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I want to increase learning_rate and train_workers, is that possible? #35
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
I noticed that if I trained more than 100 times, I would get this error. I also tried searching the val.csv file in the model and only got 1726 records while my dataset had more than 20 thousand images. @pythonlessons please help me
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
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?
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
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?
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pythonlessons commentedon Oct 20, 2023
Which tutorial? Simply change these values and you good to go
nDBac14 commentedon Oct 20, 2023
I want to change the values in the config file to increase training speed, is it possible? @pythonlessons
pythonlessons commentedon Oct 20, 2023
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
nDBac14 commentedon Oct 20, 2023
This is my computer configuration, I find the train is very slow, and it can only be turned off after more than 100 trains.
pythonlessons commentedon Oct 20, 2023
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
nDBac14 commentedon Oct 20, 2023
I'm also configuring training using GPU like you. I also tried using google collab but I found it too slow @pythonlessons
pythonlessons commentedon Oct 20, 2023
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).
nDBac14 commentedon Oct 20, 2023
I can see the GPU but when I run the train it still only runs through the CPU @pythonlessons
nDBac14 commentedon Oct 21, 2023
I noticed that if I trained more than 100 times, I would get this error. I also tried searching the val.csv file in the model and only got 1726 records while my dataset had more than 20 thousand images.
@pythonlessons please help me
pythonlessons commentedon Oct 21, 2023
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
nDBac14 commentedon Oct 21, 2023
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?
nDBac14 commentedon Oct 21, 2023
this is the data in my train.csv
pythonlessons commentedon Oct 27, 2023
solved?
nDBac14 commentedon Oct 27, 2023
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
pythonlessons commentedon Oct 27, 2023
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
nDBac14 commentedon Oct 27, 2023
My captcha has 6 characters, do I need to change the model?
pythonlessons commentedon Oct 30, 2023
no, you dont
nDBac14 commentedon Nov 8, 2023
Can you solve the image pulling captcha and image rotation captcha