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---
license: apache-2.0
tags:
- token-classification
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilroberta-base-ner-wikiann
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: wikiann
type: wikiann
metrics:
- type: precision
value: 0.8331921416757433
name: Precision
- type: recall
value: 0.84243586083126
name: Recall
- type: f1
value: 0.8377885044416501
name: F1
- type: accuracy
value: 0.91930707459758
name: Accuracy
- task:
type: token-classification
name: Token Classification
dataset:
name: wikiann
type: wikiann
config: en
split: test
metrics:
- type: accuracy
value: 0.9200373733433721
name: Accuracy
verified: true
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- type: precision
value: 0.9258482820953792
name: Precision
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzFhNGJlMzk0N2JmYmU3YjAxZjJjNGFjZjZjOTJhODc3MjQyODMzYzE2Y2Y4NWQ4YThhMjg3NWI1MGRmODczMiIsInZlcnNpb24iOjF9.eVTQJqXeGY0XZaGURXBrT8sjMl7O_SxuFB4NS7C6jbpr46MMZdusvzkmndOIrGjReB2vB3sAmpcT0hydpqRkDg
- type: recall
value: 0.9347545055892119
name: Recall
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2Y5ZGIzM2JlOWNjZGUzOWU5MGIwOTFiODM4NmU3NGQ3ZmUxYzM4ZmYxNjIwOTE0ZWFiYWJhMzk4NDg4ZjI3MSIsInZlcnNpb24iOjF9.tzl3gTEDFuj7kpGsERkQzXfh7B0Qwao31VcXKF1rSvf3ulVgXsU-vTB2oZiGr3w5AySr_80J0pIpSpvGzfhNAQ
- type: f1
value: 0.9302800779500893
name: F1
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjY5MDM2ZWQ1MzJmNDFhMGFmZmQ1MzM0NmJmOTVmYTM1OWZmNzc4YWI4ZWUwMTFlMTQ5MTJmYWRhNmVmZTUyZCIsInZlcnNpb24iOjF9.zMUq4ZGLfu0eQF7lHNkaf6LByypIevygVGLpBA3jW80OUy5VeZDK7d6q0RV_N4SO5gTkLEjoDvSqLDcaw-9VBw
- type: loss
value: 0.3007512390613556
name: loss
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzI5YmIxODFkN2NkYzJkZDgyZTc4MDhlMDkyMzM3NWFiZWQ1MmUzMDA1MGYyM2RlNzVlNTIwNDcwNTFmNjYwMSIsInZlcnNpb24iOjF9.D8vx5YhoNHY4CdRXEt3rL95odR2kZJ1e_c34HD28xX9YeWKIjjt4E0FSz6Xw4ufJd9UlCnQ_u4VPFTYI-RXlCQ
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilroberta-base-ner-wikiann
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the wikiann dataset.
eval F1-Score: **83,78**
test F1-Score: **83,76**
## Model Usage
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("philschmid/distilroberta-base-ner-wikiann")
model = AutoModelForTokenClassification.from_pretrained("philschmid/distilroberta-base-ner-wikiann")
nlp = pipeline("ner", model=model, tokenizer=tokenizer, grouped_entities=True)
example = "My name is Philipp and live in Germany"
nlp(example)
```
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4.9086903597787154e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
### Training results
It achieves the following results on the evaluation set:
- Loss: 0.3156
- Precision: 0.8332
- Recall: 0.8424
- F1: 0.8378
- Accuracy: 0.9193
It achieves the following results on the test set:
- Loss: 0.3023
- Precision: 0.8301
- Recall: 0.8452
- F1: 0.8376
- Accuracy: 0.92
### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.6.2
- Tokenizers 0.10.2
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