README.md

metadata

library_name: transformers
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - alayaran/bodo-monolingual-dataset
metrics:
  - accuracy
model-index:
  - name: legal-bert
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: alayaran/bodo-monolingual-dataset
          type: alayaran/bodo-monolingual-dataset
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.15121982702981798

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