<jupyter_start><jupyter_text><jupyter_code>!unzip /content/drive/MyDrive/fingerveinrecognition.zip
%cd /content/fingerveinrecognition/fingerveinrecognition-37
!tar zxvf /content/drive/MyDrive/FV-USM-processed.tgz
!pip install ptflops
%%shell 

bash /content/fingerveinrecognition/fingerveinrecognition-37/run.sh<jupyter_output>Namespace(batch_size=4, dataset='FVUSM', feature_dim=128, gamma_cos=1.0, gamma_tri=1.0, hard_margin=0.2, k=4, log_interval=10, loss='tripletCosface', lr=0.01, lr_decay=0.1, lr_fc=0.1, m=0.2, max_epoch=60, momentum=0.9, network='resnet18', openset=True, p=8, plot=False, pretrained=True, s=15.0, seed=1, wd=0.0005)
Namespace(batch_size=4, dataset='FVUSM', feature_dim=128, gamma_cos=1.0, gamma_tri=6.0, hard_margin=0.2, k=4, log_interval=10, loss='tripletCosface', lr=0.01, lr_decay=0.1, lr_fc=0.1, m=0.2, max_epoch=60, momentum=0.9, network='resnet18', openset=True, p=8, plot=False, pretrained=True, s=15.0, seed=1, wd=0.0005)
02:11:15 Training started.
02:11:15 Epoch:[0]-[0/92] batchLoss:9.4815(cosface:8.7543, triplet:0.7272) averLoss:9.4815 batchAcc:0.00% averAcc:0.00%, numTriplet:86
02:11:16 Epoch:[0]-[10/92] batchLoss:9.5274(cosface:8.8618, triplet:0.6656) averLoss:9.3982 batchAcc:0.00% averAcc:0.28%, numTriplet:73
02:11:16 Epoch:[0]-[20/92] batchLoss:9.1601(cosface:8.5206, triplet:0.6394[...]
{'fraction_non_alphanumeric': 0.18215892053973012, 'fraction_numerical': 0.14167916041979012, 'mean_word_length': 7.782894736842105, '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': '32237', 'license': 'MIT', 'n_tokens_mistral': 699, 'n_tokens_neox': 597, 'n_words': 81, 'path': 'FVR.ipynb', 'repo_name': 'lady0528/Face-Track-Detect-Extract', 'size': '1334'}