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update model card README.md

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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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+ model-index:
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+ - name: bert-base-german-cased-noisy-pretrain-fine-tuned
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+ results: []
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+ ---
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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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+
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+ # bert-base-german-cased-noisy-pretrain-fine-tuned
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+
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+ This model is a fine-tuned version of [tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData](https://huggingface.co/tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2925
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+ - Precision: 0.7933
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+ - Recall: 0.7457
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+ - F1: 0.7688
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+ - Accuracy: 0.9147
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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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: 7
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 33 | 0.3093 | 0.7456 | 0.6029 | 0.6667 | 0.8808 |
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+ | No log | 2.0 | 66 | 0.2587 | 0.7774 | 0.7286 | 0.7522 | 0.9078 |
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+ | No log | 3.0 | 99 | 0.2529 | 0.7775 | 0.7686 | 0.7730 | 0.9136 |
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+ | No log | 4.0 | 132 | 0.2598 | 0.8063 | 0.7257 | 0.7639 | 0.9147 |
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+ | No log | 5.0 | 165 | 0.2783 | 0.7927 | 0.7429 | 0.7670 | 0.9159 |
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+ | No log | 6.0 | 198 | 0.2899 | 0.8019 | 0.74 | 0.7697 | 0.9165 |
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+ | No log | 7.0 | 231 | 0.2925 | 0.7933 | 0.7457 | 0.7688 | 0.9147 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.1
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+ - Tokenizers 0.12.1