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@ -8,7 +8,6 @@ import os
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model = tf.keras.models.load_model('model.h5')
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test_data = pd.read_csv('data.csv', sep=';')
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test_data = pd.get_dummies(test_data, columns=['Sex', 'Medal'])
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test_data = test_data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])
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@ -33,7 +32,8 @@ if os.path.exists(metrics_file):
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metrics_df = pd.read_csv(metrics_file)
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else:
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metrics_df = pd.DataFrame(columns=['top_1_accuracy', 'top_5_accuracy'])
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metrics_df = metrics_df.concat({'top_1_accuracy': np.mean(top_1_accuracy), 'top_5_accuracy': np.mean(top_5_accuracy)}, ignore_index=True)
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new_row = pd.DataFrame({'top_1_accuracy': np.mean(top_1_accuracy), 'top_5_accuracy': np.mean(top_5_accuracy)}, index=[0])
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metrics_df = pd.concat([metrics_df, new_row], ignore_index=True)
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metrics_df.to_csv(metrics_file, index=False)
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plt.figure(figsize=(10, 6))
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