legal-bert

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

  • Loss: 4.3914
  • Accuracy: 0.1512

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 4.0

Training results

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.0.1+cu117
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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Dataset used to train Mwnthai/pretrained-bodo-legal-bert

Evaluation results