{"action":"opened","issue":{"url":"https://api.github.com/repos/BVLC/caffe/issues/2622","labels_url":"https://api.github.com/repos/BVLC/caffe/issues/2622/labels{/name}","comments_url":"https://api.github.com/repos/BVLC/caffe/issues/2622/comments","events_url":"https://api.github.com/repos/BVLC/caffe/issues/2622/events","html_url":"https://github.com/BVLC/caffe/issues/2622","id":89441474,"number":2622,"title":"Accuracy remain unchanged for some class","user":{"login":"benlam62","id":12960170,"avatar_url":"https://avatars.githubusercontent.com/u/12960170?v=3","gravatar_id":"","url":"https://api.github.com/users/benlam62","html_url":"https://github.com/benlam62","followers_url":"https://api.github.com/users/benlam62/followers","following_url":"https://api.github.com/users/benlam62/following{/other_user}","gists_url":"https://api.github.com/users/benlam62/gists{/gist_id}","starred_url":"https://api.github.com/users/benlam62/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/benlam62/subscriptions","organizations_url":"https://api.github.com/users/benlam62/orgs","repos_url":"https://api.github.com/users/benlam62/repos","events_url":"https://api.github.com/users/benlam62/events{/privacy}","received_events_url":"https://api.github.com/users/benlam62/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-06-19T01:37:51Z","updated_at":"2015-06-19T01:37:51Z","closed_at":null,"body":"Hi folks, during the VGG-16 net training for 2 classes + background class, I find weird that one of the class' accuracy remain unchanged. You can see the output #1 below remain 0.333. Does anyone has any comment on it?\r\n\r\nI0618 23:45:36.158685 40897 solver.cpp:209] Iteration 54, loss = 0.767131\r\nI0618 23:45:36.158941 40897 solver.cpp:224]     Train net output #0: accuracy = 0.734801\r\nI0618 23:45:36.158967 40897 solver.cpp:224]     Train net output #1: accuracy = 0.333333\r\nI0618 23:45:36.158982 40897 solver.cpp:224]     Train net output #2: accuracy = 0.244934\r\nI0618 23:45:36.159001 40897 solver.cpp:447] Iteration 54, lr = 0.001\r\nI0618 23:56:05.718288 40897 solver.cpp:209] Iteration 55, loss = 0.740111\r\nI0618 23:56:05.718528 40897 solver.cpp:224]     Train net output #0: accuracy = 0.74539\r\nI0618 23:56:05.718552 40897 solver.cpp:224]     Train net output #1: accuracy = 0.333333\r\nI0618 23:56:05.718569 40897 solver.cpp:224]     Train net output #2: accuracy = 0.248463\r\nI0618 23:56:05.718587 40897 solver.cpp:447] Iteration 55, lr = 0.001\r\nI0619 00:06:34.629878 40897 solver.cpp:209] Iteration 56, loss = 0.710542\r\nI0619 00:06:34.630365 40897 solver.cpp:224]     Train net output #0: accuracy = 0.76395\r\nI0619 00:06:34.630394 40897 solver.cpp:224]     Train net output #1: accuracy = 0.333333\r\nI0619 00:06:34.630411 40897 solver.cpp:224]     Train net output #2: accuracy = 0.25465\r\nI0619 00:06:34.630430 40897 solver.cpp:447] Iteration 56, lr = 0.001\r\n\r\nThx\r\nBen\r\n\r\n"}}