--- license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: punjabi-distilbert-ner results: [] --- # punjabi-distilbert-ner This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an [punjabi-ner](https://huggingface.co/datasets/mirfan899/punjabi-ner) dataset. It achieves the following results on the evaluation set: - Loss: 0.0787 - Precision: 0.7618 - Recall: 0.7452 - F1: 0.7534 - Accuracy: 0.9777 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.0743 | 1.0 | 807 | 0.0794 | 0.6756 | 0.7653 | 0.7176 | 0.9731 | | 0.0463 | 2.0 | 1614 | 0.0752 | 0.7545 | 0.7437 | 0.7491 | 0.9772 | | 0.0371 | 3.0 | 2421 | 0.0787 | 0.7618 | 0.7452 | 0.7534 | 0.9777 | ### Framework versions - Transformers 4.33.1 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3