RoBERTa for Multilabel Language Classification
Training
RoBERTa fine-tuned on small parts of Open Subtitles, Oscar and Tatoeba datasets (~9k samples per language).
Implemented heuristic algorithm for multilingual training data creation - https://github.com/n1kstep/lang-classifier
| data source | language |
|---|---|
| open_subtitles | ka, he, en, de |
| oscar | be, kk, az, hu |
| tatoeba | ru, uk |
Validation
The metrics obtained from validation on the another part of dataset (~1k samples per language).
| Training Loss | Validation Loss | F1-Score | Roc Auc | Accuracy | Support |
|---|---|---|---|---|---|
| 0.161500 | 0.110949 | 0.947844 | 0.953939 | 0.762063 | 26858 |
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.