Upload README.md

README.md

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+---
+base_model: bert-base-uncased
+tags:
+- safety
+- occupational-safety
+- bert
+- domain-adaptation
+---
+
+# 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