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--- |
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language: |
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- de |
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license: mit |
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datasets: |
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- germeval_14 |
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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: gelectra-large-germeval_14 |
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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: germeval_14 |
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type: germeval_14 |
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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: 0.85778125349123 |
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- name: recall |
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type: recall |
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value: 0.8761839552664613 |
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- name: f1 |
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type: f1 |
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value: 0.8668849497572543 |
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- name: accuracy |
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type: accuracy |
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value: 0.976306430788049 |
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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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# gelectra-large-germeval_14 |
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This model is a fine-tuned version of [deepset/gelectra-large](https://huggingface.co/deepset/gelectra-large) on the germeval_14 dataset. |
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It achieves the following results on the evaluation set: |
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- precision: 0.8578 |
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- recall: 0.8762 |
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- f1: 0.8669 |
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- accuracy: 0.9763 |
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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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- num_train_epochs: 5 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- learning_rate: 2e-05 |
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- weight_decay_rate: 0.01 |
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- num_warmup_steps: 0 |
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- fp16: True |
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### Framework versions |
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- Transformers 4.18.0 |
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- Datasets 1.18.0 |
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- Tokenizers 0.12.1 |
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