anonymouspd / SecureBERT-APTNER

huggingface.co
Total runs: 6
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: December 17 2023
token-classification

Introduction of SecureBERT-APTNER

Model Details of SecureBERT-APTNER

anonymouspd/SecureBERT-APTNER

This model is a fine-tuned version of ehsanaghaei/SecureBERT on the APTNER dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2915
  • Precision: 0.5392
  • Recall: 0.5871
  • F1: 0.5621
  • Accuracy: 0.9211

It achieves the following results on the prediction set:

  • Loss: 0.2404
  • Precision: 0.6277
  • Recall: 0.6450
  • F1: 0.6362
  • Accuracy: 0.9367
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10.0
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.8252 0.59 500 0.3771 0.4383 0.4413 0.4398 0.9112
0.3593 1.19 1000 0.2915 0.5392 0.5871 0.5621 0.9211
0.2704 1.78 1500 0.2949 0.5480 0.6201 0.5818 0.9203
0.2308 2.37 2000 0.2988 0.5524 0.6269 0.5873 0.9187
0.1934 2.97 2500 0.3123 0.5365 0.6515 0.5884 0.9152
0.1567 3.56 3000 0.3128 0.5702 0.6404 0.6033 0.9210
0.1471 4.15 3500 0.3651 0.5379 0.6243 0.5779 0.9117
0.1249 4.74 4000 0.3771 0.5363 0.6566 0.5904 0.9125
0.1106 5.34 4500 0.3866 0.5624 0.6341 0.5961 0.9156
0.1063 5.93 5000 0.3754 0.5731 0.6371 0.6034 0.9191
0.0835 6.52 5500 0.4015 0.5551 0.6428 0.5957 0.9165
0.0854 7.12 6000 0.4325 0.5461 0.6425 0.5904 0.9138
0.0743 7.71 6500 0.4184 0.5642 0.6473 0.6029 0.9179
0.0704 8.3 7000 0.4315 0.5613 0.6323 0.5947 0.9172
0.06 8.9 7500 0.4354 0.5635 0.6401 0.5994 0.9176
0.0612 9.49 8000 0.4452 0.5643 0.6452 0.6020 0.9179
Framework versions
  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1

Runs of anonymouspd SecureBERT-APTNER on huggingface.co

6
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs

More Information About SecureBERT-APTNER huggingface.co Model

More SecureBERT-APTNER license Visit here:

https://choosealicense.com/licenses/bigscience-openrail-m

SecureBERT-APTNER huggingface.co

SecureBERT-APTNER huggingface.co is an AI model on huggingface.co that provides SecureBERT-APTNER's model effect (), which can be used instantly with this anonymouspd SecureBERT-APTNER model. huggingface.co supports a free trial of the SecureBERT-APTNER model, and also provides paid use of the SecureBERT-APTNER. Support call SecureBERT-APTNER model through api, including Node.js, Python, http.

SecureBERT-APTNER huggingface.co Url

https://huggingface.co/anonymouspd/SecureBERT-APTNER

anonymouspd SecureBERT-APTNER online free

SecureBERT-APTNER huggingface.co is an online trial and call api platform, which integrates SecureBERT-APTNER's modeling effects, including api services, and provides a free online trial of SecureBERT-APTNER, you can try SecureBERT-APTNER online for free by clicking the link below.

anonymouspd SecureBERT-APTNER online free url in huggingface.co:

https://huggingface.co/anonymouspd/SecureBERT-APTNER

SecureBERT-APTNER install

SecureBERT-APTNER is an open source model from GitHub that offers a free installation service, and any user can find SecureBERT-APTNER on GitHub to install. At the same time, huggingface.co provides the effect of SecureBERT-APTNER install, users can directly use SecureBERT-APTNER installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

SecureBERT-APTNER install url in huggingface.co:

https://huggingface.co/anonymouspd/SecureBERT-APTNER

Url of SecureBERT-APTNER

SecureBERT-APTNER huggingface.co Url

Provider of SecureBERT-APTNER huggingface.co

anonymouspd
ORGANIZATIONS

Other API from anonymouspd