{"action":"created","issue":{"url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/102","repository_url":"https://api.github.com/repos/NVIDIA/tacotron2","labels_url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/102/labels{/name}","comments_url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/102/comments","events_url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/102/events","html_url":"https://github.com/NVIDIA/tacotron2/issues/102","id":386691975,"node_id":"MDU6SXNzdWUzODY2OTE5NzU=","number":102,"title":"Training result is not as good as the pre-trained model","user":{"login":"nanma","id":1190445,"node_id":"MDQ6VXNlcjExOTA0NDU=","avatar_url":"https://avatars3.githubusercontent.com/u/1190445?v=4","gravatar_id":"","url":"https://api.github.com/users/nanma","html_url":"https://github.com/nanma","followers_url":"https://api.github.com/users/nanma/followers","following_url":"https://api.github.com/users/nanma/following{/other_user}","gists_url":"https://api.github.com/users/nanma/gists{/gist_id}","starred_url":"https://api.github.com/users/nanma/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/nanma/subscriptions","organizations_url":"https://api.github.com/users/nanma/orgs","repos_url":"https://api.github.com/users/nanma/repos","events_url":"https://api.github.com/users/nanma/events{/privacy}","received_events_url":"https://api.github.com/users/nanma/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2018-12-03T07:33:17Z","updated_at":"2018-12-14T03:10:23Z","closed_at":"2018-12-03T08:22:04Z","author_association":"NONE","body":"I train this Tacotron2 model with the latest version of code and hparams(commit:6e430).  After running 500 epochs, the validation loss 0.3308, but the alignment is not very good:\r\n![image](https://user-images.githubusercontent.com/1190445/49358849-25782100-f70f-11e8-8ef1-18e09854d50b.png)\r\n\r\nThe training and validation loss curves are:\r\n![image](https://user-images.githubusercontent.com/1190445/49359223-7ccac100-f710-11e8-9899-db071b8e4777.png)\r\n\r\n![image](https://user-images.githubusercontent.com/1190445/49359188-53aa3080-f710-11e8-8b4b-f6f84bbde28d.png)\r\n\r\nAnd the audio generated by my Tacotron2 model with the pre-trained Waveglow is not as good as the pre-trained Tacotron2 and Waveglow model.\r\n\r\nShould I continue training with more than 500 epochs? Or any suggestion for improving training would be help.\r\n"},"comment":{"url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/comments/447198873","html_url":"https://github.com/NVIDIA/tacotron2/issues/102#issuecomment-447198873","issue_url":"https://api.github.com/repos/NVIDIA/tacotron2/issues/102","id":447198873,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0NzE5ODg3Mw==","user":{"login":"nanma","id":1190445,"node_id":"MDQ6VXNlcjExOTA0NDU=","avatar_url":"https://avatars3.githubusercontent.com/u/1190445?v=4","gravatar_id":"","url":"https://api.github.com/users/nanma","html_url":"https://github.com/nanma","followers_url":"https://api.github.com/users/nanma/followers","following_url":"https://api.github.com/users/nanma/following{/other_user}","gists_url":"https://api.github.com/users/nanma/gists{/gist_id}","starred_url":"https://api.github.com/users/nanma/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/nanma/subscriptions","organizations_url":"https://api.github.com/users/nanma/orgs","repos_url":"https://api.github.com/users/nanma/repos","events_url":"https://api.github.com/users/nanma/events{/privacy}","received_events_url":"https://api.github.com/users/nanma/received_events","type":"User","site_admin":false},"created_at":"2018-12-14T03:10:23Z","updated_at":"2018-12-14T03:10:23Z","author_association":"NONE","body":"@dnnnew  \r\nI train the model for more epochs with the default learning rate, the valid loss reaches 0.28+. After that I start to decay the lr and continue training. The valid loss is 0.27+ now, and the alignment is better than when only training 500 epochs.\r\nThe alignment is still not as good as the pre-trained model, I will continue training."}}
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