pytorch distilbert token-classification en dataset:conll2003 transformers license:apache-2.0
.gitattributes README.md config.json eval_results_ner.txt pytorch_model.bin special_tokens_map.json tokenizer_config.json train_results.txt trainer_state.json training_args.bin vocab.txt
---
language: en
license: apache-2.0
datasets:
- conll2003
---

[DistilBERT base cased](https://huggingface.co/distilbert-base-cased), fine-tuned for NER using the [conll03 english dataset](https://huggingface.co/datasets/conll2003). Note that this model is sensitive to capital letters — "english" is different than "English". For the case insensitive version, please use [elastic/distilbert-base-uncased-finetuned-conll03-english](https://huggingface.co/elastic/distilbert-base-uncased-finetuned-conll03-english).

## Versions

- Transformers version: 4.3.1
- Datasets version: 1.3.0

## Training

```
$ run_ner.py \
  --model_name_or_path distilbert-base-cased \
  --label_all_tokens True \
  --return_entity_level_metrics True \
  --dataset_name conll2003 \
  --output_dir /tmp/distilbert-base-cased-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)
