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Isotonic
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deberta-v3-base_finetuned_ai4privacy_v2

Token Classification
Transformers
ONNX
Safetensors
English
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
3
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  1. README.md +58 -58
  2. all_results.json +58 -58
  3. eval_results.json +53 -53
  4. train_results.json +5 -5
  5. trainer_state.json +502 -544
README.md CHANGED
@@ -15,67 +15,67 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0424
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- - Overall Precision: 0.9550
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- - Overall Recall: 0.9680
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- - Overall F1: 0.9614
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- - Overall Accuracy: 0.9818
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- - Accountname F1: 0.9965
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  - Accountnumber F1: 1.0
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- - Age F1: 0.9676
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- - Amount F1: 0.9897
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- - Bic F1: 0.9868
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- - Bitcoinaddress F1: 0.9926
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- - Buildingnumber F1: 0.9818
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- - City F1: 0.9968
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- - Companyname F1: 0.9979
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- - County F1: 1.0
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- - Creditcardcvv F1: 1.0
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  - Creditcardissuer F1: 0.9964
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- - Creditcardnumber F1: 0.9631
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- - Currency F1: 0.8896
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  - Currencycode F1: 0.9949
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- - Currencyname F1: 0.7481
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  - Currencysymbol F1: 0.9984
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- - Date F1: 0.9609
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- - Dob F1: 0.9160
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- - Email F1: 1.0
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  - Ethereumaddress F1: 1.0
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- - Eyecolor F1: 0.9608
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- - Firstname F1: 0.9908
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- - Gender F1: 0.9988
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- - Height F1: 0.9925
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- - Iban F1: 0.9974
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- - Ip F1: 0.2177
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- - Ipv4 F1: 0.8145
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- - Ipv6 F1: 0.7835
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- - Jobarea F1: 0.9831
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- - Jobtitle F1: 0.9992
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- - Jobtype F1: 0.9899
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- - Lastname F1: 0.9643
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- - Litecoinaddress F1: 0.9815
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  - Mac F1: 1.0
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- - Maskednumber F1: 0.9590
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- - Middlename F1: 0.4375
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  - Nearbygpscoordinate F1: 1.0
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- - Ordinaldirection F1: 0.4
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- - Password F1: 0.9960
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  - Phoneimei F1: 0.9961
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- - Phonenumber F1: 0.9978
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- - Pin F1: 0.9814
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- - Prefix F1: 0.9807
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- - Secondaryaddress F1: 0.9989
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- - Sex F1: 0.9783
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- - Ssn F1: 0.9950
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- - State F1: 0.9923
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- - Street F1: 0.9968
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- - Time F1: 0.9862
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  - Url F1: 1.0
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- - Useragent F1: 0.9975
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  - Username F1: 1.0
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  - Vehiclevin F1: 1.0
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  - Vehiclevrm F1: 0.9929
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- - Zipcode F1: 0.9943
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  ## Model description
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@@ -95,8 +95,8 @@ More information needed
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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: 8
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- - eval_batch_size: 8
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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_with_restarts
@@ -107,13 +107,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Accountname F1 | Accountnumber F1 | Age F1 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Companyname F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Dob F1 | Email F1 | Ethereumaddress F1 | Eyecolor F1 | Firstname F1 | Gender F1 | Height F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Nearbygpscoordinate F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phonenumber F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Ssn F1 | State F1 | Street F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
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- | 0.2542 | 1.0 | 1070 | 0.1744 | 0.7933 | 0.8151 | 0.8040 | 0.9469 | 0.9734 | 0.9011 | 0.8465 | 0.8807 | 0.5502 | 0.7683 | 0.8006 | 0.6202 | 0.8908 | 0.8431 | 0.0 | 0.8100 | 0.6975 | 0.5052 | 0.0 | 0.0 | 0.7156 | 0.8292 | 0.3902 | 0.9907 | 0.9810 | 0.4808 | 0.8015 | 0.8076 | 0.9744 | 0.9529 | 0.0 | 0.8335 | 0.7879 | 0.0 | 0.9365 | 0.0 | 0.0 | 0.0 | 0.9355 | 0.0890 | 0.0 | 1.0 | 0.0 | 0.9670 | 0.9882 | 0.9706 | 0.7341 | 0.8914 | 0.9112 | 0.0851 | 0.9072 | 0.6932 | 0.7065 | 0.9543 | 0.9939 | 0.9667 | 0.8542 | 0.9642 | 0.0184 | 0.7480 |
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- | 0.1494 | 2.0 | 2140 | 0.1213 | 0.8470 | 0.8747 | 0.8606 | 0.9590 | 0.9832 | 0.8908 | 0.9126 | 0.5531 | 0.9419 | 0.7910 | 0.7723 | 0.8919 | 0.9175 | 0.9560 | 0.0 | 0.9858 | 0.8649 | 0.6121 | 0.8738 | 0.0 | 0.9287 | 0.8676 | 0.5886 | 0.9882 | 0.9873 | 0.8319 | 0.9381 | 0.8815 | 0.9744 | 0.9580 | 0.0 | 0.8388 | 0.8040 | 0.0 | 0.9355 | 0.6122 | 0.5918 | 0.1882 | 0.9908 | 0.7311 | 0.0 | 0.9967 | 0.0 | 0.9440 | 0.9738 | 0.9257 | 0.7566 | 0.9015 | 0.9467 | 0.8776 | 0.9010 | 0.6753 | 0.9297 | 0.9021 | 0.9836 | 0.9637 | 0.9585 | 0.9451 | 0.9417 | 0.6969 |
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- | 0.1008 | 3.0 | 3210 | 0.0728 | 0.9038 | 0.9222 | 0.9129 | 0.9708 | 0.9773 | 0.9091 | 0.9144 | 0.8619 | 0.9610 | 0.9546 | 0.9023 | 0.9711 | 0.9906 | 0.8943 | 0.3889 | 0.9680 | 0.8853 | 0.7540 | 0.9239 | 0.0633 | 0.9665 | 0.8906 | 0.6993 | 0.9987 | 0.9905 | 0.9804 | 0.9640 | 0.9763 | 0.7631 | 0.9724 | 0.0 | 0.8374 | 0.8081 | 0.6087 | 0.9882 | 0.8649 | 0.5698 | 0.8708 | 0.9931 | 0.8410 | 0.0 | 1.0 | 0.0 | 0.9858 | 0.9921 | 0.9903 | 0.8889 | 0.9173 | 0.9897 | 0.9263 | 0.9042 | 0.8811 | 0.9503 | 0.9836 | 0.9965 | 0.9692 | 0.9847 | 0.9584 | 0.9763 | 0.9171 |
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- | 0.0793 | 4.0 | 4280 | 0.0675 | 0.9356 | 0.9446 | 0.9401 | 0.9742 | 0.9894 | 0.9810 | 0.9608 | 0.9825 | 0.9539 | 0.9633 | 0.9435 | 0.9881 | 0.9793 | 0.9894 | 0.8462 | 0.9893 | 0.9303 | 0.8391 | 0.9694 | 0.4124 | 0.9922 | 0.8978 | 0.7260 | 0.9975 | 0.9968 | 0.9804 | 0.9757 | 0.9834 | 0.9925 | 0.9949 | 0.0 | 0.8325 | 0.8106 | 0.8333 | 0.9899 | 0.9495 | 0.7368 | 0.9086 | 1.0 | 0.9003 | 0.0 | 1.0 | 0.0 | 0.9919 | 0.9934 | 0.9913 | 0.9556 | 0.9338 | 0.9943 | 0.9474 | 0.9888 | 0.9788 | 0.9915 | 0.9699 | 0.9948 | 0.9778 | 0.9898 | 0.9752 | 0.9835 | 0.9559 |
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- | 0.0656 | 5.0 | 5350 | 0.0469 | 0.9524 | 0.9588 | 0.9556 | 0.9780 | 0.9965 | 0.9965 | 0.9626 | 0.9866 | 0.9770 | 0.9789 | 0.9657 | 0.9935 | 0.9958 | 0.9970 | 0.9655 | 0.9964 | 0.9432 | 0.8342 | 0.9744 | 0.6977 | 0.9938 | 0.9382 | 0.8596 | 1.0 | 1.0 | 0.9608 | 0.9822 | 0.9941 | 0.9925 | 0.9949 | 0.1360 | 0.8390 | 0.8003 | 0.9333 | 0.9992 | 0.98 | 0.9157 | 0.9570 | 1.0 | 0.9361 | 0.0 | 1.0 | 0.4 | 0.9828 | 0.9921 | 0.9978 | 0.9814 | 0.9652 | 0.9989 | 0.9574 | 0.9938 | 0.9923 | 0.9957 | 0.9766 | 0.9991 | 0.9975 | 0.9983 | 0.9944 | 0.9976 | 0.9765 |
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- | 0.057 | 6.0 | 6420 | 0.0448 | 0.9595 | 0.9662 | 0.9628 | 0.9803 | 0.9965 | 1.0 | 0.9582 | 0.9897 | 0.9836 | 0.9851 | 0.9833 | 0.9978 | 0.9979 | 0.9985 | 1.0 | 0.9964 | 0.9581 | 0.8956 | 0.9949 | 0.7294 | 0.9984 | 0.9524 | 0.8848 | 1.0 | 1.0 | 0.9608 | 0.9886 | 0.9988 | 0.9925 | 0.9974 | 0.1663 | 0.8377 | 0.8195 | 0.9123 | 0.9992 | 0.9608 | 0.9556 | 0.9563 | 1.0 | 0.9527 | 0.2857 | 1.0 | 0.4 | 0.9960 | 0.9961 | 0.9978 | 0.9852 | 0.9798 | 0.9989 | 0.9783 | 0.9975 | 0.9942 | 0.9979 | 0.9807 | 1.0 | 0.9975 | 1.0 | 0.9808 | 0.9929 | 0.9932 |
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- | 0.0455 | 7.0 | 7490 | 0.0424 | 0.9550 | 0.9680 | 0.9614 | 0.9818 | 0.9965 | 1.0 | 0.9676 | 0.9897 | 0.9868 | 0.9926 | 0.9818 | 0.9968 | 0.9979 | 1.0 | 1.0 | 0.9964 | 0.9631 | 0.8896 | 0.9949 | 0.7481 | 0.9984 | 0.9609 | 0.9160 | 1.0 | 1.0 | 0.9608 | 0.9908 | 0.9988 | 0.9925 | 0.9974 | 0.2177 | 0.8145 | 0.7835 | 0.9831 | 0.9992 | 0.9899 | 0.9643 | 0.9815 | 1.0 | 0.9590 | 0.4375 | 1.0 | 0.4 | 0.9960 | 0.9961 | 0.9978 | 0.9814 | 0.9807 | 0.9989 | 0.9783 | 0.9950 | 0.9923 | 0.9968 | 0.9862 | 1.0 | 0.9975 | 1.0 | 1.0 | 0.9929 | 0.9943 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
17
  It achieves the following results on the evaluation set:
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+ - Loss: 0.0101
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+ - Overall Precision: 0.9818
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+ - Overall Recall: 0.9871
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+ - Overall F1: 0.9844
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+ - Overall Accuracy: 0.9965
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+ - Accountname F1: 1.0
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  - Accountnumber F1: 1.0
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+ - Age F1: 0.9951
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+ - Amount F1: 1.0
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+ - Bic F1: 1.0
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+ - Bitcoinaddress F1: 0.9915
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+ - Buildingnumber F1: 0.9969
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+ - City F1: 1.0
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+ - Companyname F1: 1.0
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+ - County F1: 0.9985
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+ - Creditcardcvv F1: 0.9831
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  - Creditcardissuer F1: 0.9964
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+ - Creditcardnumber F1: 0.9889
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+ - Currency F1: 0.9678
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  - Currencycode F1: 0.9949
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+ - Currencyname F1: 0.9266
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  - Currencysymbol F1: 0.9984
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+ - Date F1: 0.9895
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+ - Dob F1: 0.9774
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+ - Email F1: 0.9776
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  - Ethereumaddress F1: 1.0
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+ - Eyecolor F1: 1.0
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+ - Firstname F1: 1.0
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+ - Gender F1: 0.9976
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+ - Height F1: 1.0
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+ - Iban F1: 1.0
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+ - Ip F1: 0.7367
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+ - Ipv4 F1: 0.8360
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+ - Ipv6 F1: 0.9797
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+ - Jobarea F1: 0.9667
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+ - Jobtitle F1: 1.0
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+ - Jobtype F1: 1.0
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+ - Lastname F1: 1.0
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+ - Litecoinaddress F1: 0.9688
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  - Mac F1: 1.0
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+ - Maskednumber F1: 0.9887
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+ - Middlename F1: 0.9583
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  - Nearbygpscoordinate F1: 1.0
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+ - Ordinaldirection F1: 0.8571
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+ - Password F1: 0.9949
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  - Phoneimei F1: 0.9961
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+ - Phonenumber F1: 0.9838
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+ - Pin F1: 0.9963
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+ - Prefix F1: 0.9949
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+ - Secondaryaddress F1: 1.0
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+ - Sex F1: 1.0
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+ - Ssn F1: 0.9938
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+ - State F1: 1.0
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+ - Street F1: 0.9989
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+ - Time F1: 0.9958
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  - Url F1: 1.0
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+ - Useragent F1: 1.0
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  - Username F1: 1.0
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  - Vehiclevin F1: 1.0
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  - Vehiclevrm F1: 0.9929
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+ - Zipcode F1: 0.9966
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  ## Model description
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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: 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: cosine_with_restarts
 
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  | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Accountname F1 | Accountnumber F1 | Age F1 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Companyname F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Dob F1 | Email F1 | Ethereumaddress F1 | Eyecolor F1 | Firstname F1 | Gender F1 | Height F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Nearbygpscoordinate F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phonenumber F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Ssn F1 | State F1 | Street F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
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+ | 0.0484 | 1.0 | 535 | 0.1039 | 0.9213 | 0.9437 | 0.9324 | 0.9686 | 0.9973 | 1.0 | 0.9642 | 0.9918 | 0.9868 | 0.9543 | 0.9752 | 0.9978 | 0.9948 | 0.9955 | 0.9667 | 0.9964 | 0.9317 | 0.8788 | 0.9949 | 0.7526 | 0.9969 | 0.8814 | 0.6186 | 0.9987 | 0.9196 | 0.9804 | 0.9882 | 0.9988 | 1.0 | 0.9949 | 0.0922 | 0.8337 | 0.5216 | 0.9492 | 0.9983 | 0.98 | 0.9471 | 0.9351 | 0.5688 | 0.9115 | 0.1538 | 1.0 | 0.4 | 0.9732 | 0.9947 | 0.9967 | 0.9704 | 0.9806 | 0.9966 | 0.9783 | 0.9926 | 0.9715 | 0.9989 | 0.9890 | 0.9983 | 1.0 | 0.9966 | 0.9944 | 0.9976 | 0.9854 |
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+ | 0.0607 | 2.0 | 1070 | 0.0445 | 0.9510 | 0.9612 | 0.9560 | 0.9797 | 0.9938 | 0.9860 | 0.9723 | 0.9887 | 0.9733 | 0.9779 | 0.9813 | 0.9946 | 0.9906 | 0.9985 | 0.9474 | 0.9929 | 0.9331 | 0.8508 | 0.9898 | 0.7176 | 0.9969 | 0.9530 | 0.9028 | 0.9969 | 1.0 | 0.9804 | 0.9847 | 0.9918 | 0.9779 | 0.9758 | 0.2269 | 0.8362 | 0.7929 | 0.8667 | 0.9941 | 0.9245 | 0.9710 | 0.9491 | 0.9954 | 0.9351 | 0.2222 | 1.0 | 0.0 | 0.9919 | 0.9961 | 0.9892 | 0.9779 | 0.9669 | 0.9989 | 0.9670 | 0.9840 | 0.9923 | 0.9979 | 0.9834 | 0.9974 | 0.9975 | 0.9923 | 0.9808 | 0.9837 | 0.9776 |
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+ | 0.0585 | 3.0 | 1605 | 0.0391 | 0.9584 | 0.9652 | 0.9618 | 0.9834 | 1.0 | 0.9895 | 0.9706 | 0.9969 | 0.9868 | 0.9894 | 0.9788 | 0.9935 | 0.9990 | 0.9985 | 0.9825 | 0.9964 | 0.9639 | 0.8127 | 0.9897 | 0.7173 | 0.9953 | 0.9519 | 0.875 | 0.9981 | 1.0 | 1.0 | 0.9912 | 0.9988 | 0.9925 | 0.9923 | 0.3031 | 0.8371 | 0.8252 | 0.9836 | 0.9831 | 1.0 | 0.9581 | 0.9608 | 0.9954 | 0.9645 | 0.7805 | 1.0 | 0.8571 | 0.9850 | 0.9961 | 0.9967 | 0.9926 | 0.9790 | 0.9989 | 0.9890 | 0.9829 | 0.9904 | 0.9968 | 0.9903 | 1.0 | 1.0 | 0.9974 | 0.9833 | 0.9953 | 0.9818 |
113
+ | 0.0449 | 4.0 | 2140 | 0.0396 | 0.9668 | 0.9747 | 0.9707 | 0.9866 | 1.0 | 0.9956 | 0.9821 | 0.9928 | 0.9868 | 0.9936 | 0.9891 | 0.9989 | 0.9958 | 1.0 | 0.9655 | 0.9893 | 0.9721 | 0.9329 | 0.9949 | 0.8498 | 1.0 | 0.9763 | 0.9611 | 0.9839 | 1.0 | 0.9903 | 0.9965 | 0.9988 | 0.9925 | 0.9949 | 0.5304 | 0.8240 | 0.8382 | 0.9508 | 0.9949 | 1.0 | 0.9753 | 0.8916 | 0.9954 | 0.9666 | 0.8889 | 0.9984 | 0.75 | 1.0 | 0.9948 | 0.9967 | 0.9888 | 0.9840 | 0.9989 | 1.0 | 0.9914 | 0.9923 | 0.9989 | 0.9889 | 1.0 | 1.0 | 0.9983 | 1.0 | 0.9929 | 0.9910 |
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+ | 0.0405 | 5.0 | 2675 | 0.0204 | 0.9756 | 0.9807 | 0.9782 | 0.9912 | 1.0 | 1.0 | 0.9755 | 1.0 | 0.9934 | 0.9925 | 0.9969 | 0.9978 | 1.0 | 0.9985 | 0.9831 | 1.0 | 0.9839 | 0.9449 | 0.9897 | 0.8794 | 1.0 | 0.9884 | 0.9762 | 0.9863 | 1.0 | 1.0 | 0.9982 | 0.9976 | 0.9813 | 0.9949 | 0.5933 | 0.8519 | 0.8759 | 0.9667 | 0.9882 | 1.0 | 0.9867 | 0.9791 | 1.0 | 0.9822 | 0.8636 | 1.0 | 0.5714 | 1.0 | 0.9974 | 1.0 | 1.0 | 0.9949 | 1.0 | 1.0 | 0.9975 | 0.9981 | 0.9979 | 0.9930 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.9966 |
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+ | 0.026 | 6.0 | 3210 | 0.0116 | 0.9819 | 0.9863 | 0.9841 | 0.9960 | 1.0 | 1.0 | 0.9951 | 1.0 | 1.0 | 0.9883 | 1.0 | 1.0 | 1.0 | 0.9985 | 0.9831 | 1.0 | 0.9828 | 0.9663 | 0.9949 | 0.9225 | 0.9984 | 0.9872 | 0.9749 | 0.9800 | 1.0 | 1.0 | 1.0 | 0.9976 | 1.0 | 1.0 | 0.7247 | 0.8389 | 0.9779 | 0.9667 | 0.9958 | 1.0 | 0.9956 | 0.9688 | 1.0 | 0.9850 | 0.9583 | 1.0 | 0.8571 | 0.9949 | 0.9961 | 0.9967 | 0.9963 | 0.9940 | 1.0 | 1.0 | 0.9975 | 0.9981 | 0.9989 | 0.9958 | 1.0 | 1.0 | 1.0 | 1.0 | 0.9929 | 0.9977 |
116
+ | 0.0175 | 7.0 | 3745 | 0.0101 | 0.9818 | 0.9871 | 0.9844 | 0.9965 | 1.0 | 1.0 | 0.9951 | 1.0 | 1.0 | 0.9915 | 0.9969 | 1.0 | 1.0 | 0.9985 | 0.9831 | 0.9964 | 0.9889 | 0.9678 | 0.9949 | 0.9266 | 0.9984 | 0.9895 | 0.9774 | 0.9776 | 1.0 | 1.0 | 1.0 | 0.9976 | 1.0 | 1.0 | 0.7367 | 0.8360 | 0.9797 | 0.9667 | 1.0 | 1.0 | 1.0 | 0.9688 | 1.0 | 0.9887 | 0.9583 | 1.0 | 0.8571 | 0.9949 | 0.9961 | 0.9838 | 0.9963 | 0.9949 | 1.0 | 1.0 | 0.9938 | 1.0 | 0.9989 | 0.9958 | 1.0 | 1.0 | 1.0 | 1.0 | 0.9929 | 0.9966 |
117
 
118
 
119
  ### Framework versions
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