Updated README.md #13

	name: model-training-evaluate
	on: [push]
	jobs:
	run:
	runs-on: [ubuntu-latest]
	container: docker://dvcorg/cml-py3:latest
	steps:
	- uses: actions/checkout@v2
	- name: 'Train and Evaluate model'
	shell: bash
	env:
	repo_token: ${{ secrets.GITHUB_TOKEN }}
	AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
	AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
	run: \|
	# Install requirements
	pip install -r requirements.txt

	# Pull data & run-cache from S3 and reproduce pipeline
	dvc pull --run-cache
	dvc repro

	# Report metrics
	echo "## Metrics" >> report.md
	git fetch --prune
	dvc metrics diff master --show-md >> report.md

	# Publish confusion matrix diff
	echo -e "## Plots\n### ROC Curve" >> report.md
	cml-publish ./results/roc_curve.png --md >> report.md
	echo -e "\n### Precision and Recall Curve" >> report.md
	cml-publish ./results/precision_recall_curve.png --md >> report.md
	cml-send-comment report.md

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