model.compile(optimizer='adam',loss='categorical_crossentropy', metrics=['accuracy'])
history = model.fit(train_data,epochs = 1,validation_data = test_data,verbose=1, callbacks =[earlystopping, csv_logger])
9/87606 [..............................] - ETA: 20:44 - loss: 0.2311 - accuracy: 0.8889
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I found this on Kaggle and it has worked for me. Just paste the code below and it should hopefully work for you too.
from IPython.display import clear_output
!pip install -q tensorflow==2.4.1
clear_output()
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