CONDA small refactoring
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10
deepl.py
10
deepl.py
@ -46,11 +46,11 @@ def train(epochs):
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data = data.dropna()
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company_profile = data["company_profile"]
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# data_train, data_test = train_test_split(data, test_size=3000, random_state=1)
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# data_dev, data_test = train_test_split(data_test, test_size=1500, random_state=1)
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data_train = pd.read_csv('data_train.csv', engine='python', header=None).dropna()
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data_dev = pd.read_csv('data_dev.csv', engine='python', header=None).dropna()
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data_test = pd.read_csv('data_test.csv', engine='python', header=None).dropna()
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data_train, data_test = train_test_split(data, test_size=3000, random_state=1)
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data_dev, data_test = train_test_split(data_test, test_size=1500, random_state=1)
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# data_train = pd.read_csv('data_train.csv', engine='python', header=None).dropna()
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# data_dev = pd.read_csv('data_dev.csv', engine='python', header=None).dropna()
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# data_test = pd.read_csv('data_test.csv', engine='python', header=None).dropna()
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x_train = data_train[5]
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x_dev = data_dev[5]
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