--- license: mit base_model: MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33 tags: - generated_from_trainer pipeline_tag: zero-shot-classification widget: - text: >- Die Gemeinde Saint-Martin-de-l’Arçon liegt in den Monts de l’Espinouse im Regionalen Naturpark Haut-Languedoc, etwa 31 Kilometer nordnordwestlich von Béziers an der Mündung des Flusses Jaur in den Orb, der die Gemeinde im Süden begrenzt. candidate_labels: in Frankreich, in Deutschland, Dorf, Kleinstadt, Stadt, Großstadt multi_class: true metrics: - accuracy model-index: - name: zeroshot-classification-test4 results: [] language: - de --- # zeroshot-classification-de This model is a fine-tuned version of [MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33](https://huggingface.co/MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33) on the michaelp11/wiki-tags dataset. It achieves the following results on the evaluation set: - Loss: 0.4552 - F1 Micro: 0.859 - Accuracy: 0.859 - Precision Micro: 0.859 - Recall Micro: 0.859 ## Intended uses & limitations Zeroshot classification for german language - yay. ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| | No log | 1.0 | 313 | 0.3407 | 0.8507 | 0.851 | 0.8509 | 0.851 | 0.8534 | 0.8509 | 0.851 | 0.851 | | 0.373 | 2.0 | 626 | 0.3830 | 0.8600 | 0.86 | 0.8600 | 0.86 | 0.86 | 0.8600 | 0.86 | 0.86 | | 0.373 | 3.0 | 939 | 0.4552 | 0.8589 | 0.859 | 0.8590 | 0.859 | 0.8596 | 0.8590 | 0.859 | 0.859 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1