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---
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 |