scales-okn / ontology-arrest

huggingface.co
Total runs: 4
24-hour runs: 0
7-day runs: 0
30-day runs: -19
Model's Last Updated: August 06 2026
text-classification

Introduction of ontology-arrest

Model Details of ontology-arrest

ontology-arrest

This model is a fine-tuned version of scales-okn/docket-language-model on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0000
  • Accuracy: 1.0
  • F1: 1.0
  • Precision: 1.0
  • Recall: 1.0
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: 3e-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 5
Training results
Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.0006 0.62 95 0.0003 1.0 1.0 1.0 1.0
0.0004 1.25 190 0.0002 1.0 1.0 1.0 1.0
0.0001 1.88 285 0.0001 1.0 1.0 1.0 1.0
0.0001 2.5 380 0.0001 1.0 1.0 1.0 1.0
0.0001 3.12 475 0.0000 1.0 1.0 1.0 1.0
0.0001 3.75 570 0.0000 1.0 1.0 1.0 1.0
0.0001 4.38 665 0.0000 1.0 1.0 1.0 1.0
0.0001 5.0 760 0.0000 1.0 1.0 1.0 1.0
Framework versions
  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0
Public release information

This model is released by the SCALES Open Knowledge Network under the GNU General Public License v3.0. It is derived from scales-okn/docket-language-model and is intended for research and development involving legal-document classification or information extraction. It is not legal advice.

The organization has reviewed the release decision and confirmed that the model's training data and resulting weights are legally and ethically releasable. Users are responsible for evaluating accuracy, bias, privacy, and fitness for their own use.

The repository includes PyTorch .bin artifacts. Hugging Face's server-side security scan reported no file issues before publication. As with any serialized model artifact, load it only with maintained libraries and in an appropriately isolated environment.

Runs of scales-okn ontology-arrest on huggingface.co

4
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
-19
30-day runs

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https://choosealicense.com/licenses/gpl-3.0

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https://huggingface.co/scales-okn/ontology-arrest

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https://huggingface.co/scales-okn/ontology-arrest

ontology-arrest install

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

ontology-arrest install url in huggingface.co:

https://huggingface.co/scales-okn/ontology-arrest

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