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bert-base-german-cased-20000-ner

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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0368
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- - Precision: 0.8221
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- - Recall: 0.875
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- - F1: 0.8478
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- - Accuracy: 0.9920
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  ## Model description
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@@ -54,15 +54,27 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 0.1 | 64 | 0.0427 | 0.7796 | 0.8714 | 0.8229 | 0.9893 |
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- | No log | 0.19 | 128 | 0.0472 | 0.5471 | 0.85 | 0.6657 | 0.9831 |
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- | No log | 0.29 | 192 | 0.0384 | 0.7897 | 0.8179 | 0.8035 | 0.9899 |
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- | No log | 0.38 | 256 | 0.0488 | 0.4970 | 0.8786 | 0.6348 | 0.9793 |
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- | No log | 0.48 | 320 | 0.0412 | 0.7548 | 0.8464 | 0.7980 | 0.9895 |
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- | No log | 0.58 | 384 | 0.0437 | 0.8373 | 0.8821 | 0.8591 | 0.9914 |
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- | No log | 0.67 | 448 | 0.0399 | 0.7727 | 0.85 | 0.8095 | 0.9899 |
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- | 0.0914 | 0.77 | 512 | 0.0394 | 0.7859 | 0.8786 | 0.8297 | 0.9899 |
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- | 0.0914 | 0.86 | 576 | 0.0368 | 0.8221 | 0.875 | 0.8478 | 0.9920 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0826
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+ - Precision: 0.8904
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+ - Recall: 0.8693
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+ - F1: 0.8797
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+ - Accuracy: 0.9832
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 0.11 | 64 | 0.0840 | 0.8076 | 0.7842 | 0.7957 | 0.9752 |
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+ | No log | 0.23 | 128 | 0.0787 | 0.8119 | 0.7735 | 0.7922 | 0.9746 |
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+ | No log | 0.34 | 192 | 0.0677 | 0.8264 | 0.8362 | 0.8313 | 0.9794 |
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+ | No log | 0.45 | 256 | 0.0630 | 0.8440 | 0.8125 | 0.8280 | 0.9801 |
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+ | No log | 0.57 | 320 | 0.0664 | 0.8035 | 0.8391 | 0.8209 | 0.9782 |
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+ | No log | 0.68 | 384 | 0.0674 | 0.8850 | 0.8285 | 0.8558 | 0.9819 |
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+ | No log | 0.79 | 448 | 0.0631 | 0.8834 | 0.8598 | 0.8714 | 0.9825 |
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+ | 0.094 | 0.9 | 512 | 0.0572 | 0.8933 | 0.8462 | 0.8691 | 0.9832 |
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+ | 0.094 | 1.02 | 576 | 0.0728 | 0.8520 | 0.8681 | 0.8600 | 0.9795 |
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+ | 0.094 | 1.13 | 640 | 0.0784 | 0.8496 | 0.8717 | 0.8605 | 0.9800 |
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+ | 0.094 | 1.24 | 704 | 0.0721 | 0.8868 | 0.8527 | 0.8695 | 0.9814 |
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+ | 0.094 | 1.36 | 768 | 0.0700 | 0.8755 | 0.8362 | 0.8554 | 0.9808 |
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+ | 0.094 | 1.47 | 832 | 0.0590 | 0.8662 | 0.8610 | 0.8636 | 0.9822 |
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+ | 0.094 | 1.58 | 896 | 0.0615 | 0.8692 | 0.8764 | 0.8728 | 0.9821 |
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+ | 0.094 | 1.7 | 960 | 0.0670 | 0.8812 | 0.8557 | 0.8683 | 0.9826 |
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+ | 0.0413 | 1.81 | 1024 | 0.0623 | 0.9061 | 0.8557 | 0.8802 | 0.9843 |
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+ | 0.0413 | 1.92 | 1088 | 0.0570 | 0.8891 | 0.8770 | 0.8830 | 0.9833 |
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+ | 0.0413 | 2.04 | 1152 | 0.0643 | 0.8859 | 0.8859 | 0.8859 | 0.9831 |
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+ | 0.0413 | 2.15 | 1216 | 0.0705 | 0.8824 | 0.8740 | 0.8782 | 0.9830 |
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+ | 0.0413 | 2.26 | 1280 | 0.0698 | 0.8818 | 0.8557 | 0.8685 | 0.9824 |
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+ | 0.0413 | 2.37 | 1344 | 0.0826 | 0.8904 | 0.8693 | 0.8797 | 0.9832 |
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  ### Framework versions