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merge into: s464979:master
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s464979:master
s464979:evaluation
s464979:training
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pull from: s464979:training
Branches Tags
s464979:master
s464979:evaluation
s464979:training

4 Commits
master ... training

Author SHA1 Message Date
AWieczarek
22d93bb82e IUM_06 2024-05-05 19:34:42 +02:00
AWieczarek
29e4a67c43 IUM_06 2024-05-05 19:31:29 +02:00
AWieczarek
3f4ada3b12 IUM_06 2024-05-05 19:01:35 +02:00
AWieczarek
4a468eac34 IUM_06 2024-05-05 18:56:31 +02:00
2 changed files with 14 additions and 31 deletions
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3
IUM_05-model.py
View File

@ -1,5 +1,6 @@
import pandas as pd
import tensorflow as tf
import sys
train_data = pd.read_csv('./beer_reviews_train.csv')
X_train = train_data[['review_aroma', 'review_appearance', 'review_palate', 'review_taste']]
@ -22,6 +23,6 @@ model.compile(optimizer='adam',
loss='binary_crossentropy',
metrics=['accuracy'])
model.fit(X_train_pad, y_train, epochs=40, batch_size=32, validation_split=0.1)
model.fit(X_train_pad, y_train, epochs=int(sys.argv[1]), batch_size=int(sys.argv[2]), validation_split=0.1)
model.save('beer_review_sentiment_model.h5')

42
Jenkinsfile vendored
View File

@ -1,36 +1,25 @@
pipeline {
agent any
triggers {
upstream(upstreamProjects: 'z-s464979-create-dataset', threshold: hudson.model.Result.SUCCESS)
}
parameters {
string(name: 'CUTOFF', defaultValue: '10000', description: 'Liczba wierszy do obcięcia ze zbioru danych')
string(name: 'KAGGLE_USERNAME', defaultValue: '', description: 'Kaggle username')
password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
string(name: 'EPOCHS', defaultValue: '40', description: 'Number of epochs')
string(name: 'BATCH_SIZE', defaultValue: '32', description: 'Batch size')
buildSelector(defaultSelector: lastSuccessful(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR')
}
stages {
stage('Clone Repository') {
steps {
git url: "https://git.wmi.amu.edu.pl/s464979/ium_464979"
git branch: 'training', url: "https://git.wmi.amu.edu.pl/s464979/ium_464979.git"
}
}
stage('Download dataset') {
stage('Copy Artifacts') {
steps {
withEnv(["KAGGLE_USERNAME=${env.KAGGLE_USERNAME}", "KAGGLE_KEY=${env.KAGGLE_KEY}"]) {
sh "kaggle datasets download -d thedevastator/1-5-million-beer-reviews-from-beer-advocate --unzip"
}
}
}
stage('Process and Split Dataset') {
agent {
dockerfile {
filename 'Dockerfile'
reuseNode true
}
}
steps {
sh "chmod +x ./IUM_05-split.py"
sh "python3 ./IUM_05-split.py"
archiveArtifacts artifacts: 'beer_reviews.csv,beer_reviews_train.csv,beer_reviews_test.csv', onlyIfSuccessful: true
copyArtifacts filter: 'beer_reviews.csv,beer_reviews_train.csv,beer_reviews_test.csv', projectName: 'z-s464979-create-dataset', selector: buildParameter('BUILD_SELECTOR')
}
}
stage("Run") {
@ -42,16 +31,9 @@ pipeline {
}
steps {
sh "chmod +x ./IUM_05-model.py"
sh "chmod +x ./IUM_05-predict.py"
sh "python3 ./IUM_05-model.py"
sh "python3 ./IUM_05-predict.py"
archiveArtifacts artifacts: 'beer_review_sentiment_model.h5,beer_review_sentiment_predictions.csv', onlyIfSuccessful: true
sh "python3 ./IUM_05-model.py ${params.EPOCHS} ${params.BATCH_SIZE}"
archiveArtifacts artifacts: 'beer_review_sentiment_model.h5', onlyIfSuccessful: true
}
}
}
// post {
// always {
// deleteDir()
// }
// }
}