leondz/wnut_17
Updated • 3.53k • 19
How to use muhtasham/bert-small-finetuned-xglue-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="muhtasham/bert-small-finetuned-xglue-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("muhtasham/bert-small-finetuned-xglue-ner")
model = AutoModelForTokenClassification.from_pretrained("muhtasham/bert-small-finetuned-xglue-ner", device_map="auto")This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the wnut_17 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 425 | 0.3590 | 0.6185 | 0.3433 | 0.4415 | 0.9220 |
| 0.2242 | 2.0 | 850 | 0.3638 | 0.6226 | 0.3947 | 0.4832 | 0.9245 |
| 0.1219 | 3.0 | 1275 | 0.3663 | 0.5932 | 0.3959 | 0.4749 | 0.9252 |