eriktks/conll2003
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How to use hamza666/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="hamza666/bert-finetuned-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("hamza666/bert-finetuned-ner")
model = AutoModelForTokenClassification.from_pretrained("hamza666/bert-finetuned-ner")This model is a fine-tuned version of bert-base-cased on an eriktks/conll2003. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 0.1708 | 0.0641 | 0 |
| 0.0476 | 0.0559 | 1 |
| 0.0285 | 0.0555 | 2 |
Base model
google-bert/bert-base-cased