Update CI to Pharo12. Update README

pharo-ai · Dec 19, 2023 · e968246 · e968246
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diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
@@ -15,7 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        smalltalk: [ Pharo64-9.0, Pharo64-10, Pharo64-11 ]
+        smalltalk: [ Pharo64-9.0, Pharo64-10, Pharo64-11, Pharo64-12 ]
     name: ${{ matrix.smalltalk }}
     steps:
       - uses: actions/checkout@v2

diff --git a/README.md b/README.md
@@ -1,17 +1,19 @@
 [![Build status](https://github.com/pharo-ai/metrics/workflows/CI/badge.svg)](https://github.com/pharo-ai/metrics/actions/workflows/test.yml)
 [![Coverage Status](https://coveralls.io/repos/github/pharo-ai/metrics/badge.svg?branch=master)](https://coveralls.io/github/pharo-ai/metrics?branch=master)
-![License](https://img.shields.io/badge/license-MIT-blue.svg)
+[![Pharo version](https://img.shields.io/badge/Pharo-9-%23aac9ff.svg)](https://pharo.org/download)
 [![Pharo version](https://img.shields.io/badge/Pharo-10-%23aac9ff.svg)](https://pharo.org/download)
-[![Pharo version](https://img.shields.io/badge/Pharo-9.0-%23aac9ff.svg)](https://pharo.org/download)
+[![Pharo version](https://img.shields.io/badge/Pharo-11-%23aac9ff.svg)](https://pharo.org/download)
+[![Pharo version](https://img.shields.io/badge/Pharo-12-%23aac9ff.svg)](https://pharo.org/download)
+![License](https://img.shields.io/badge/license-MIT-blue.svg)
+
+# Description
 
-# Metrics for Machine Learning models
+This package is part of the Pharo AI project: It contains implementations, tests and documentation of different metrics for Machine Learning models. The evaluation metrics allows to assess how a trained Machine Learning model has performed.
 
 For more information please refer to the wiki: https://github.com/pharo-ai/wiki/blob/master/wiki/DataExploration/Metrics.md
 
 There is explained with more detail the available metrics and how to use them.
 
-This package is part of the Pharo AI project: It contains implementations, tests and documentation of different metrics for Machine Learning models. The evaluation metrics allows to assess how a trained Machine Learning model has performed.
-
 ## How to install it
 
 ```smalltalk