{"action":"created","issue":{"url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/31","repository_url":"https://api.github.com/repos/princeton-vl/CornerNet","labels_url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/31/labels{/name}","comments_url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/31/comments","events_url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/31/events","html_url":"https://github.com/princeton-vl/CornerNet/issues/31","id":368924830,"node_id":"MDU6SXNzdWUzNjg5MjQ4MzA=","number":31,"title":"Loss chages little","user":{"login":"XiaSunny","id":32034469,"node_id":"MDQ6VXNlcjMyMDM0NDY5","avatar_url":"https://avatars1.githubusercontent.com/u/32034469?v=4","gravatar_id":"","url":"https://api.github.com/users/XiaSunny","html_url":"https://github.com/XiaSunny","followers_url":"https://api.github.com/users/XiaSunny/followers","following_url":"https://api.github.com/users/XiaSunny/following{/other_user}","gists_url":"https://api.github.com/users/XiaSunny/gists{/gist_id}","starred_url":"https://api.github.com/users/XiaSunny/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/XiaSunny/subscriptions","organizations_url":"https://api.github.com/users/XiaSunny/orgs","repos_url":"https://api.github.com/users/XiaSunny/repos","events_url":"https://api.github.com/users/XiaSunny/events{/privacy}","received_events_url":"https://api.github.com/users/XiaSunny/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-10-11T02:18:52Z","updated_at":"2018-10-15T15:27:47Z","closed_at":null,"author_association":"NONE","body":"When i train my own 2047 training sets,its loss is around 4.The problem is as follows:\r\n\r\n\r\n\r\ntraining loss at iteration 54405: 3.7331526279449463                            \r\ntraining loss at iteration 54410: 3.6703977584838867                            \r\ntraining loss at iteration 54415: 3.792213201522827                             \r\ntraining loss at iteration 54420: 3.184262275695801                             \r\ntraining loss at iteration 54425: 2.5833559036254883                            \r\ntraining loss at iteration 54430: 3.983672618865967                             \r\ntraining loss at iteration 54435: 2.3275046348571777                            \r\ntraining loss at iteration 54440: 5.39171838760376                              \r\ntraining loss at iteration 54445: 4.39638090133667                              \r\ntraining loss at iteration 54450: 4.163412094116211                             \r\ntraining loss at iteration 54455: 3.498041868209839                             \r\ntraining loss at iteration 54460: 4.481285572052002                             \r\ntraining loss at iteration 54465: 4.839260101318359                             \r\ntraining loss at iteration 54470: 3.994492769241333                             \r\ntraining loss at iteration 54475: 3.5584001541137695                            \r\ntraining loss at iteration 54480: 4.685251712799072                             \r\ntraining loss at iteration 54485: 4.015157222747803                             \r\ntraining loss at iteration 54490: 4.063553810119629                             \r\ntraining loss at iteration 54495: 3.18803334236145                              \r\ntraining loss at iteration 54500: 4.06464147567749                              \r\nvalidation loss at iteration 54500: 3.384662628173828                           \r\ntraining loss at iteration 54505: 4.854454517364502                             \r\ntraining loss at iteration 54510: 4.531534671783447                             \r\ntraining loss at iteration 54515: 3.9393210411071777                            \r\ntraining loss at iteration 54520: 3.8535616397857666                            \r\ntraining loss at iteration 54525: 4.103610992431641                             \r\ntraining loss at iteration 54530: 5.204475402832031                             \r\ntraining loss at iteration 54535: 4.274611949920654                             \r\ntraining loss at iteration 54540: 3.4196114540100098                            \r\ntraining loss at iteration 54545: 3.8542287349700928                            \r\ntraining loss at iteration 54550: 2.900420904159546                             \r\ntraining loss at iteration 54555: 4.218133926391602                             \r\ntraining loss at iteration 54560: 3.702637195587158                             \r\ntraining loss at iteration 54565: 4.377786159515381                             \r\ntraining loss at iteration 54570: 4.17509126663208                              \r\ntraining loss at iteration 54575: 4.399285316467285                             \r\ntraining loss at iteration 54580: 4.801181316375732                             \r\ntraining loss at iteration 54585: 3.8167858123779297                            \r\ntraining loss at iteration 54590: 3.7509422302246094                            \r\ntraining loss at iteration 54595: 3.3366339206695557                            \r\ntraining loss at iteration 54600: 4.960026264190674                             \r\nvalidation loss at iteration 54600: 4.456686496734619                           \r\ntraining loss at iteration 54605: 7.162835597991943                             \r\ntraining loss at iteration 54610: 4.2326860427856445                            \r\ntraining loss at iteration 54615: 5.217791557312012                             \r\ntraining loss at iteration 54620: 5.991508483886719                             \r\ntraining loss at iteration 54625: 3.405985116958618                             \r\ntraining loss at iteration 54630: 8.021293640136719                             \r\ntraining loss at iteration 54635: 4.542353630065918                             \r\ntraining loss at iteration 54640: 5.705121040344238                             \r\n 47%|██████████████▍                | 39641/85000 [15:58:31<18:16:47,  1.45s/it]\r\n\r\nThank  you! @heilaw \r\n\r\n"},"comment":{"url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/comments/429900307","html_url":"https://github.com/princeton-vl/CornerNet/issues/31#issuecomment-429900307","issue_url":"https://api.github.com/repos/princeton-vl/CornerNet/issues/31","id":429900307,"node_id":"MDEyOklzc3VlQ29tbWVudDQyOTkwMDMwNw==","user":{"login":"heilaw","id":2282700,"node_id":"MDQ6VXNlcjIyODI3MDA=","avatar_url":"https://avatars0.githubusercontent.com/u/2282700?v=4","gravatar_id":"","url":"https://api.github.com/users/heilaw","html_url":"https://github.com/heilaw","followers_url":"https://api.github.com/users/heilaw/followers","following_url":"https://api.github.com/users/heilaw/following{/other_user}","gists_url":"https://api.github.com/users/heilaw/gists{/gist_id}","starred_url":"https://api.github.com/users/heilaw/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/heilaw/subscriptions","organizations_url":"https://api.github.com/users/heilaw/orgs","repos_url":"https://api.github.com/users/heilaw/repos","events_url":"https://api.github.com/users/heilaw/events{/privacy}","received_events_url":"https://api.github.com/users/heilaw/received_events","type":"User","site_admin":false},"created_at":"2018-10-15T15:27:47Z","updated_at":"2018-10-15T15:27:47Z","author_association":"COLLABORATOR","body":"Can you give more details about the training? For example, size of your dataset, batch size, number of GPUs etc. You may also consider fine-tuning our model on your dataset. https://github.com/princeton-vl/CornerNet/issues/23#issuecomment-425477357"}}
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