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adanish91/
safetybert

Name: safetybert
Availability: InStock

google-bert/bert-base-uncased

finetune

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SafetyBERT

SafetyBERT is a BERT model fine-tuned on occupational safety data from MSHA, OSHA, NTSB, and other safety organizations, as well as a large corpus of occupational safety-related Abstracts.

Quick Start

python

from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
model = AutoModelForMaskedLM.from_pretrained("adanish91/safetybert")

# Example usage
text = "The worker failed to wear proper [MASK] equipment."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)

Model Details

Base Model: bert-base-uncased
Parameters: 110M
Training Data: 2.4M safety documents from multiple sources
Specialization: Mining, construction, transportation safety

Performance

Significantly outperforms BERT-base on safety classification tasks:

76.9% improvement in pseudo-perplexity
Superior performance on Occupational safety-related downstream tasks

Applications

Safety document analysis
Incident report classification