With batch size of 256, training the ResNet18 model, I go the CUDA out of memory error, so I had to reduce the batch size to 128. With batch size 128, below are the logs:
Epoch: [49][ 200/1080] Time 2.723 ( 2.664) Data 2.575 ( 2.515) Loss 1.3415e+00 (1.3413e+00) Acc@1 100.00 ( 99.33) Acc@5 100.00 ( 99.96)
Epoch: [49][ 400/1080] Time 3.064 ( 2.778) Data 2.915 ( 2.630) Loss 1.3431e+00 (1.3420e+00) Acc@1 99.22 ( 99.31) Acc@5 100.00 ( 99.96)
Epoch: [49][ 600/1080] Time 2.882 ( 2.845) Data 2.729 ( 2.696) Loss 1.3618e+00 (1.3444e+00) Acc@1 100.00 ( 99.27) Acc@5 100.00 ( 99.95)
I am not sure if the model is overfitting, could you please provide clarification on reading this output logs?
I am using the VoxCeleb1 data from 2022 challenge.
Hello,
With batch size of 256, training the ResNet18 model, I go the CUDA out of memory error, so I had to reduce the batch size to 128. With batch size 128, below are the logs:
Epoch: [49][ 200/1080] Time 2.723 ( 2.664) Data 2.575 ( 2.515) Loss 1.3415e+00 (1.3413e+00) Acc@1 100.00 ( 99.33) Acc@5 100.00 ( 99.96) Epoch: [49][ 400/1080] Time 3.064 ( 2.778) Data 2.915 ( 2.630) Loss 1.3431e+00 (1.3420e+00) Acc@1 99.22 ( 99.31) Acc@5 100.00 ( 99.96) Epoch: [49][ 600/1080] Time 2.882 ( 2.845) Data 2.729 ( 2.696) Loss 1.3618e+00 (1.3444e+00) Acc@1 100.00 ( 99.27) Acc@5 100.00 ( 99.95)
I am not sure if the model is overfitting, could you please provide clarification on reading this output logs?
I am using the VoxCeleb1 data from 2022 challenge.