Closed DL-Practise closed 8 months ago
Hi,
In the below test with our code, we didn't observe notable differences in
--use_ema
option, and unet
folder vs. the unet_ema
folder, when training with --use_ema
.Whether to use the EMA checkpoint or not seems quite debatable [discussion link].
FID Score (lower is better) | FID↓ | train with --use_ema |
with --use_ema |
without --use_ema |
---|---|---|---|---|
iteration | eval with unet_ema |
unet |
unet |
|
5000 | 18.63 | 18.57 | 19.24 | |
10000 | 17.65 | 18.36 | 17.44 | |
20000 | 16.23 | 16.65 | 16.66 | |
30000 | 16.41 | 16.98 | 16.79 | |
40000 | 16.26 | 16.23 | 16.84 | |
50000 | 16.50 | 17.34 | 16.72 |
Inception Score (higher is better) | IS↑ | train with --use_ema |
with --use_ema |
without --use_ema |
---|---|---|---|---|
iteration | eval with unet_ema |
unet |
unet |
|
5000 | 25.04 | 25.55 | 24.53 | |
10000 | 27.64 | 27.13 | 27.13 | |
20000 | 29.14 | 28.59 | 28.59 | |
30000 | 30.19 | 29.48 | 29.75 | |
40000 | 30.49 | 30.01 | 29.78 | |
50000 | 30.71 | 30.84 | 30.49 |
CLIP Score (higher is better)
CLIP↑ | train with --use_ema |
with --use_ema |
without --use_ema |
---|---|---|---|
iteration | eval with unet_ema |
unet |
unet |
5000 | 0.2447 | 0.2446 | 0.2439 |
10000 | 0.2557 | 0.2546 | 0.2546 |
20000 | 0.2630 | 0.2622 | 0.2620 |
30000 | 0.2655 | 0.2627 | 0.2648 |
40000 | 0.2674 | 0.2647 | 0.2653 |
50000 | 0.2681 | 0.2659 | 0.2659 |
thanks for your paper and code. my question is how about the model performance when i not use the eam option. it means i didn't pass the option "--use_ema"