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I want to increase learning_rate and train_workers, is that possible? #35
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Which tutorial? Simply change these values and you good to go |
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it really depends on your machine, if your GPU is used 100% batch size and workers number will not help, then you need to change model architecture or input size or other stuff |
So, you are training model on CPU. That's why it takes a lot of time. You should train it on GPU, if you don't have one try to use google collab and try training on free GPU |
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I am configuring only ram, not reserving all possible GPU ram, you need to make sure your system can see GPU device (install drivers, CUDA, cuDNN). |
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You received this error, because you try to convert model to onnx, but your GPU is too old to support it. You need to convert it manually using cpu onnx version. Your 20k images dataset should be split into train and validation, check how much data you had in your train.csv |
I checked that the train runs entirely on CPU and not on GPU. I tried print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU'))) returned = 0, is there any way to fix it? fix this error? |
solved? |
oh no friend. I have fixed the error and trained with GPU, but when I train I am encountering an Early stopping error. I will train again and send you specific images. Hope you will help me |
Early stopping is not an error, its a function, if you model is not learning enough, increase early stopping patience, try playing around with learning rate or even model. Maybe you images are hard to crack |
My captcha has 6 characters, do I need to change the model? |
no, you dont |
Can you solve the image pulling captcha and image rotation captcha |
@pythonlessons please help me
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