my collect_env.py results are pretty much the same as yours.
$ python collect_env.py 
Collecting environment information...
PyTorch version: 1.6.0
Is debug build: No
CUDA used to build PyTorch: 10.2

OS: Ubuntu 18.04.3 LTS
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
CMake version: version 3.10.2

Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: 10.2.89
GPU models and configuration: GPU 0: GeForce RTX 2060
Nvidia driver version: 440.33.01
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.4

Versions of relevant libraries:
[pip3] numpy==1.16.2
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               10.2.89              hfd86e86_1  
[conda] efficientnet-pytorch      0.6.3                    pypi_0    pypi
[conda] mkl                       2019.4                      243  
[conda] mkl-service               2.3.0            py37he904b0f_0  
[conda] mkl_fft                   1.0.15           py37ha843d7b_0  
[conda] mkl_random                1.1.0            py37hd6b4f25_0  
[conda] numpy                     1.17.4           py37hc1035e2_0  
[conda] numpy-base                1.17.4           py37hde5b4d6_0  
[conda] numpydoc                  0.9.2                      py_0  
[conda] pytorch                   1.6.0           py3.7_cuda10.2.89_cudnn7.6.5_0    pytorch
[conda] torchvision               0.7.0                py37_cu102    pytorch

But as you can see I do not have this



 lostork:

[pip3] torch==1.6.0
[pip3] torchvision==0.7.0



You should maybe try and properly uninstall the pytorch you installed via pip3