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--- |
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license: mit |
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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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widget: |
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- text: 12064SAN101WAZW05 |
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- text: 11004SAN001AH01SM83 |
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- text: 11004SAN002DE02SM46 |
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- text: 11040HZG501WW01MT01 |
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- text: Stör. Tauchpumpen fest |
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base_model: bert-base-german-cased |
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model-index: |
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- name: Klassifizierung-Sanitaer |
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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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# Klassifizierung-Sanitaer |
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This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4922 |
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- F1: 0.7374 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 3.0 |
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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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| 1.4874 | 1.0 | 11 | 1.0656 | 0.6124 | |
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| 0.9892 | 2.0 | 22 | 0.6269 | 0.7374 | |
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| 0.5846 | 3.0 | 33 | 0.4922 | 0.7374 | |
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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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