Historical Entities Models
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5 items • Updated
How to use emanuelaboros/chrono-link-bert-topres19th-ner with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="emanuelaboros/chrono-link-bert-topres19th-ner") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("emanuelaboros/chrono-link-bert-topres19th-ner")
model = AutoModelForTokenClassification.from_pretrained("emanuelaboros/chrono-link-bert-topres19th-ner")This model is a fine-tuned version of emanuelaboros/chrono-link-bert-americanstories-1850-1890 on the None 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 |
|---|---|---|---|---|---|---|
| 0.0555 | 1.0 | 368 | 0.0369 | 0.6835 | 0.8085 | 0.7407 |
| 0.0340 | 2.0 | 736 | 0.0377 | 0.7209 | 0.7915 | 0.7546 |
| 0.0189 | 3.0 | 1104 | 0.0402 | 0.7077 | 0.8553 | 0.7746 |
| 0.0093 | 4.0 | 1472 | 0.0481 | 0.7510 | 0.8340 | 0.7903 |
| 0.0043 | 5.0 | 1840 | 0.0495 | 0.7569 | 0.8213 | 0.7878 |
Base model
google-bert/bert-base-cased