| | --- |
| | 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 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # 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 |
