Comments (3)
from adan.
the loss didn't decreased very normal, looks like didn't decrease after several steps....
from adan.
Hi, @jinfagang
What is your original optimizer? Please show us the original config. Since it does not throw error from the beginning. It seems not a problem for the optimizer.
My guess is that the peak learning rate is too large. From the log, BASE_LR = 0.0015
seems fine.
If you need my help in debugging, you can add me on WeChat: xyxie_joy.
Best
from adan.
Related Issues (20)
- Training yolov5 model appears nan HOT 6
- Suggestions for applying to visual dense prediction tasks. HOT 6
- HumanEval shall not be used for training. HOT 1
- OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root. HOT 12
- Some questions about learning rate. HOT 7
- GPU type and GPU nums and total training time on Transformer-XL, GPT-2 HOT 2
- processing data for BERT experiment HOT 4
- module 'fused_adan' has no attribute 'adan_multi_tensor' HOT 1
- Gradient clipping option in DeepSpeed HOT 1
- Deepspeed Integration HOT 4
- Restarting strategy HOT 4
- Adan相比于SGD在前 74 epochs保持领先,但是后续收敛变慢,我改如何调整lr等超参数? HOT 2
- Concrete weight decay configuration for GPT-2 pretraining HOT 1
- How to implement Adan optimizer in Yolov7? HOT 1
- 在我的cnn模型中,lr=0.01时,在20-30epoch,map可以提升的很快但是后续会成为NAN。但是如果使用0.001不会直接为NAN,但是效果不好,请问这个现象代表着什么问题?谢谢! HOT 4
- Settings for instruction-tuning HOT 2
- About the pre-trained model HOT 1
- RuntimeError: The detected CUDA version (12.2) mismatches the version that was used to compile PyTorch (11.8). HOT 2
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