Text Classification
Transformers
ONNX
Safetensors
German
xlm-roberta
job-classification
german
taxonomy-main
text-embeddings-inference
Instructions to use Ashybalka/xlm-roberta-taxonomy-main-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashybalka/xlm-roberta-taxonomy-main-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashybalka/xlm-roberta-taxonomy-main-de")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashybalka/xlm-roberta-taxonomy-main-de") model = AutoModelForSequenceClassification.from_pretrained("Ashybalka/xlm-roberta-taxonomy-main-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| precision recall f1-score support | |
| Administration & Office 0.704 0.737 0.720 190 | |
| Construction & Building 0.702 0.733 0.717 90 | |
| Design & Creative 0.714 0.800 0.755 25 | |
| Education & Teaching 0.620 0.689 0.653 45 | |
| Engineering 0.788 0.769 0.778 363 | |
| Finance, Accounting & Controlling 0.778 0.755 0.766 200 | |
| General Management & Consulting 0.611 0.767 0.680 129 | |
| Healthcare & Medical 0.892 0.892 0.892 194 | |
| Hospitality, Gastronomy & Tourism 0.897 0.776 0.832 67 | |
| Human Resources 0.667 0.783 0.720 23 | |
| IT & Software 0.907 0.880 0.893 500 | |
| Insurance & Real Estate 0.819 0.907 0.861 75 | |
| Legal 0.688 0.786 0.733 14 | |
| Logistics, Transport & Warehouse 0.859 0.905 0.882 74 | |
| Marketing, Communications & PR 0.794 0.711 0.750 38 | |
| Production & Manufacturing 0.712 0.767 0.739 129 | |
| Public Sector, Security & Defense 0.695 0.725 0.710 91 | |
| Sales & Business Development 0.908 0.908 0.908 500 | |
| Science & Research 0.733 0.815 0.772 27 | |
| Skilled Trades & Crafts 0.873 0.780 0.824 431 | |
| Social Work & Care 0.826 0.826 0.826 115 | |
| accuracy 0.817 3320 | |
| macro avg 0.771 0.796 0.781 3320 | |
| weighted avg 0.822 0.817 0.819 3320 | |