
[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)

{"language": "en", "license": "apache-2.0", "datasets": ["conll2003"], "model-index": [{"name": "elastic/distilbert-base-cased-finetuned-conll03-english", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "config": "conll2003", "split": "validation"}, "metrics": [{"type": "accuracy", "value": 0.9834432212868665, "name": "Accuracy", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTZmZTJlMzUzOTAzZjg3N2UxNmMxMjQ2M2FhZTM4MDdkYzYyYTYyNjM1YjQ0M2Y4ZmIyMzkwMmY5YjZjZGVhYSIsInZlcnNpb24iOjF9.QaSLUR7AtQmE9F-h6EBueF6INQgdKwUUzS3bNvRu44rhNDY1KAJJkmDC8FeAIVMnlOSvPKvr5pOvJ59W1zckCw"}, {"type": "precision", "value": 0.9857564461012737, "name": "Precision", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDVmNmNmNWIwNTI0Yzc0YTI1NTk2NDM4YjY4NzY0ODQ4NzQ5MDQxMzYyYWM4YzUwNmYxZWQ1NTU2YTZiM2U2MCIsInZlcnNpb24iOjF9.ui_o64VBS_oC89VeQTx_B-nUUM0ZaivFyb6wNrYZcopJXvYgzptLCkARdBKdBajFjjupdhtq1VCdGbJ3yaXgBA"}, {"type": "recall", "value": 0.9882123948925569, "name": "Recall", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODg4Mzg1NTY3NjU4ZGQxOGVhMzQxNWU0ZTYxNWM2ZTg1OGZlM2U5ZGMxYTA2NzdiZjM5YWFkZjkzOGYwYTlkMyIsInZlcnNpb24iOjF9.8jHJv_5ZQp_CX3-k8-C3c5Hs4zp7bJPRTeE5SFrNgeX-FdhPv_8bHBM_DqOD2P_nkAzQ_PtEFfEokQpouZFJCw"}, {"type": "f1", "value": 0.9869828926905132, "name": "F1", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzZlOGRjMDllYWY5MjdhODk2MmNmMDk5MDQyZGYzZDYwZTE1ZDY2MDNlMzAzN2JlMmE5Y2M3ZTNkOWE2MDBjYyIsInZlcnNpb24iOjF9.VKwzPQFSbrnUZ25gkKUZvYO_xFZcaTOSkDcN-YCxksF5DRnKudKI2HmvO8l8GCsQTCoD4DiSTKzghzLMxB1jCg"}, {"type": "loss", "value": 0.07748260349035263, "name": "loss", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmVmOTQ2MWI2MzZhY2U2ODQ3YjA0ZWVjYzU1NGRlMTczZDI0NmM0OWI4YmIzMmEyYjlmNDIwYmRiODM4MWM0YiIsInZlcnNpb24iOjF9.0Prq087l2Xfh-ceS99zzUDcKM4Vr4CLM2rF1F1Fqd2fj9MOhVZEXF4JACVn0fWAFqfZIPS2GD8sSwfNYaXkZAA"}]}]}]}
transformers pytorch safetensors distilbert token-classification en dataset:conll2003 license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #en #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 


DistilBERT base cased, fine-tuned for NER using the conll03 english dataset. 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.

## Versions

- Transformers version: 4.3.1
- Datasets version: 1.3.0

## Training



After training, we update the labels to match the NER specific labels from the
dataset conll2003

## Versions

- Transformers version: 4.3.1
- Datasets version: 1.3.0 ## Training



After training, we update the labels to match the NER specific labels from the
dataset conll2003
TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #en #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ## Versions

- Transformers version: 4.3.1
- Datasets version: 1.3.0 ## Training



After training, we update the labels to match the NER specific labels from the
dataset conll2003
passage: TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #en #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
## Versions

- Transformers version: 4.3.1
- Datasets version: 1.3.0## Training



After training, we update the labels to match the NER specific labels from the
dataset conll2003