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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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datasets: |
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- germa_ner |
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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: bert-base-german-cased-fine-tuned-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: germa_ner |
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type: germa_ner |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8089260808926081 |
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- name: Recall |
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type: recall |
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value: 0.872836719337848 |
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- name: F1 |
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type: f1 |
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value: 0.8396670285921101 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9748511630761677 |
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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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# bert-base-german-cased-fine-tuned-ner |
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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 germa_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0966 |
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- Precision: 0.8089 |
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- Recall: 0.8728 |
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- F1: 0.8397 |
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- Accuracy: 0.9749 |
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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: 32 |
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- eval_batch_size: 32 |
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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 |
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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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| 0.159 | 1.0 | 737 | 0.0922 | 0.7472 | 0.8461 | 0.7936 | 0.9703 | |
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| 0.0714 | 2.0 | 1474 | 0.0916 | 0.7886 | 0.8713 | 0.8279 | 0.9731 | |
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| 0.0319 | 3.0 | 2211 | 0.0966 | 0.8089 | 0.8728 | 0.8397 | 0.9749 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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