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bert-base-german-cased-gnad10

Text Classification Transformers PyTorch Safetensors
German bert german-news-classification Eval Results Inference Endpoints
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bert-base-german-cased-gnad10 / README.md
mathieu
Add evaluation results on the default config and train split of gnad10 (#2)
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metadata
language:
  - de
tags:
  - text-classification
  - german-news-classification
datasets:
  - gnad10
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: Mathking/bert-base-german-cased-gnad10
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: gnad10
          type: gnad10
          config: default
          split: train
        metrics:
          - type: accuracy
            value: 0.9557598702001082
            name: Accuracy
            verified: true
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          - type: f1
            value: 0.9550736462647613
            name: F1 Macro
            verified: true
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          - type: f1
            value: 0.9557598702001082
            name: F1 Micro
            verified: true
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          - type: f1
            value: 0.9556789875763837
            name: F1 Weighted
            verified: true
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          - type: precision
            value: 0.953834169384936
            name: Precision Macro
            verified: true
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          - type: precision
            value: 0.9557598702001082
            name: Precision Micro
            verified: true
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          - type: precision
            value: 0.9558822798145145
            name: Precision Weighted
            verified: true
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          - type: recall
            value: 0.956651983810566
            name: Recall Macro
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          - type: recall
            value: 0.9557598702001082
            name: Recall Micro
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          - type: recall
            value: 0.9557598702001082
            name: Recall Weighted
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          - type: loss
            value: 0.17337004840373993
            name: loss
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German BERT for News Classification

This a bert-base-german-cased model finetuned for text classification on german news articles

Training data

Used the training set from the 10KGNAD dataset (gnad10 on HuggingFace Datasets).