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ojbects -> objects

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Nadeen Udantha
2018-05-18 14:19:19 +05:30
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@ -349,7 +349,7 @@ Usually sufficient 2000 iterations for each class(object). But for a more precis
2. Once training is stopped, you should take some of last `.weights`-files from `darknet\build\darknet\x64\backup` and choose the best of them:
For example, you stopped training after 9000 iterations, but the best result can give one of previous weights (7000, 8000, 9000). It can happen due to overfitting. **Overfitting** - is case when you can detect objects on images from training-dataset, but can't detect ojbects on any others images. You should get weights from **Early Stopping Point**:
For example, you stopped training after 9000 iterations, but the best result can give one of previous weights (7000, 8000, 9000). It can happen due to overfitting. **Overfitting** - is case when you can detect objects on images from training-dataset, but can't detect objects on any others images. You should get weights from **Early Stopping Point**:
![Overfitting](https://hsto.org/files/5dc/7ae/7fa/5dc7ae7fad9d4e3eb3a484c58bfc1ff5.png)