| language: en | |
| license: apache-2.0 | |
| datasets: | |
| - conll2003 | |
| model-index: | |
| - name: elastic/distilbert-base-uncased-finetuned-conll03-english | |
| results: | |
| - task: | |
| type: token-classification | |
| name: Token Classification | |
| dataset: | |
| name: conll2003 | |
| type: conll2003 | |
| config: conll2003 | |
| split: validation | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9854480753649896 | |
| verified: true | |
| - name: Precision | |
| type: precision | |
| value: 0.9880928983228512 | |
| verified: true | |
| - name: Recall | |
| type: recall | |
| value: 0.9895677847945542 | |
| verified: true | |
| - name: F1 | |
| type: f1 | |
| value: 0.9888297915932504 | |
| verified: true | |
| - name: loss | |
| type: loss | |
| value: 0.06707527488470078 | |
| verified: true | |
| [DistilBERT base uncased](https://huggingface.co/distilbert-base-uncased), fine-tuned for NER using the [conll03 english dataset](https://huggingface.co/datasets/conll2003). Note that this model is **not** sensitive to capital letters — "english" is the same as "English". For the case sensitive version, please use [elastic/distilbert-base-cased-finetuned-conll03-english](https://huggingface.co/elastic/distilbert-base-cased-finetuned-conll03-english). | |
| ## Versions | |
| - Transformers version: 4.3.1 | |
| - Datasets version: 1.3.0 | |
| ## Training | |
| ``` | |
| $ run_ner.py \ | |
| --model_name_or_path distilbert-base-uncased \ | |
| --label_all_tokens True \ | |
| --return_entity_level_metrics True \ | |
| --dataset_name conll2003 \ | |
| --output_dir /tmp/distilbert-base-uncased-finetuned-conll03-english \ | |
| --do_train \ | |
| --do_eval | |
| ``` | |
| After training, we update the labels to match the NER specific labels from the | |
| dataset [conll2003](https://raw.githubusercontent.com/huggingface/datasets/1.3.0/datasets/conll2003/dataset_infos.json) | |