
## Model information:
distilbert-base-uncased model finetuned using the conll2003 dataset from the datasets library. 

## Intended uses & limitations
This model is intended to be used for named entity recoginition tasks. The model will identify entities of persons, locations, organisations, and miscellaneous.  The model will predict lables based upon the CoNLL-2003 dataset.

Note that the dataset and model may not be fully represetative or suitable for all needs it is recommended that the paper for the dataset and base model card should be reviewed before using the model - 
- [CoNLL-2003](https://aclanthology.org/W03-0419)
- [distilbert](https://huggingface.co/distilbert-base-uncased)


## How to use 
Load the model from the library using the following checkpoints:
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("sarahmiller137/distilbert-base-uncased-ft-conll2003")
model = AutoModel.from_pretrained("sarahmiller137/distilbert-base-uncased-ft-conll2003")
```




{"language": "en", "license": "cc", "tags": ["token classification"], "datasets": "conll2003", "model-index": [{"name": "sarahmiller137/distilbert-base-uncased-ft-conll2003", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "config": "conll2003", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.9750189904012154, "name": "Accuracy", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDE2ODAzNGQ2YjZjMjczODhjOTdkZmQ1YjM2YzQzZTUxYmRhNTBkMWI0ZWE3YjhjNzA2MTFkNjFlZWY2NzI4ZSIsInZlcnNpb24iOjF9.IA4HRZlyYTEaowTUwjDXaPl3RghaHkFcfgcin3dQK8iD8NN_9hqGOgawyuObrHEnXjSnYhDs-gFGwTZSIDErBg"}, {"type": "precision", "value": 0.9802152215150602, "name": "Precision", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjkxZjE5YTQ3MTVhZGEwMjVlMWJjODFiN2MzNTc0ZmM0Mjk0ZDU0YmFlZDgxMzQ4MTJmMzk5MjUxMjAwODJjMiIsInZlcnNpb24iOjF9.kZwo2mx4NegRFGaecaxGzoRvdk2TiN-A1oo0lhkce7AGORYh7hc_XeEuwoA9A8O5LIKtaHOtTcsuRrv0BLuUAA"}, {"type": "recall", "value": 0.9803021169462076, "name": "Recall", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWM4MjM3NmMxZDc3ZDI1ZjM2MGE2MGNmYTJkOWU5Njc3Y2JkOWM3MWMxMTlkNTBlYmQ3ZDMxNjQxMjNkZDAzOSIsInZlcnNpb24iOjF9.qvJiBb2vAPaLh-OJ9DsYggvpgysSFWcpAoO2jcBWT4S5PeCjjHTkEWuF_O_g63vyBO2Jmhw8-hqA5Uv3pJTqDA"}, {"type": "f1", "value": 0.9802586673049137, "name": "F1", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWIzY2MxZTU3ZTJjMTgzNWMyMGYzZTFjOGVhMzkwNzZiMThmZGQxMmVjZGE4ODcxZjRhZDRhOGY3YWM5NmRmNCIsInZlcnNpb24iOjF9.m-RwJI0tLT_l9VMP23Ko_DOwIKKPMdA7FOqOenXRICzWzeHJgEYzKu-9nPse2SXherPyUYfuRrMmIT876yIjAw"}, {"type": "loss", "value": 0.10723897069692612, "name": "loss", "verified": true, "verifyToken": "eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTlkZWI2YzMzNDhkNGQzMzhlYzkzY2VjYmIyZTI3MjQxMDg1ODZmOTg3ZjJkOTliZTFlMDdjOGQ2NjAxMzk5NiIsInZlcnNpb24iOjF9.hS4GKzSkG7sXWEarilb0Jc8vhZjFauJBuIUuycw23HkWKhBfIW-0F7lxDoOH8rgRqJh821VxZiNi4J3LQJlDBg"}]}]}]}
transformers pytorch safetensors distilbert token-classification token classification en dataset:conll2003 license:cc model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #token classification #en #dataset-conll2003 #license-cc #model-index #autotrain_compatible #endpoints_compatible #region-us 


## Model information:
distilbert-base-uncased model finetuned using the conll2003 dataset from the datasets library. 

## Intended uses & limitations
This model is intended to be used for named entity recoginition tasks. The model will identify entities of persons, locations, organisations, and miscellaneous.  The model will predict lables based upon the CoNLL-2003 dataset.

Note that the dataset and model may not be fully represetative or suitable for all needs it is recommended that the paper for the dataset and base model card should be reviewed before using the model - 
- CoNLL-2003
- distilbert


## How to use 
Load the model from the library using the following checkpoints:





## Model information:
distilbert-base-uncased model finetuned using the conll2003 dataset from the datasets library. ## Intended uses & limitations
This model is intended to be used for named entity recoginition tasks. The model will identify entities of persons, locations, organisations, and miscellaneous.  The model will predict lables based upon the CoNLL-2003 dataset.

Note that the dataset and model may not be fully represetative or suitable for all needs it is recommended that the paper for the dataset and base model card should be reviewed before using the model - 
- CoNLL-2003
- distilbert ## How to use 
Load the model from the library using the following checkpoints:
TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #token classification #en #dataset-conll2003 #license-cc #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ## Model information:
distilbert-base-uncased model finetuned using the conll2003 dataset from the datasets library. ## Intended uses & limitations
This model is intended to be used for named entity recoginition tasks. The model will identify entities of persons, locations, organisations, and miscellaneous.  The model will predict lables based upon the CoNLL-2003 dataset.

Note that the dataset and model may not be fully represetative or suitable for all needs it is recommended that the paper for the dataset and base model card should be reviewed before using the model - 
- CoNLL-2003
- distilbert ## How to use 
Load the model from the library using the following checkpoints:
passage: TAGS
#transformers #pytorch #safetensors #distilbert #token-classification #token classification #en #dataset-conll2003 #license-cc #model-index #autotrain_compatible #endpoints_compatible #region-us 
## Model information:
distilbert-base-uncased model finetuned using the conll2003 dataset from the datasets library.## Intended uses & limitations
This model is intended to be used for named entity recoginition tasks. The model will identify entities of persons, locations, organisations, and miscellaneous.  The model will predict lables based upon the CoNLL-2003 dataset.

Note that the dataset and model may not be fully represetative or suitable for all needs it is recommended that the paper for the dataset and base model card should be reviewed before using the model - 
- CoNLL-2003
- distilbert## How to use 
Load the model from the library using the following checkpoints: