Timeline for Loss value going down while accuracy remains constant?
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 4, 2019 at 22:12 | history | edited | Simon Larsson | CC BY-SA 4.0 | Typo |
| May 4, 2019 at 21:55 | vote | accept | Zadak Leader | ||
| May 4, 2019 at 21:52 | comment | added | Simon Larsson | Yes, accuracy only makes sense for exact matches which is quite rare in regression. Will try to explain why in my answer. But if accuracy was the only issue, then all is good! :) | |
| May 4, 2019 at 21:48 | comment | added | Zadak Leader | Thanks! I was already using that, but also accuracy and also validating the data. So you're saying accuracy is not important for what I am trying to do? The training seems to kind of do what I want, just wondering why the accuracy stays pretty much pinned at that specific value after the first epoch :) | |
| May 4, 2019 at 21:40 | history | answered | Simon Larsson | CC BY-SA 4.0 |