<jupyter_start><jupyter_text>ResNet50 ATC * $s_n$ = 5<jupyter_code>!python _compSemiSup.py --source 'dslr' --target 'webcam' 
!python _compSemiSup.py --source 'dslr' --target 'amazon' 
!python _compSemiSup.py --source 'amazon' --target 'webcam'
!python _compSemiSup.py --source 'amazon' --target 'dslr'
!python _compSemiSup.py --source 'webcam' --target 'amazon'
 !python _compSemiSup.py --source 'webcam' --target 'dslr'<jupyter_output><empty_output><jupyter_text>AlexNet ATC * $s_n$ = 7<jupyter_code>!python _compSemiSup_Alexnet.py --source 'dslr' --target 'webcam' 
!python _compSemiSup_Alexnet.py --source 'dslr' --target 'amazon' 
!python _compSemiSup_Alexnet.py --source 'amazon' --target 'webcam'
!python _compSemiSup_Alexnet.py --source 'amazon' --target 'dslr'
!python _compSemiSup_Alexnet.py --source 'webcam' --target 'amazon'
!python _compSemiSup_Alexnet.py --source 'webcam' --target 'dslr'<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1564844587352626, 'fraction_numerical': 0.004287245444801715, 'mean_word_length': 5.397260273972603, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '402294', 'license': 'MIT', 'n_tokens_mistral': 375, 'n_tokens_neox': 363, 'n_words': 77, 'path': 'results/compSemiSup.ipynb', 'repo_name': 'ceroo1005/DATL', 'size': '933'}