Fast ai F_beta and Precision recall same?

Part 1 (2019)
1

from fastai.vision import *

from fastai.metrics import error_rate
train=’/content/drive/My Drive/test2’
data = ImageDataBunch.from_folder(train, train=’.’, valid_pct=0.3,

                              ds_tfms=get_transforms(), size=224, num_workers=4).normalize(imagenet_stats)

from fastai.metrics import accuracy,Precision,Recall,FBeta

learn = cnn_learner(data, models.vgg16_bn, metrics=accuracy)
learn
learn.metrics=[accuracy,

           Precision(average='macro'),

           Recall(average='macro'),

           FBeta(average='macro')]

doc(learn.fit_one_cycle)
defaults.device = torch.device(‘cuda’) # makes sure the gpu is used

learn.fit_one_cycle(4)

epoch train_loss valid_loss accuracy precision recall f_beta time
0 1.193228 0.408133 0.840741 0.850517 0.840709 0.840866 02:35
1 0.816444 0.280234 0.875926 0.876151 0.876655 0.876534 00:35
2 0.685609 0.227305 0.894444 0.898285 0.895033 0.894569 00:34
3 0.570045 0.212675 0.896296 0.899135 0.896895 0.896825 00:34

this is my code please check it please tell me what my mistake…bcz i already try ‘weighted’ and ‘micro’ what i do so my precision and recall and F_beta are different please tell me…waiting for your reply