--- 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](https://huggingface.co/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