Training Results

[Huage001]

Dear authors,

Thanks for your excellent work in autoregressive image generation!

I try to reproduce the training of GPT-B-256 following the instruction provided here. The specific command I used is:

torchrun \
--nnodes=1 --nproc_per_node=8 --node_rank=0 \
--master_addr=127.0.0.1 --master_port=26667 \
train_c2i.py --cloud-save-path ckpt/GPT_B --code-path dataset/imagenet_code_c2i_flip_256_ten_crop/ --image-size 256 --gpt-model GPT-B 

However, after training ~150 epoch on ImageNet1k, it seems that the generated results are still meaningless:

My environment is 8xA5000 GPUs, which is different from yours (8xA100). I wonder whether the results are sensitive to such a difference, and whether the problem would be alleviated after full training (300 epochs).

Thanks for your help in advance :)