Question About .csv file about mentornet HOT 10 OPEN

We first train our model for 18 epochs on the noisy dataset. Then we use the model to evaluate on another small dataset, where we have some clean labels. The model will outputs all the feature (on the small dataset) to generate the csv.

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I got it,thanks

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We first train our model for 18 epochs on the noisy dataset. Then we use the model to evaluate on another small dataset, where we have some clean labels. The model will outputs all the feature (on the small dataset) to generate the csv.

Hi，I want to make sure how the csv file is generated.You said that it pre-trained model on the nosiy dataset firstly, and then evaluate the model on the small dataset(whose size is 10 percents?). So ,the clean labels in the csv file is the true labels of clean data, while the noisy labels is the prediction of the model？Is right?

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Details are in
https://github.com/google/mentornet/blob/master/TRAINING.md

clean label column: ground-truth labels on small clean dataset
noisy label column: given labels on the current noisy dataset
loss column: loss computed using the noisy label

from mentornet.

Details are in
https://github.com/google/mentornet/blob/master/TRAINING.md

clean label column: ground-truth labels on small clean dataset
noisy label column: given labels on the current noisy dataset
loss column: loss computed using the noisy label

Sorry ,i don't quite get it. Whether if evaluating the pre-trained model on the clean and noisy dataset together? The samples whose ground-truth label and noisy label is the same comes from clean dataset, while the others come from noisy dataset. What's more, how does calculate the value in the clean label column for this noisy dataset. Is it manually annotated or prediciton of pre-trained model?

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Could you upload the files or code about the function 'provide_resnet_noisy_data' for extract resnet features in the cifa_eval.py(line 186)?

from mentornet.

Details are in
https://github.com/google/mentornet/blob/master/TRAINING.md
clean label column: ground-truth labels on small clean dataset
noisy label column: given labels on the current noisy dataset
loss column: loss computed using the noisy label

Sorry ,i don't quite get it. Whether if evaluating the pre-trained model on the clean and noisy dataset together? The samples whose ground-truth label and noisy label is the same comes from clean dataset, while the others come from noisy dataset. What's more, how does calculate the value in the clean label column for this noisy dataset. Is it manually annotated or prediciton of pre-trained model?

Have you finished the generation of the csv files? could you give me the csv file generation code. I can't found it in these files

from mentornet.

from mentornet.

We first train our model for 18 epochs on the noisy dataset. Then we use the model to evaluate on another small dataset, where we have some clean labels. The model will outputs all the feature (on the small dataset) to generate the csv.

Hi，I want to make sure how the csv file is generated.You said that it pre-trained model on the nosiy dataset firstly, and then evaluate the model on the small dataset(whose size is 10 percents?). So ,the clean labels in the csv file is the true labels of clean data, while the noisy labels is the prediction of the model？Is right?

Hi @ruirui88 , did you manage to create your csv file?

from mentornet.

Details are in
https://github.com/google/mentornet/blob/master/TRAINING.md
clean label column: ground-truth labels on small clean dataset
noisy label column: given labels on the current noisy dataset
loss column: loss computed using the noisy label

Sorry ,i don't quite get it. Whether if evaluating the pre-trained model on the clean and noisy dataset together? The samples whose ground-truth label and noisy label is the same comes from clean dataset, while the others come from noisy dataset. What's more, how does calculate the value in the clean label column for this noisy dataset. Is it manually annotated or prediciton of pre-trained model?

Have you finished the generation of the csv files? could you give me the csv file generation code. I can't found it in these files

Hi @wffzxyl , did you manage to generate the csv file? I can not reproduce the authors' results, so im afraid Im doing all the wrong way round

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