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---
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license: mit
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base_model: dbmdz/bert-base-german-uncased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: class_classificator_results
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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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# class_classificator_results
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This model is a fine-tuned version of [dbmdz/bert-base-german-uncased](https://huggingface.co./dbmdz/bert-base-german-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7400
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- Precision: 0.9096
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- Recall: 0.9096
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- F1: 0.9096
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- Accuracy: 0.9096
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: cosine
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 1.321 | 1.0 | 2527 | 1.1812 | 0.8505 | 0.8505 | 0.8505 | 0.8505 |
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| 0.8803 | 2.0 | 5054 | 0.8872 | 0.8850 | 0.8850 | 0.8850 | 0.8850 |
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| 0.6046 | 3.0 | 7581 | 0.7477 | 0.9042 | 0.9042 | 0.9042 | 0.9042 |
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| 0.4113 | 4.0 | 10108 | 0.7400 | 0.9096 | 0.9096 | 0.9096 | 0.9096 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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