--- license: apache-2.0 tags: - generated_from_trainer datasets: - conll2003 model_index: - name: distilbert-base-uncased-finetuned-ner results: - task: name: Token Classification type: token-classification dataset: name: conll2003 type: conll2003 args: conll2003 --- # distilbert-base-uncased-finetuned-ner This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset. It achieves the following results on the evaluation set: - Loss: 0.0623 ## 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: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:| | 0.2377 | 1.0 | 878 | 0.0711 | | 0.0514 | 2.0 | 1756 | 0.0637 | | 0.031 | 3.0 | 2634 | 0.0623 | ### Framework versions - Transformers 4.9.0 - Pytorch 1.9.0+cu102 - Datasets 1.10.2 - Tokenizers 0.10.3