--- library_name: transformers license: cc-by-sa-4.0 base_model: nlpaueb/legal-bert-base-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: legal_ai_India_ner_results results: [] datasets: - opennyaiorg/InLegalNER --- # legal_ai_India_ner_results This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the opennyaiorg/InLegalNER dataset. It achieves the following results on the evaluation set: - Loss: 0.1057 - Precision: 0.8370 - Recall: 0.8742 - F1: 0.8552 - Accuracy: 0.9741 ## 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 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.4633 | 1.0 | 917 | 0.1226 | 0.7624 | 0.8040 | 0.7827 | 0.9642 | | 0.1039 | 2.0 | 1834 | 0.1077 | 0.7996 | 0.8583 | 0.8279 | 0.9702 | | 0.0686 | 3.0 | 2751 | 0.1021 | 0.8054 | 0.8695 | 0.8362 | 0.9714 | | 0.048 | 4.0 | 3668 | 0.1084 | 0.8309 | 0.8706 | 0.8503 | 0.9732 | | 0.0368 | 5.0 | 4585 | 0.1057 | 0.8370 | 0.8742 | 0.8552 | 0.9741 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/678a4e12ad4940dca8954255/TIq5P3LGF7q51EuWa7s3k.png)