distilroberta-base-ner-wikiann

This model is a fine-tuned version of distilroberta-base on the wikiann dataset.

eval F1-Score: 83,78 test F1-Score: 83,76

Model Usage

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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Select AutoNLP in the “Train” menu to fine-tune this model automatically.

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Evaluation results