<jupyter_start><jupyter_text>loss: 2.76247<jupyter_code>pred = []
for i in range(5):
    model.load_weights('./models/DeepResUNet_%d.h5' % i)
    pred.append(model.predict(X_test.astype('float32')))
pred = np.array(pred).mean(axis=0)
submission = pd.read_csv('./data/sample_submission.csv')
submission.iloc[:,1:] = pred.reshape(-1, 14400).astype(int)
submission.to_csv('./results/Dacon_DeepResUNet_2.csv', index = False)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18666666666666668, 'fraction_numerical': 0.042222222222222223, 'mean_word_length': 6.6440677966101696, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '242214', 'license': 'MIT', 'n_tokens_mistral': 193, 'n_tokens_neox': 182, 'n_words': 19, 'path': 'ResCycleGAN.ipynb', 'repo_name': 'ataraxno/DACON_rainfall', 'size': '450'}