0.0563 (0.0564) loss_box_reg: 0.0576 (0.0563) loss_mask: 0.0002 (0.0045) loss_objectness: 0.0183 (0.0222) loss_rpn_box_reg: 0.0895 (0.0964) time: 0.8565 data: 0.0031 max mem: 8508
  498. Epoch: [1] [ 120/2000] eta: 0:27:30 lr: 0.005000 loss: 0.2176 (0.2345) loss_classifier: 0.0569 (0.0565) loss_box_reg: 0.0552 (0.0563) loss_mask: 0.0000 (0.0042) loss_objectness: 0.0172 (0.0218) loss_rpn_box_reg: 0.0871 (0.0956) time: 0.8542 data: 0.0031 max mem: 8508
  499. Epoch: [1] [ 130/2000] eta: 0:27:18 lr: 0.005000 loss: 0.2119 (0.2324) loss_classifier: 0.0561 (0.0565) loss_box_reg: 0.0502 (0.0556) loss_mask: 0.0000 (0.0039) loss_objectness: 0.0179 (0.0216) loss_rpn_box_reg: 0.0865 (0.0949) time: 0.8526 data: 0.0016 max mem: 8508
  500. Epoch: [1] [ 140/2000] eta: 0:27:06 lr: 0.005000 loss: 0.2022 (0.2301) loss_classifier: 0.0550 (0.0563) loss_box_reg: 0.0433 (0.0545) loss_mask: 0.0000 (0.0036) loss_objectness: 0.0166 (0.0212) loss_rpn_box_reg: 0.0863 (0.0945) time: 0.8527 data: 0.0008 max mem: 8508
  501. Epoch: [1] [ 150/2000] eta: 0:26:54 lr: 0.005000 loss: 0.2022 (0.2285) loss_classifier: 0.0531 (0.0560) loss_box_reg: 0.0406 (0.0537) loss_mask: 0.0000 (0.0034) loss_objectness: 0.0169 (0.0210) loss_rpn_box_reg: 0.0887 (0.0943) time: 0.8527 data: 0.0008 max mem: 8508
  502. Epoch: [1] [ 160/2000] eta: 0:26:43 lr: 0.005000 loss: 0.2051 (0.2269) loss_classifier: 0.0532 (0.0559) loss_box_reg: 0.0425 (0.0531) loss_mask: 0.0000 (0.0032) loss_objectness: 0.0179 (0.0209) loss_rpn_box_reg: 0.0882 (0.0938) time: 0.8519 data: 0.0023 max mem: 8508
  503. Epoch: [1] [ 170/2000] eta: 0:26:32 lr: 0.005000 loss: 0.1989 (0.2251) loss_classifier: 0.0521 (0.0556) loss_box_reg: 0.0428 (0.0524) loss_mask: 0.0000 (0.0030) loss_objectness: 0.0174 (0.0207) loss_rpn_box_reg: 0.0865 (0.0934) time: 0.8511 data: 0.0023 max mem: 8508
  504. Epoch: [1] [ 180/2000] eta: 0:26:22 lr: 0.005000 loss: 0.1936 (0.2234) loss_classifier: 0.0499 (0.0552) loss_box_reg: 0.0404 (0.0517) loss_mask: 0.0000 (0.0028) loss_objectness: 0.0174 (0.0205) loss_rpn_box_reg: 0.0863 (0.0930) time: 0.8526 data: 0.0016 max mem: 8508
  505. Epoch: [1] [ 190/2000] eta: 0:26:12 lr: 0.005000 loss: 0.1926 (0.2216) loss_classifier: 0.0484 (0.0548) loss_box_reg: 0.0402 (0.0512) loss_mask: 0.0000 (0.0027) loss_objectness: 0.0154 (0.0203) loss_rpn_box_reg: 0.0863 (0.0927) time: 0.8534 data: 0.0016 max mem: 8508
  506. Epoch: [1] [ 200/2000] eta: 0:26:02 lr: 0.005000 loss: 0.1885 (0.2200) loss_classifier: 0.0459 (0.0543) loss_box_reg: 0.0391 (0.0506) loss_mask: 0.0000 (0.0026) loss_objectness: 0.0148 (0.0202) loss_rpn_box_reg: 0.0863 (0.0924) time: 0.8534 data: 0.0016 max mem: 8508
  507. Epoch: [1] [ 210/2000] eta: 0:25:51 lr: 0.005000 loss: 0.1853 (0.2182) loss_classifier: 0.0444 (0.0538) loss_box_reg: 0.0370 (0.0499) loss_mask: 0.0000 (0.0024) loss_objectness: 0.0160 (0.0200) loss_rpn_box_reg: 0.0861 (0.0921) time: 0.8518 data: 0.0023 max mem: 8508
  508. Epoch: [1] [ 220/2000] eta: 0:25:42 lr: 0.005000 loss: 0.1808 (0.2165) loss_classifier: 0.0414 (0.0532) loss_box_reg: 0.0349 (0.0492) loss_mask: 0.0000 (0.0023) loss_objectness: 0.0180 (0.0200) loss_rpn_box_reg: 0.0861 (0.0919) time: 0.8511 data: 0.0039 max mem: 8508
  509. Epoch: [1] [ 230/2000] eta: 0:25:32 lr: 0.005000 loss: 0.1780 (0.2148) loss_classifier: 0.0402 (0.0526) loss_box_reg: 0.0327 (0.0484) loss_mask: 0.0000 (0.0022) loss_objectness: 0.0188 (0.0199) loss_rpn_box_reg: 0.0866 (0.0916) time: 0.8518 data: 0.0031 max mem: 8508
  510. Epoch: [1] [ 240/2000] eta: 0:25:22 lr: 0.005000 loss: 0.1780 (0.2135) loss_classifier: 0.0397 (0.0520) loss_box_reg: 0.0313 (0.0477) loss_mask: 0.0000 (0.0021) loss_objectness: 0.0197 (0.0200) loss_rpn_box_reg: 0.0869 (0.0916) time: 0.8518 data: 0.0023 max mem: 8508
  511. Epoch: [1] [ 250/2000] eta: 0:25:12 lr: 0.005000 loss: 0.1793 (0.2119) loss_classifier: 0.0385 (0.0515) loss_box_reg: 0.0293 (0.0470) loss_mask: 0.0000 (0.0021) loss_objectness: 0.0189 (0.0199) loss_rpn_box_reg: 0.0885 (0.0915) time: 0.8510 data: 0.0039 max mem: 8508
  512. Epoch: [1] [ 260/2000] eta: 0:25:03 lr: 0.005000 loss: 0.1688 (0.2102) loss_classifier: 0.0356 (0.0508) loss_box_reg: 0.0283 (0.0462) loss_mask: 0.0000 (0.0020) loss_objectness: 0.0156 (0.0198) loss_rpn_box_reg: 0.0868 (0.0913) time: 0.8519 data: 0.0047 max mem: 8508
  513. Epoch: [1] [ 270/2000] eta: 0:24:54 lr: 0.005000 loss: 0.1654 (0.2084) loss_classifier: 0.0318 (0.0501) loss_box_reg: 0.0241 (0.0453) loss_mask: 0.0000 (0.0020) loss_objectness: 0.0160 (0.0197) loss_rpn_box_reg: 0.0872 (0.0913) time: 0.8519 data: 0.0023 max mem: 8508
  514. Epoch: [1] [ 280/2000] eta: 0:24:44 lr: 0.005000 loss: 0.1596 (0.2067) loss_classifier: 0.0306 (0.0494) loss_box_reg: 0.0223 (0.0445) loss_mask: 0.0000 (0.0019) loss_objectness: 0.0160 (0.0196) loss_rpn_box_reg: 0.0879 (0.0913) time: 0.8511 data: 0.0016 max mem: 8508
  515. Epoch: [1] [ 290/2000] eta: 0:24:35 lr: 0.005000 loss: 0.1667 (0.2057) loss_classifier: 0.0316 (0.0490) loss_box_reg: 0.0233 (0.0438) loss_mask: 0.0000 (0.0018) loss_objectness: 0.0157 (0.0195) loss_rpn_box_reg: 0.0947 (0.0916) time: 0.8518 data: 0.0023 max mem: 8508
  516. Epoch: [1] [ 300/2000] eta: 0:24:26 lr: 0.005000 loss: 0.1735 (0.2046) loss_classifier: 0.0325 (0.0484) loss_box_reg: 0.0257 (0.0432) loss_mask: 0.0000 (0.0018) loss_objectness: 0.0163 (0.0195) loss_rpn_box_reg: 0.0947 (0.0916) time: 0.8518 data: 0.0016 max mem: 8508
  517. Epoch: [1] [ 310/2000] eta: 0:24:16 lr: 0.005000 loss: 0.1681 (0.2034) loss_classifier: 0.0319 (0.0479) loss_box_reg: 0.0246 (0.0427) loss_mask: 0.0000 (0.0017) loss_objectness: 0.0163 (0.0193) loss_rpn_box_reg: 0.0920 (0.0918) time: 0.8510 data: 0.0023 max mem: 8508
  518. Epoch: [1] [ 320/2000] eta: 0:24:07 lr: 0.005000 loss: 0.1628 (0.2022) loss_classifier: 0.0314 (0.0474) loss_box_reg: 0.0234 (0.0420) loss_mask: 0.0000 (0.0017) loss_objectness: 0.0147 (0.0192) loss_rpn_box_reg: 0.0920 (0.0919) time: 0.8511 data: 0.0039 max mem: 8508
  519. Epoch: [1] [ 330/2000] eta: 0:23:58 lr: 0.005000 loss: 0.1538 (0.2005) loss_classifier: 0.0287 (0.0468) loss_box_reg: 0.0186 (0.0413) loss_mask: 0.0000 (0.0016) loss_objectness: 0.0159 (0.0191) loss_rpn_box_reg: 0.0881 (0.0917) time: 0.8519 data: 0.0031 max mem: 8508
  520. Epoch: [1] [ 340/2000] eta: 0:23:49 lr: 0.005000 loss: 0.1415 (0.1987) loss_classifier: 0.0274 (0.0462) loss_box_reg: 0.0135 (0.0404) loss_mask: 0.0000 (0.0016) loss_objectness: 0.0125 (0.0189) loss_rpn_box_reg: 0.0863 (0.0916) time: 0.8511 data: 0.0016 max mem: 8508
  521. Loss is nan, stopping training
  522. {'loss_classifier': tensor(nan, device='cuda:0', grad_fn=<NllLossBackward0>), 'loss_box_reg': tensor(nan, device='cuda:0', grad_fn=<DivBackward0>), 'loss_mask': tensor(0., device='cuda:0', grad_fn=<BinaryCrossEntropyWithLogitsBackward0>), 'loss_objectness': tensor(nan, device='cuda:0', grad_fn=<BinaryCrossEntropyWithLogitsBackward0>), 'loss_rpn_box_reg': tensor(5.9330e+34, device='cuda:0', grad_fn=<DivBackward0>)}
  523.  
  524. Process finished with exit code 1
  525.  
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