<jupyter_start><jupyter_text>2017-11-26 Axel (1060)%run src/run_train.py --train annotated_images --label_names annotated_images/_labels.json --iteration 10000 --val_iteration 1000 --loaderjob 4 --batchsize 7 --log_iteration 10 --gpu 0<jupyter_code>import numpy as np
import matplotlib.pyplot as plt
%run src/visualize_bb.py testing_images/set1/ss1.jpg --pretrained_model ../backup/2017-11-26_model/model_iter_1000 --label_names ../backup/2017-11-26_model/_labels.txt<jupyter_output>([array([], shape=(0, 4), dtype=float32)], [array([], dtype=int32)], [array([], dtype=float32)])
{'fraction_non_alphanumeric': 0.15889464594127806, 'fraction_numerical': 0.09671848013816926, 'mean_word_length': 5.590909090909091, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, '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': '652352', 'license': 'MIT', 'n_tokens_mistral': 251, 'n_tokens_neox': 204, 'n_words': 41, 'path': '2017-11-26 Axel (1060).ipynb', 'repo_name': 'MLPRA/evaluation', 'size': '579'}