Closed AndrewZhe closed 1 year ago
What deepspeed config did you use? T5 is not working fp16
also.
Sorry, it is bf16.
I use ds_flan_t5_z3_config_bf16.json
{
"bf16": {
"enabled": "auto"
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupLR",
"params": {
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto"
}
},
"zero_optimization": {
"stage": 3,
"overlap_comm": true,
"contiguous_gradients": true,
"sub_group_size": 1e9,
"reduce_bucket_size": "auto",
"stage3_prefetch_bucket_size": "auto",
"stage3_param_persistence_threshold": "auto",
"stage3_max_live_parameters": 1e9,
"stage3_max_reuse_distance": 1e9,
"stage3_gather_16bit_weights_on_model_save": false
},
"gradient_accumulation_steps": "auto",
"gradient_clipping": "auto",
"steps_per_print": 2000,
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"wall_clock_breakdown": false
}
Yes, it seems the 4x A40 GBs are insufficient to load the XXL model without offloading. I only tested 8x A100 40GBs without offloading. It seems that the activations are that big that its not fitting.
Thanks! I will try to find another 4 gpus and try it.
It is really attractive that 8 * A100 40G could use batch_size = 8 per GPU, without offloading.
I use 4 A40 48G to finetune a FLANT5-XXL, following your blog "https://www.philschmid.de/fine-tune-flan-t5-deepspeed#2-fine-tune-flan-t5-xxl-using-deepspeed". However, I met OOM with batch_size = 1 per GPU.
I use fp16 and with offload off. If I turn on the offload, I could run the code and each GPU uses 22G VM.
Do you have any suggestions?