--- license: apache-2.0 tags: - generated_from_trainer datasets: - conll2003 metrics: - precision - recall - f1 - accuracy base_model: distilbert-base-cased model-index: - name: distilbert-base-cased-ner results: - task: type: token-classification name: Token Classification dataset: name: conll2003 type: conll2003 config: conll2003 split: validation args: conll2003 metrics: - type: precision value: 0.932077342588002 name: Precision - type: recall value: 0.9491753618310333 name: Recall - type: f1 value: 0.940548653381139 name: F1 - type: accuracy value: 0.984782480720551 name: Accuracy - task: type: token-classification name: Token Classification dataset: name: conll2003 type: conll2003 config: conll2003 split: test metrics: - type: accuracy value: 0.8975276153858275 name: Accuracy verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjA4OTdkZGZhOGVjNzUxMTExZTIxOTBhN2ExYmU0ZGE3MmFmZGYwZjhhMzExYjgwYjljMTg1YzJkMjk2NzVmYyIsInZlcnNpb24iOjF9.4QqmAwmUTNJlRnQiukdI23SNjKa6ZC9K6GBuuVuELeUueYI5R1tP58WYtNglr9BHWqhj1NuqeRNJSa7VFP0dDg - type: precision value: 0.9258126323573902 name: Precision verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2ZmZTAwZTBmZGNkODM2NTk3NjkyMTZmOGVhOGM0MDY1YzVlMTdkYjkwMTU3YzI4ODNhZDMyMTM5N2M4YjhjNCIsInZlcnNpb24iOjF9.ybM6lA3dtYn6sFT70ocFeAxLGoMUcXedGx2YeVz58VQt0g2WqhCsHm6MOeTH1W33zgaYF7thcEoT6zOEr8PzBw - type: recall value: 0.9132871306827602 name: Recall verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjM0ZTY5NTQzYWI2ZGQzOWU1YjQ1MjhjYjVjNzllYzE5MjE3MTI2ODY2NzQzOWIwMjJiODIxNTJiYWI3MDg0YyIsInZlcnNpb24iOjF9.8nEFuGWTjzFButONIeft0c9pSrdxkNTNxwlyr76tqu3B9VSRdSCswauC2d5ccTXqrNBljmMa8CixqwlVwEj2CQ - type: auc value: NaN name: AUC verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWMwY2Q2MGY4ODM2NTdlYjQ0OTI3ZmYyYjYyYTk3ZmNjMTRmYTZjYWFjOTg2NGI2NGZkNGQxZmRiNGU0N2VhYyIsInZlcnNpb24iOjF9.15J6CBL2SyWfraaDRfA80qptuANH89eQzrpnYKoNLyysmblllMwJxJWzQdMEHRveLOXgpNYjdurAZSFy7p0KCA - type: f1 value: 0.9195072279905185 name: F1 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTZmMTgwZDc2M2ZhMWE5MjMxZDVmOWViNjI3MTM0MTJjMWE5ZTU1NDJhNjRmMTE1NmVlZGY1NmVkODBlNGZiYSIsInZlcnNpb24iOjF9.OoKpemZwjZKioOj4fTNAnJHHBBdOlTHyNIEKWTLfuHcIiqJwYZ_VQ9LyEGPrN9YsgDkM-NiIWaEKkdi4Ww15Dw - type: loss value: 0.8574212193489075 name: loss verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGVhYzFhMzEzOWM4NDJmN2QwZjRmMjYxNjY1MjczNzEzZTZhYzY1YzhjMzg1MjdjODgyNjE2YTRhMzcyMzhiMiIsInZlcnNpb24iOjF9.jfXLq-DE6HVYMC43QoxmTFKmCS7uSKxJYr0lJMu8Z7dKOfv9P4Py1cJG1GWcsdlGjlfVPvGq3pZ1Ofu8uao5BA --- # distilbert-base-cased-ner This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the conll2003 dataset. It achieves the following results on the evaluation set: - Loss: 0.1088 - Precision: 0.9321 - Recall: 0.9492 - F1: 0.9405 - Accuracy: 0.9848 ## 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: 8 - eval_batch_size: 8 - seed: 2147483647 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.1015 | 1.0 | 1756 | 0.1001 | 0.8858 | 0.9167 | 0.9010 | 0.9740 | | 0.049 | 2.0 | 3512 | 0.0803 | 0.8993 | 0.9273 | 0.9131 | 0.9798 | | 0.0327 | 3.0 | 5268 | 0.0794 | 0.9199 | 0.9350 | 0.9274 | 0.9821 | | 0.0237 | 4.0 | 7024 | 0.0880 | 0.9050 | 0.9344 | 0.9194 | 0.9813 | | 0.0131 | 5.0 | 8780 | 0.0849 | 0.9178 | 0.9446 | 0.9310 | 0.9837 | | 0.0073 | 6.0 | 10536 | 0.0975 | 0.9166 | 0.9446 | 0.9304 | 0.9838 | | 0.0044 | 7.0 | 12292 | 0.0965 | 0.9267 | 0.9475 | 0.9370 | 0.9842 | | 0.0015 | 8.0 | 14048 | 0.1075 | 0.9273 | 0.9463 | 0.9367 | 0.9843 | | 0.0011 | 9.0 | 15804 | 0.1089 | 0.9317 | 0.9480 | 0.9398 | 0.9847 | | 0.0006 | 10.0 | 17560 | 0.1088 | 0.9321 | 0.9492 | 0.9405 | 0.9848 | ### Framework versions - Transformers 4.27.4 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3