unimelb-nlp/wikiann
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How to use Gladiator/funnel-transformer-xlarge_ner_wikiann with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="Gladiator/funnel-transformer-xlarge_ner_wikiann") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("Gladiator/funnel-transformer-xlarge_ner_wikiann")
model = AutoModelForTokenClassification.from_pretrained("Gladiator/funnel-transformer-xlarge_ner_wikiann")This model is a fine-tuned version of funnel-transformer/xlarge on the wikiann 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 |
|---|---|---|---|---|---|---|---|
| 0.3193 | 1.0 | 5000 | 0.3116 | 0.8239 | 0.8296 | 0.8267 | 0.9260 |
| 0.2836 | 2.0 | 10000 | 0.2846 | 0.8446 | 0.8498 | 0.8472 | 0.9325 |
| 0.2237 | 3.0 | 15000 | 0.3258 | 0.8427 | 0.8542 | 0.8484 | 0.9332 |
| 0.1303 | 4.0 | 20000 | 0.3801 | 0.8531 | 0.8634 | 0.8582 | 0.9362 |
| 0.0867 | 5.0 | 25000 | 0.4023 | 0.8522 | 0.8634 | 0.8577 | 0.9358 |