Edit model card

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

Direct Link

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

Downloads last month
11
Safetensors
Model size
108M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train huggingsaurusRex/bert-base-uncased-for-mountain-ner