Instructions to use stefan-it/hmbench-ajmc-de-hmbert-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use stefan-it/hmbench-ajmc-de-hmbert-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5 with Flair:
from flair.models import SequenceTagger tagger = SequenceTagger.load("stefan-it/hmbench-ajmc-de-hmbert-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5") - Notebooks
- Google Colab
- Kaggle
| EPOCH TIMESTAMP LEARNING_RATE TRAIN_LOSS DEV_LOSS DEV_PRECISION DEV_RECALL DEV_F1 DEV_ACCURACY | |
| 1 08:50:13 0.0000 0.9886 0.2147 0.6689 0.7469 0.7057 0.5744 | |
| 2 08:50:27 0.0000 0.1748 0.1474 0.8073 0.8734 0.8391 0.7395 | |
| 3 08:50:42 0.0000 0.0982 0.1655 0.8077 0.8859 0.8450 0.7453 | |
| 4 08:50:57 0.0000 0.0777 0.1456 0.8050 0.8809 0.8412 0.7411 | |
| 5 08:51:10 0.0000 0.0580 0.1755 0.8243 0.9082 0.8642 0.7722 | |
| 6 08:51:24 0.0000 0.0463 0.1799 0.8322 0.8983 0.8640 0.7686 | |
| 7 08:51:36 0.0000 0.0353 0.1623 0.8440 0.9132 0.8772 0.7863 | |
| 8 08:51:50 0.0000 0.0287 0.1572 0.8360 0.9107 0.8717 0.7825 | |
| 9 08:52:05 0.0000 0.0245 0.1661 0.8437 0.9107 0.8759 0.7876 | |
| 10 08:52:17 0.0000 0.0205 0.1607 0.8430 0.9057 0.8732 0.7833 | |