{"action":"created","issue":{"url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/27","repository_url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss","labels_url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/27/labels{/name}","comments_url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/27/comments","events_url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/27/events","html_url":"https://github.com/omoindrot/tensorflow-triplet-loss/issues/27","id":377796339,"node_id":"MDU6SXNzdWUzNzc3OTYzMzk=","number":27,"title":"Loss goes to 0 but embeddings are bad","user":{"login":"FSetragno","id":8984671,"node_id":"MDQ6VXNlcjg5ODQ2NzE=","avatar_url":"https://avatars0.githubusercontent.com/u/8984671?v=4","gravatar_id":"","url":"https://api.github.com/users/FSetragno","html_url":"https://github.com/FSetragno","followers_url":"https://api.github.com/users/FSetragno/followers","following_url":"https://api.github.com/users/FSetragno/following{/other_user}","gists_url":"https://api.github.com/users/FSetragno/gists{/gist_id}","starred_url":"https://api.github.com/users/FSetragno/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/FSetragno/subscriptions","organizations_url":"https://api.github.com/users/FSetragno/orgs","repos_url":"https://api.github.com/users/FSetragno/repos","events_url":"https://api.github.com/users/FSetragno/events{/privacy}","received_events_url":"https://api.github.com/users/FSetragno/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-11-06T11:04:11Z","updated_at":"2018-11-07T21:20:56Z","closed_at":null,"author_association":"NONE","body":"I trained a network with the triplet loss over a small dataset with 6 different identities and about 1000 total images. I noticed that the loss goes to 0 after 100 steps. However, the performances are not good: the embeddings seem just noise. I used a small learning rate (1e-4) and a simple network with 6 convolutions (conv+BN+relu) and 3 pooling. This happens both with batch hard and batch all. What could be the problem?"},"comment":{"url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/comments/436781501","html_url":"https://github.com/omoindrot/tensorflow-triplet-loss/issues/27#issuecomment-436781501","issue_url":"https://api.github.com/repos/omoindrot/tensorflow-triplet-loss/issues/27","id":436781501,"node_id":"MDEyOklzc3VlQ29tbWVudDQzNjc4MTUwMQ==","user":{"login":"omoindrot","id":13662086,"node_id":"MDQ6VXNlcjEzNjYyMDg2","avatar_url":"https://avatars3.githubusercontent.com/u/13662086?v=4","gravatar_id":"","url":"https://api.github.com/users/omoindrot","html_url":"https://github.com/omoindrot","followers_url":"https://api.github.com/users/omoindrot/followers","following_url":"https://api.github.com/users/omoindrot/following{/other_user}","gists_url":"https://api.github.com/users/omoindrot/gists{/gist_id}","starred_url":"https://api.github.com/users/omoindrot/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/omoindrot/subscriptions","organizations_url":"https://api.github.com/users/omoindrot/orgs","repos_url":"https://api.github.com/users/omoindrot/repos","events_url":"https://api.github.com/users/omoindrot/events{/privacy}","received_events_url":"https://api.github.com/users/omoindrot/received_events","type":"User","site_admin":false},"created_at":"2018-11-07T21:20:56Z","updated_at":"2018-11-07T21:20:56Z","author_association":"OWNER","body":"What are you measuring when you say \"performance is not good\"?\r\n\r\nIf you are looking at embeddings on a separate test set, it is possible that the model overfits with 6 identities. Maybe you could add regularization or increase the number of identities / images?"}}
{"actor":{"display_login":"omoindrot"}}