Sentiment Analysis using BERT, DistilBERT and ALBERT (Installation)

We will do Sentiment Analysis using the code from this repo: GitHub
Note: The entire GitHub code base for this project is about 18 MB in size.
And for the first time, when you run the "server.py" from Anaconda Prompt, it downloads the BERT model of size about 450 MB.

Contents of YAML file for conda environment creation: env.yml

name: barissayil
channels:
  - defaults
  - conda-forge
  - pytorch
  
dependencies:
  - python==3.9
  - pip
  - pip:
    - transformers==4.15.0
  - pytorch
  - pandas
  - numpy
  - flask
  - flask_cors
  - scikit-learn 

Running the command in Ubuntu Terminal
(base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ conda env create -f env.yml


Collecting package metadata (repodata.json): done
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.12.0
  latest version: 4.14.0

Please update conda by running

    $ conda update -n base -c defaults conda

Downloading and Extracting Packages
numpy-base-1.23.1    | 5.6 MB    | ### | 100% 
pytz-2022.1          | 194 KB    | ### | 100% 
tzdata-2022c         | 107 KB    | ### | 100% 
numexpr-2.8.3        | 124 KB    | ### | 100% 
ninja-1.10.2         | 8 KB      | ### | 100% 
flask_cors-3.0.10    | 16 KB     | ### | 100% 
certifi-2022.9.14    | 155 KB    | ### | 100% 
libgcc-ng-11.2.0     | 5.3 MB    | ### | 100% 
scipy-1.7.1          | 16.9 MB   | ### | 100% 
setuptools-63.4.1    | 1.1 MB    | ### | 100% 
libgomp-11.2.0       | 474 KB    | ### | 100% 
numpy-1.23.1         | 11 KB     | ### | 100% 
pip-22.1.2           | 2.5 MB    | ### | 100% 
flask-2.1.3          | 130 KB    | ### | 100% 
pandas-1.4.4         | 9.8 MB    | ### | 100% 
bottleneck-1.3.5     | 115 KB    | ########### | 100% 
scikit-learn-1.1.1   | 6.1 MB    | ########### | 100% 
ninja-base-1.10.2    | 109 KB    | ########### | 100% 
python-3.9.0         | 18.1 MB   | ########### | 100% 
pyparsing-3.0.9      | 151 KB    | ########### | 100% 
typing_extensions-4. | 42 KB     | ########### | 100% 
typing-extensions-4. | 9 KB      | ########### | 100% 
_openmp_mutex-5.1    | 21 KB     | ########### | 100% 
zipp-3.8.0           | 15 KB     | ########### | 100% 
pytorch-1.10.2       | 44.1 MB   | ########### | 100% 
markupsafe-2.1.1     | 21 KB     | ########### | 100% 



cffi-1.15.1          | 228 KB    | ########### | 100% 
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

    Installed package of scikit-learn can be accelerated using scikit-learn-intelex.
    More details are available here: https://intel.github.io/scikit-learn-intelex

    For example:

        $ conda install scikit-learn-intelex
        $ python -m sklearnex my_application.py

Installing pip dependencies: - Ran pip subprocess with arguments:
['/home/ashish/anaconda3/envs/barissayil/bin/python', '-m', 'pip', 'install', '-U', '-r', '/home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt']
Pip subprocess output:
Collecting transformers==4.15.0
  Downloading transformers-4.15.0-py3-none-any.whl (3.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.4/3.4 MB 194.6 kB/s eta 0:00:00
Requirement already satisfied: numpy>=1.17 in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (1.23.1)
Collecting regex!=2019.12.17
  Downloading regex-2022.9.13-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (769 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 770.0/770.0 kB 169.9 kB/s eta 0:00:00
Collecting requests
  Downloading requests-2.28.1-py3-none-any.whl (62 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.8/62.8 kB 178.2 kB/s eta 0:00:00
Collecting huggingface-hub<1.0,>=0.1.0
  Downloading huggingface_hub-0.9.1-py3-none-any.whl (120 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 120.7/120.7 kB 128.6 kB/s eta 0:00:00
Collecting pyyaml>=5.1
  Downloading PyYAML-6.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (661 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 661.8/661.8 kB 192.7 kB/s eta 0:00:00
Requirement already satisfied: packaging>=20.0 in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (21.3)
Collecting filelock
  Downloading filelock-3.8.0-py3-none-any.whl (10 kB)

  Downloading tqdm-4.64.1-py2.py3-none-any.whl (78 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 78.5/78.5 kB 168.1 kB/s eta 0:00:00
Collecting sacremoses
  Downloading sacremoses-0.0.53.tar.gz (880 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 880.6/880.6 kB 144.4 kB/s eta 0:00:00
  Preparing metadata (setup.py): started
  Preparing metadata (setup.py): finished with status 'done'
Collecting tokenizers<0.11,>=0.10.1
  Downloading tokenizers-0.10.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.3/3.3 MB 162.9 kB/s eta 0:00:00
Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from huggingface-hub<1.0,>=0.1.0->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (4.3.0)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from packaging>=20.0->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (3.0.9)
Collecting idna<4,>=2.5
  Downloading idna-3.4-py3-none-any.whl (61 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 61.5/61.5 kB 139.1 kB/s eta 0:00:00
Collecting charset-normalizer<3,>=2
  Downloading charset_normalizer-2.1.1-py3-none-any.whl (39 kB)
Requirement already satisfied: certifi>=2017.4.17 in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from requests->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (2022.9.14)
Collecting urllib3<1.27,>=1.21.1
  Downloading urllib3-1.26.12-py2.py3-none-any.whl (140 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 140.4/140.4 kB 188.4 kB/s eta 0:00:00
Requirement already satisfied: six in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from sacremoses->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (1.16.0)
Requirement already satisfied: click in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from sacremoses->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (8.0.4)
Requirement already satisfied: joblib in /home/ashish/anaconda3/envs/barissayil/lib/python3.9/site-packages (from sacremoses->transformers==4.15.0->-r /home/ashish/Desktop/condaenv.6jfaxui9.requirements.txt (line 1)) (1.1.0)
Building wheels for collected packages: sacremoses
  Building wheel for sacremoses (setup.py): started
  Building wheel for sacremoses (setup.py): finished with status 'done'
  Created wheel for sacremoses: filename=sacremoses-0.0.53-py3-none-any.whl size=895241 sha256=3aa00715128a0c0de964dd1229c0cd2704c6ddb45ef5407c4bb3e5d273808164
  Stored in directory: /home/ashish/.cache/pip/wheels/12/1c/3d/46cf06718d63a32ff798a89594b61e7f345ab6b36d909ce033
Successfully built sacremoses
Installing collected packages: tokenizers, urllib3, tqdm, regex, pyyaml, idna, filelock, charset-normalizer, sacremoses, requests, huggingface-hub, transformers
Successfully installed charset-normalizer-2.1.1 filelock-3.8.0 huggingface-hub-0.9.1 idna-3.4 pyyaml-6.0 regex-2022.9.13 requests-2.28.1 sacremoses-0.0.53 tokenizers-0.10.3 tqdm-4.64.1 transformers-4.15.0 urllib3-1.26.12

#
# To activate this environment, use
#
#     $ conda activate barissayil
#
# To deactivate an active environment, use
#
#     $ conda deactivate 

Tags: Technology,BERT,Natural Language Processing,