<jupyter_start><jupyter_text>Load data<jupyter_code>X_train = np.load('./dataset-n15-X-train.npy')
X_valid = np.load('./dataset-n15-X-validate.npy')
y_train = np.load('./dataset-n15-y-train.npy')
y_valid = np.load('./dataset-n15-y-validate.npy')<jupyter_output><empty_output><jupyter_text>Train dataset exploring<jupyter_code>visualization.dataset_classes_summary(y_train, 'Train data', include_indels=False)<jupyter_output>Total number of data: 21877098
Number of A: 6776852
Number of C: 4175808
Number of G: 4170512
Number of T: 6753926<jupyter_text>Valid dataset exploring<jupyter_code>visualization.dataset_classes_summary(y_valid, 'Valid data', include_indels=False)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1326676176890157, 'fraction_numerical': 0.06276747503566334, 'mean_word_length': 8.616438356164384, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '400315', 'license': 'MIT', 'n_tokens_mistral': 300, 'n_tokens_neox': 264, 'n_words': 39, 'path': 'experiments/karla/diplomski-rad/blade/ont/datasets/n15-s-cerevisiae/dataset-statistics.ipynb', 'repo_name': 'lvrcek/consensus-net', 'size': '701'}