# 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

[Add information about evaluation data]

## Training Results

### Training Infrastructure

[Add training infrastructure details]

### 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

[Add environmental impact information]

## 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