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# 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
[Add citation information]
## 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