Organization
UTD Systems Security Lab
syssec-utd
Compare the published evidence
This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Published tasks: Token classification.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.
Models
This model is a fine-tuned version of syssec-utd/py314-pylingual-v11-mlm on the syssec-utd/segmentation-py314-pylingual-v11-tokenized dataset. It achieves the following results on the evaluation set: The following hyperparameters were used during training: - learningrate: 2e-05 - trainbatchsize: 64 - evalbatchsize: 8 - distributedtype: multi-GPU - numdevices: 3 - totaltrainbatchsize: 192 - totalevalbatchsize: 24 - lrschedulertype: linear - numepochs: 2 - mixedprecisiontraining: Native AMP - Transformers 5.17.0 - Pytorch 2.14.0+cu130 - Datasets 5.0.1 - Tokenizers 0.23.2