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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: legal-german-roberta-base |
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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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# legal-german-roberta-base |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7080 |
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- Accuracy: 0.8387 |
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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: 0.0001 |
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- train_batch_size: 1024 |
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- eval_batch_size: 512 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- training_steps: 1000000 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:-------:|:--------:|:---------------:| |
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| 2.1008 | 0.05 | 50000 | 0.6533 | 2.0523 | |
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| 1.5248 | 0.1 | 100000 | 0.7661 | 1.1575 | |
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| 1.3152 | 0.15 | 150000 | 0.7674 | 1.1281 | |
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| 1.1239 | 0.2 | 200000 | 0.7971 | 0.9458 | |
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| 0.9472 | 0.25 | 250000 | 0.7876 | 0.9979 | |
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| 0.961 | 0.3 | 300000 | 0.8075 | 0.8798 | |
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| 1.0179 | 0.35 | 350000 | 0.8018 | 0.9102 | |
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| 1.037 | 0.4 | 400000 | 0.8195 | 0.8107 | |
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| 1.1206 | 0.45 | 450000 | 0.8152 | 0.8323 | |
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| 1.0865 | 0.5 | 500000 | 0.8242 | 0.7829 | |
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| 0.9616 | 0.55 | 550000 | 0.8224 | 0.7895 | |
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| 0.7727 | 0.6 | 600000 | 0.8285 | 0.7585 | |
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| 0.9871 | 1.04 | 650000 | 0.8320 | 0.7391 | |
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| 1.0679 | 1.09 | 700000 | 0.8311 | 0.7436 | |
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| 0.9203 | 1.14 | 750000 | 0.8355 | 0.7187 | |
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| 0.9626 | 1.19 | 800000 | 0.8353 | 0.7242 | |
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| 0.7263 | 1.24 | 850000 | 0.7094 | 0.8378 | |
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| 0.8578 | 1.29 | 900000 | 0.7140 | 0.8368 | |
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| 0.7693 | 1.34 | 950000 | 0.7091 | 0.8377 | |
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| 1.0488 | 1.39 | 1000000 | 0.7080 | 0.8387 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 2.8.0 |
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- Tokenizers 0.12.1 |
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