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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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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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base_model: bert-base-german-cased |
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model-index: |
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- name: bert-base-german-cased-own-data-ner |
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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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# bert-base-german-cased-own-data-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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0535 |
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- Precision: 0.7134 |
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- Recall: 0.8536 |
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- F1: 0.7772 |
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- Accuracy: 0.9895 |
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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: 5e-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: 10 |
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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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| No log | 0.8 | 32 | 0.0308 | 0.7593 | 0.8 | 0.7791 | 0.9917 | |
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| No log | 1.6 | 64 | 0.0342 | 0.7756 | 0.8393 | 0.8062 | 0.9911 | |
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| No log | 2.4 | 96 | 0.0457 | 0.7764 | 0.8679 | 0.8196 | 0.9906 | |
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| No log | 3.2 | 128 | 0.0383 | 0.7524 | 0.8464 | 0.7966 | 0.9911 | |
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| No log | 4.0 | 160 | 0.0420 | 0.7539 | 0.8536 | 0.8007 | 0.9907 | |
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| No log | 4.8 | 192 | 0.0535 | 0.7134 | 0.8536 | 0.7772 | 0.9895 | |
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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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