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HuggingsaurusRex/bert-base-uncased-for-mountain-ner

Purpose

Detect mountain names in text using token classification.

Usage

from transformers import AutoModelForTokenClassification, AutoTokenizer, pipeline

# Load model and tokenizer
model = AutoModelForTokenClassification.from_pretrained('huggingsaurusRex/bert-base-uncased-for-mountain-ner')
tokenizer = AutoTokenizer.from_pretrained('huggingsaurusRex/bert-base-uncased-for-mountain-ner')

# Create NER pipeline
ner = pipeline('ner', model=model, tokenizer=tokenizer)

# Perform inference
res = ner("I spent days climbing the Mount Everest.")
print(res)

Architecture

The model is a BERT-based token classification model fine-tuned on the Few-NERD dataset.

Results

  • F1-Score: 0.87
  • Precision: 0.84
  • Recall: 0.91

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HuggingsaurusRex/bert-base-uncased-for-mountain-ner

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Model size
108M params
Tensor type
F32
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Dataset used to train huggingsaurusRex/bert-base-uncased-for-mountain-ner