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HI ,Folks . I'm really late π₯².
\nI was training efficientnetv2 s on previous dataset using pytorch lightning . But the results i obtained are somewhat odd .Why there is fluctuation in both training and validation , How to reduce it .
\n
HI ,Folks . I'm really late π₯².
\nI was training efficientnetv2 s on previous dataset using pytorch lightning . But the results i obtained are somewhat odd .Why there is fluctuation in both training and validation , How to reduce it .
\n
It seems that you might not be smoothing out the curve? Usually when logging these metrics, running loss and running acc is used, which means that the value is the mean of the past batches in this epoch therefore producing more of a smooth training curve.
", "rawMarkdown": "It seems that you might not be smoothing out the curve? Usually when logging these metrics, running loss and running acc is used, which means that the value is the mean of the past batches in this epoch therefore producing more of a smooth training curve.", "votes": null }, { "id": "2267613", "postDate": "05/21/2023 05:52:16", "content": "So , that means the model is learning well. I just need to use running loss and running acc, i.e., i had to smooth the curves . Also ,My training took 9hrs ,i finetuning , the efiicientnetV2 model on 2021 & 2022 dataset ,with batch size 32 , i'm not using preprocessed mel spectograms , i don't know even after training this long , model hasn't saved yet πΆβπ«οΈ . Literally , lost my time and resources .
", "rawMarkdown": "So , that means the model is learning well. I just need to use running loss and running acc, i.e., i had to smooth the curves . Also ,My training took 9hrs ,i finetuning , the efiicientnetV2 model on 2021 & 2022 dataset ,with batch size 32 , i'm not using preprocessed mel spectograms , i don't know even after training this long , model hasn't saved yet πΆβπ«οΈ . Literally , lost my time and resources .", "votes": null }, { "id": "2267867", "postDate": "05/21/2023 09:42:08", "content": "Well, welcome to Kaggle! I guess making mistakes is an inevitable process where everyone has to go through.
", "rawMarkdown": "Well, welcome to Kaggle! I guess making mistakes is an inevitable process where everyone has to go through.", "votes": null } ], "comments": [ { "id": 2266943, "author_name": "lhanhsin", "author_url": "", "post_date": "05/20/2023 13:39:28", "content": "It seems that you might not be smoothing out the curve? Usually when logging these metrics, running loss and running acc is used, which means that the value is the mean of the past batches in this epoch therefore producing more of a smooth training curve.
", "votes": null, "replies": [ { "id": 2267613, "author_name": "altairfarooque", "author_url": "", "post_date": "05/21/2023 05:52:16", "content": "So , that means the model is learning well. I just need to use running loss and running acc, i.e., i had to smooth the curves . Also ,My training took 9hrs ,i finetuning , the efiicientnetV2 model on 2021 & 2022 dataset ,with batch size 32 , i'm not using preprocessed mel spectograms , i don't know even after training this long , model hasn't saved yet πΆβπ«οΈ . Literally , lost my time and resources .
", "votes": null, "replies": [ { "id": 2267867, "author_name": "lhanhsin", "author_url": "", "post_date": "05/21/2023 09:42:08", "content": "Well, welcome to Kaggle! I guess making mistakes is an inevitable process where everyone has to go through.
", "votes": null, "replies": [] } ] } ] } ], "raw_markdown_by_id": { "2266452": "HI ,Folks . I'm really late π₯².\n\nI was training efficientnetv2 s on previous dataset using pytorch lightning . But the results i obtained are somewhat odd .Why there is fluctuation in both training and validation , How to reduce it .\n\n", "2266943": "It seems that you might not be smoothing out the curve? Usually when logging these metrics, running loss and running acc is used, which means that the value is the mean of the past batches in this epoch therefore producing more of a smooth training curve.", "2267613": "So , that means the model is learning well. I just need to use running loss and running acc, i.e., i had to smooth the curves . Also ,My training took 9hrs ,i finetuning , the efiicientnetV2 model on 2021 & 2022 dataset ,with batch size 32 , i'm not using preprocessed mel spectograms , i don't know even after training this long , model hasn't saved yet πΆβπ«οΈ . Literally , lost my time and resources .", "2267867": "Well, welcome to Kaggle! I guess making mistakes is an inevitable process where everyone has to go through." }, "source": "meta" }