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davanstrien/jim-crow-laws-ml-agent-kimi

sourceHugging Facecc-by-sa-4.0updated 5mo agoView on Hugging Face
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Model Card

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jim-crow-laws-ml-agent-kimi

This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1414
  • —Accuracy: 0.9748
  • —F1: 0.9561
  • —Precision: 0.9515
  • —Recall: 0.9608

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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracyF1PrecisionRecall
0.14981.0900.17460.94400.90200.90200.9020
0.11642.01800.15090.96640.94120.94120.9412
0.03773.02700.12470.97200.950.96940.9314
0.05044.03600.15470.96640.94230.92450.9608
0.04425.04500.14140.97480.95610.95150.9608

Framework versions

  • —Transformers 5.7.0
  • —Pytorch 2.11.0+cu130
  • —Datasets 4.8.5
  • —Tokenizers 0.22.2