eriktks/conll2003
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How to use geckos/distilbert-base-uncased-fine-tuned-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="geckos/distilbert-base-uncased-fine-tuned-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("geckos/distilbert-base-uncased-fine-tuned-ner")
model = AutoModelForTokenClassification.from_pretrained("geckos/distilbert-base-uncased-fine-tuned-ner")This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2459 | 1.0 | 878 | 0.0696 | 0.9117 | 0.9195 | 0.9156 | 0.9808 |
| 0.0513 | 2.0 | 1756 | 0.0602 | 0.9223 | 0.9376 | 0.9299 | 0.9835 |
| 0.0304 | 3.0 | 2634 | 0.0606 | 0.9303 | 0.9380 | 0.9342 | 0.9842 |