Hi@oddlamaI'm curious, did your training performance increase when using the AdamW fused? I tried it on the latest nightly and noticed a drop in performance. thanks! Fused AdamW Non-fused AdamW So this indeed seems to be an issue with pytorch nightly. It was hard to find anything related...
But then I realized that makes total sense because, in the process of reclassifying the training datasets, I had some images that ended up being all in background class (I had no building in those images and all pixels are in 0 value ). Thus, I removed those images from my train and...
I understand that you are encountering an issue where the training loss is "NaN", causing the training to stop.To debug the issue please refer to the following steps: Enable verbose output in your training options to get more detailed information about each training step. Verify that your MATL...
https://discuss.pytorch.org/t/training-loss-is-decreasing-while-validation-loss-is-nan/48207 1.
ValiLoss:nanTestLoss:nanTraininglossis decreasing while validationlossisNaNhttps://discuss.pytorch.org/t/training-loss-is-decreasing-while Test 原创 emanlee 2023-10-31 14:21:02 96阅读 神经网络训练loss为nan原因神经网络画loss图 在训练神经网络的过程中往往要定时记录Loss的值,以便查看训练过程和方便调参...
Evaluation metric is a metric “we want” to minimize or maximize through the modeling process, while loss function is a metric “the model will” minimize through the model training. ... Loss function isthe quantity which the model will minimize over the training. It is also called as cost...
Hi, I want to use focal loss to train ssd, and I change the ssd code, but the loss is always nan. the file I change is below: in ssd_head.py: ` def loss_single(self, cls_score, bbox_pred, labels, label_weights, bbox_targets, bbox_weights, num_total_samples, cfg): # loss...
最近新换了工作,以后的工作内容会和大模型相关,所以先抽空跑了一下chatGLM2-6b的demo,使用Qlora或lora微调模型 今天简单写个文档记录一下,顺便也是一个简单的教程,并且踩了qlora loss变成nan训练不稳定的问题 本教程并没有写lora的原理,需要的话自行查阅 1.chatG
This MATLAB function computes loss between the predicted states and the actual states while training the Motion Planning Networks (MPNet).
意味着在训练神经网络模型时,使用了Huber损失函数作为优化目标。Huber损失函数是一种平滑的损失函数,能够更好地处理异常值的影响,相比于均方差损失函数(MSE),Huber损失函数对异常值更加鲁棒...