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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- wikiann
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model-index:
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- name: ner-bert-german
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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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# ner-bert-german
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2450
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- Overall Precision: 0.8767
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- Overall Recall: 0.8893
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- Overall F1: 0.8829
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- Overall Accuracy: 0.9606
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- Loc F1: 0.9067
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- Org F1: 0.8278
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- Per F1: 0.9152
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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: linear
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- num_epochs: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Loc F1 | Org F1 | Per F1 |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------:|:------:|:------:|
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| 0.252 | 0.8 | 1000 | 0.1724 | 0.8422 | 0.8368 | 0.8395 | 0.9501 | 0.8702 | 0.7593 | 0.8921 |
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| 0.1376 | 1.6 | 2000 | 0.1679 | 0.8388 | 0.8607 | 0.8497 | 0.9528 | 0.8814 | 0.7712 | 0.8971 |
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| 0.0982 | 2.4 | 3000 | 0.1880 | 0.8631 | 0.8598 | 0.8614 | 0.9564 | 0.8847 | 0.7915 | 0.9070 |
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| 0.0681 | 3.2 | 4000 | 0.1956 | 0.8599 | 0.8775 | 0.8686 | 0.9574 | 0.8905 | 0.8084 | 0.9097 |
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| 0.0477 | 4.0 | 5000 | 0.2115 | 0.8738 | 0.8814 | 0.8776 | 0.9593 | 0.9003 | 0.8207 | 0.9144 |
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| 0.031 | 4.8 | 6000 | 0.2274 | 0.8751 | 0.8826 | 0.8788 | 0.9598 | 0.9017 | 0.8246 | 0.9115 |
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| 0.0229 | 5.6 | 7000 | 0.2317 | 0.8715 | 0.8888 | 0.8801 | 0.9598 | 0.9061 | 0.8208 | 0.9145 |
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| 0.0181 | 6.4 | 8000 | 0.2450 | 0.8767 | 0.8893 | 0.8829 | 0.9606 | 0.9067 | 0.8278 | 0.9152 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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