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improved score on ROUGE #19

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improved score on ROUGE #19

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12 changes: 8 additions & 4 deletions backend/MultiLangProject/MultiLangApp/summerizer_model_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
from pprint import pprint

# Load the test dataset
dataset = load_dataset('cnn_dailymail', '3.0.0', split='test[:10]')
dataset = load_dataset('cnn_dailymail', '3.0.0', split='test')

# Initialize the Pegasus tokenizer and model
tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-cnn_dailymail')
Expand All @@ -15,12 +15,16 @@
references = []
predictions = []
rougescore = []
alpha = 0.2
rouge = ROUGEScore()

i = 0
for example in dataset:
if i == 5:

for i in range(len(dataset)):
if i == 100:
break
if i % 10 == 0:
print("num example:",i)
example = dataset[i]
input_ids = tokenizer.encode(example['article'], truncation=True, padding='max_length', max_length=1024, return_tensors='pt')
output_ids = model.generate(input_ids, max_length=128, num_beams=4, early_stopping=True)
reference = example['highlights']
Expand Down