Hugging Face Model Card for Steel Material Classification

Model Description

This model is designed to classify steel industry materials and products based on text descriptions. It uses XLM-RoBERTa as the base model and can classify input text into 66 different steel-related categories.

Developed by: [Your Name/Organization]
Model type: Text Classification
Language(s): Korean, English (multilingual)
License: [Your License]
Finetuned from model: xlm-roberta-base

Intended Uses & Limitations

Intended Uses

This model is intended to be used for:

Classifying steel industry materials from text descriptions
Supporting LCA (Life Cycle Assessment) analysis in steel manufacturing
Automating material categorization in steel industry documentation

Limitations

The model is specifically trained for steel industry materials and may not perform well on other domains
Performance may vary with different text styles or technical terminology
The model requires Korean or English text input

Training and Evaluation Data

Training Data

The model was trained on steel industry material descriptions and technical documents, focusing on Korean and English text related to steel manufacturing processes.

Evaluation Data

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Training Results

Training Infrastructure

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Training Results

Label Independence: Good (average similarity: 0.1166)
Orthogonality: Good (average dot product: 0.2043)
Overall Assessment: The model shows good separation between different material categories

Environmental Impact

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Citation

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Glossary

LCA: Life Cycle Assessment
Steel Industry Materials: Raw materials, fuels, gases, products, and by-products used in steel manufacturing
XLM-RoBERTa: Cross-lingual language model based on RoBERTa architecture