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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: rlt |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# rlt |
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This model is a fine-tuned version of [svalabs/gbert-large-zeroshot-nli](https://huggingface.co/svalabs/gbert-large-zeroshot-nli) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0381 |
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- F1: 0.9901 |
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## Label-Übersetzungen |
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- 0 Abluft |
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- 1 Abluftfilter |
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- 2 Abluftventilator |
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- 3 Andere |
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- 4 Aussenluftklappe |
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- 5 Befeuchter |
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- 6 Brandschutz |
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- 7 Brandschutzklappe |
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- 8 Erhitzer |
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- 9 Kühler |
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- 10 Nacherhitzer |
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- 11 RLT_Anlage |
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- 12 Raum |
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- 13 Ventilator |
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- 14 Vorerhitzer |
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- 15 Wärmerückgewinnung |
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- 16 Zuluft |
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- 17 Zuluftuftfilter |
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- 18 Zuluftventilator |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 0.99 | 36 | 1.7080 | 0.4733 | |
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| No log | 1.99 | 72 | 0.3576 | 0.9228 | |
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| No log | 2.99 | 108 | 0.1345 | 0.9689 | |
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| No log | 3.99 | 144 | 0.0519 | 0.9883 | |
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| No log | 4.99 | 180 | 0.0410 | 0.9917 | |
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| No log | 5.99 | 216 | 0.0633 | 0.9881 | |
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| No log | 6.99 | 252 | 0.0398 | 0.9932 | |
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| No log | 7.99 | 288 | 0.0415 | 0.9897 | |
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| No log | 8.99 | 324 | 0.0424 | 0.9901 | |
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| No log | 9.99 | 360 | 0.0381 | 0.9901 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.5.1 |
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- Tokenizers 0.12.1 |
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