Please provide the following information when requesting support.
• Hardware: 3090
• Network Type: Yolo_v4_tiny
Hey,
I’m trying to train a model for inference based on Yolo_v4_tiny. The training period stops after a small number of epochs (please see below the TAO’s output during the training).
One major change I made in the spec files is- because the training is based on HD resolution images, I’ve changed the output height and width in spec ‘augmentation’ section to 1920X1024
Regarding the anchors - I created the anchors at first, as suggested by the script, with the original image size (1920X1080). But let’s say I change the output size in the augmentation property, for example to 640x480. Could this create a problem at the traning phase?
im not sure why it happened, because in the spec file I specified batch_size_per_gpu: 8
BTW in the tfrecored file, i didn’t understand what are the preferred values if my data-set contains 1000 images:
num_partitions: 2
val_split: 10
num_shards: 4
is that ok?
There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
Thanks