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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Maltehb/danish-bert-botxo](https://huggingface.co/Maltehb/danish-bert-botxo) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6686
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- - Accuracy: 0.7583
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  ## Model description
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@@ -42,22 +42,27 @@ The following hyperparameters were used during training:
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 42 | 0.7139 | 0.7644 |
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- | No log | 2.0 | 84 | 0.6871 | 0.7613 |
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- | No log | 3.0 | 126 | 0.6712 | 0.7613 |
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- | 0.745 | 4.0 | 168 | 0.6700 | 0.7583 |
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- | 0.745 | 5.0 | 210 | 0.6686 | 0.7583 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.28.1
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  - Pytorch 2.0.0+cu118
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- - Datasets 2.11.0
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  - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [Maltehb/danish-bert-botxo](https://huggingface.co/Maltehb/danish-bert-botxo) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4956
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+ - Accuracy: 0.6737
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  ## Model description
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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 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 42 | 1.3370 | 0.6707 |
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+ | No log | 2.0 | 84 | 1.4095 | 0.6798 |
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+ | No log | 3.0 | 126 | 1.4965 | 0.6707 |
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+ | 0.077 | 4.0 | 168 | 1.4925 | 0.6798 |
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+ | 0.077 | 5.0 | 210 | 1.4526 | 0.6647 |
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+ | 0.077 | 6.0 | 252 | 1.4712 | 0.6737 |
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+ | 0.0593 | 7.0 | 294 | 1.4944 | 0.6707 |
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+ | 0.0593 | 8.0 | 336 | 1.4980 | 0.6677 |
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+ | 0.0593 | 9.0 | 378 | 1.4897 | 0.6707 |
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+ | 0.0646 | 10.0 | 420 | 1.4956 | 0.6737 |
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  ### Framework versions
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+ - Transformers 4.28.0
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  - Pytorch 2.0.0+cu118
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+ - Datasets 2.12.0
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  - Tokenizers 0.13.3