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distilbert-base-uncased-three_v2

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Safetensors
distilbert
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  1. README.md +66 -66
  2. all_results.json +67 -67
  3. eval_results.json +62 -62
  4. model.safetensors +1 -1
  5. train_results.json +5 -5
  6. trainer_state.json +546 -546
README.md CHANGED
@@ -15,67 +15,67 @@ should probably proofread and complete it, then remove this comment. -->
15
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1119
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- - Overall Precision: 0.6887
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- - Overall Recall: 0.7043
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- - Overall F1: 0.6964
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- - Overall Accuracy: 0.9661
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- - Accountname F1: 0.9754
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- - Accountnumber F1: 0.9909
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- - Age F1: 0.8968
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- - Amount F1: 0.9696
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- - Bic F1: 0.8958
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- - Bitcoinaddress F1: 0.9558
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- - Buildingnumber F1: 0.6231
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- - City F1: 0.4939
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- - Companyname F1: 0.7855
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- - County F1: 0.9636
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- - Creditcardcvv F1: 0.8203
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- - Creditcardissuer F1: 0.9870
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- - Creditcardnumber F1: 0.8612
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- - Currency F1: 0.7425
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- - Currencycode F1: 0.7627
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- - Currencyname F1: 0.0982
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- - Currencysymbol F1: 0.9107
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- - Date F1: 0.7740
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- - Dob F1: 0.5599
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- - Email F1: 0.6672
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  - Ethereumaddress F1: 1.0
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- - Eyecolor F1: 0.9311
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- - Firstname F1: 0.9272
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- - Gender F1: 0.9687
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- - Height F1: 0.9770
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- - Iban F1: 0.9728
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- - Ip F1: 0.3270
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- - Ipv4 F1: 0.8654
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- - Ipv6 F1: 0.7183
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- - Jobarea F1: 0.9173
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- - Jobtitle F1: 0.6473
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- - Jobtype F1: 0.9296
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- - Lastname F1: 0.4612
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- - Litecoinaddress F1: 0.8625
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- - Mac F1: 0.9881
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- - Maskednumber F1: 0.8622
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- - Middlename F1: 0.9260
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- - Nearbygpscoordinate F1: 0.6963
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- - Ordinaldirection F1: 0.9745
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- - Password F1: 0.4805
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- - Phoneimei F1: 0.9862
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- - Phonenumber F1: 0.6201
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- - Pin F1: 0.8720
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- - Prefix F1: 0.9302
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- - Secondaryaddress F1: 0.5961
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- - Sex F1: 0.6282
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- - Ssn F1: 0.5050
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- - State F1: 0.5606
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- - Street F1: 0.7082
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- - Time F1: 0.5796
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  - Url F1: 0.9878
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- - Useragent F1: 0.9852
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- - Username F1: 0.7521
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- - Vehiclevin F1: 0.9646
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- - Vehiclevrm F1: 0.9668
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- - Zipcode F1: 0.5227
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80
  ## Model description
81
 
@@ -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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- | 0.3276 | 1.0 | 1299 | 0.2229 | 0.5230 | 0.5278 | 0.5254 | 0.9424 | 0.8919 | 0.9149 | 0.7206 | 0.6079 | 0.2076 | 0.6905 | 0.3045 | 0.2728 | 0.6735 | 0.5815 | 0.2843 | 0.6916 | 0.5830 | 0.5045 | 0.0 | 0.0 | 0.5092 | 0.6867 | 0.3329 | 0.5175 | 0.9744 | 0.6538 | 0.8146 | 0.6366 | 0.75 | 0.7257 | 0.1116 | 0.7353 | 0.5603 | 0.5528 | 0.4372 | 0.7134 | 0.3042 | 0.0046 | 0.9167 | 0.0822 | 0.0840 | 0.5911 | 0.9193 | 0.3094 | 0.9275 | 0.4683 | 0.2838 | 0.8967 | 0.4395 | 0.4518 | 0.2766 | 0.2903 | 0.5173 | 0.3399 | 0.9528 | 0.9380 | 0.6582 | 0.2656 | 0.6773 | 0.2881 |
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- | 0.1401 | 2.0 | 2598 | 0.1397 | 0.6287 | 0.6284 | 0.6286 | 0.9576 | 0.9534 | 0.9882 | 0.8765 | 0.9421 | 0.8202 | 0.9559 | 0.4994 | 0.4134 | 0.7426 | 0.9261 | 0.7804 | 0.9789 | 0.8197 | 0.6180 | 0.5220 | 0.0226 | 0.8262 | 0.7257 | 0.4362 | 0.6022 | 0.9969 | 0.8986 | 0.8847 | 0.9243 | 0.9628 | 0.9030 | 0.1979 | 0.7328 | 0.7735 | 0.8205 | 0.5473 | 0.8987 | 0.3867 | 0.8544 | 0.9810 | 0.7560 | 0.6807 | 0.5924 | 0.9677 | 0.3921 | 0.9727 | 0.5302 | 0.7728 | 0.9201 | 0.5307 | 0.5501 | 0.3863 | 0.4817 | 0.6337 | 0.4443 | 0.9813 | 0.9783 | 0.7122 | 0.9508 | 0.9258 | 0.4593 |
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- | 0.1104 | 3.0 | 3897 | 0.1209 | 0.6666 | 0.6776 | 0.6720 | 0.9623 | 0.9774 | 0.9856 | 0.8887 | 0.9567 | 0.8848 | 0.9471 | 0.5858 | 0.4443 | 0.7776 | 0.9477 | 0.8110 | 0.9804 | 0.7916 | 0.6610 | 0.7299 | 0.0700 | 0.8701 | 0.7609 | 0.5071 | 0.6432 | 1.0 | 0.9197 | 0.9088 | 0.9648 | 0.9829 | 0.9534 | 0.2609 | 0.8441 | 0.7462 | 0.8918 | 0.6040 | 0.9262 | 0.4194 | 0.8408 | 0.9834 | 0.8206 | 0.8171 | 0.6754 | 0.9698 | 0.4345 | 0.9812 | 0.5896 | 0.8501 | 0.9236 | 0.5751 | 0.5900 | 0.4748 | 0.5231 | 0.6923 | 0.5301 | 0.9915 | 0.9796 | 0.7299 | 0.9891 | 0.9447 | 0.5085 |
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- | 0.0882 | 4.0 | 5196 | 0.1161 | 0.6722 | 0.6965 | 0.6841 | 0.9638 | 0.9718 | 0.9900 | 0.8882 | 0.9705 | 0.8853 | 0.9543 | 0.6118 | 0.4870 | 0.7765 | 0.9591 | 0.8066 | 0.9837 | 0.8624 | 0.6333 | 0.7563 | 0.2385 | 0.8982 | 0.7557 | 0.5353 | 0.6497 | 1.0 | 0.9205 | 0.9180 | 0.9651 | 0.9828 | 0.9488 | 0.2940 | 0.8703 | 0.7025 | 0.9113 | 0.6163 | 0.9163 | 0.4395 | 0.8634 | 0.9881 | 0.8473 | 0.9018 | 0.6874 | 0.9721 | 0.4599 | 0.9837 | 0.6139 | 0.8307 | 0.9193 | 0.5885 | 0.6180 | 0.5164 | 0.5544 | 0.7027 | 0.5589 | 0.9897 | 0.9841 | 0.7347 | 0.9863 | 0.9614 | 0.4974 |
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- | 0.0764 | 5.0 | 6495 | 0.1119 | 0.6887 | 0.7043 | 0.6964 | 0.9661 | 0.9754 | 0.9909 | 0.8968 | 0.9696 | 0.8958 | 0.9558 | 0.6231 | 0.4939 | 0.7855 | 0.9636 | 0.8203 | 0.9870 | 0.8612 | 0.7425 | 0.7627 | 0.0982 | 0.9107 | 0.7740 | 0.5599 | 0.6672 | 1.0 | 0.9311 | 0.9272 | 0.9687 | 0.9770 | 0.9728 | 0.3270 | 0.8654 | 0.7183 | 0.9173 | 0.6473 | 0.9296 | 0.4612 | 0.8625 | 0.9881 | 0.8622 | 0.9260 | 0.6963 | 0.9745 | 0.4805 | 0.9862 | 0.6201 | 0.8720 | 0.9302 | 0.5961 | 0.6282 | 0.5050 | 0.5606 | 0.7082 | 0.5796 | 0.9878 | 0.9852 | 0.7521 | 0.9646 | 0.9668 | 0.5227 |
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- | 0.0645 | 6.0 | 7794 | 0.1169 | 0.6930 | 0.7174 | 0.7050 | 0.9660 | 0.9820 | 0.9910 | 0.8980 | 0.9672 | 0.9057 | 0.9633 | 0.6393 | 0.5015 | 0.7901 | 0.9679 | 0.8131 | 0.9853 | 0.8545 | 0.7083 | 0.8079 | 0.2574 | 0.9170 | 0.7833 | 0.5912 | 0.6722 | 1.0 | 0.9451 | 0.9257 | 0.9727 | 0.9828 | 0.9575 | 0.3424 | 0.8225 | 0.6504 | 0.9186 | 0.6527 | 0.9293 | 0.4763 | 0.8833 | 0.9858 | 0.8462 | 0.9326 | 0.7296 | 0.9745 | 0.4830 | 0.9862 | 0.6415 | 0.8363 | 0.9286 | 0.5937 | 0.6443 | 0.5362 | 0.5685 | 0.7241 | 0.6023 | 0.9859 | 0.9807 | 0.7558 | 0.9753 | 0.9692 | 0.5277 |
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- | 0.0587 | 7.0 | 9093 | 0.1226 | 0.6923 | 0.7183 | 0.7051 | 0.9665 | 0.9820 | 0.9937 | 0.9013 | 0.9689 | 0.8966 | 0.9621 | 0.6535 | 0.5054 | 0.7921 | 0.9671 | 0.8220 | 0.9870 | 0.8582 | 0.7063 | 0.7943 | 0.2763 | 0.9171 | 0.7839 | 0.5918 | 0.6682 | 1.0 | 0.9304 | 0.9302 | 0.9716 | 0.9885 | 0.9495 | 0.3493 | 0.8137 | 0.6927 | 0.9216 | 0.6595 | 0.9336 | 0.4684 | 0.8825 | 0.9835 | 0.8349 | 0.9404 | 0.7217 | 0.9769 | 0.4853 | 0.9825 | 0.6447 | 0.8384 | 0.9286 | 0.6141 | 0.6360 | 0.5324 | 0.5770 | 0.7238 | 0.6028 | 0.9859 | 0.9818 | 0.7508 | 0.9728 | 0.9618 | 0.5324 |
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  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
17
  It achieves the following results on the evaluation set:
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+ - Loss: 0.0646
19
+ - Overall Precision: 0.8692
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+ - Overall Recall: 0.9049
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+ - Overall F1: 0.8867
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+ - Overall Accuracy: 0.9812
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+ - Accountname F1: 0.9773
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+ - Accountnumber F1: 0.9883
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+ - Age F1: 0.8924
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+ - Amount F1: 0.9622
27
+ - Bic F1: 0.8699
28
+ - Bitcoinaddress F1: 0.9496
29
+ - Buildingnumber F1: 0.9553
30
+ - City F1: 0.9484
31
+ - Companyname F1: 0.7802
32
+ - County F1: 0.9546
33
+ - Creditcardcvv F1: 0.8307
34
+ - Creditcardissuer F1: 0.9822
35
+ - Creditcardnumber F1: 0.8662
36
+ - Currency F1: 0.7573
37
+ - Currencycode F1: 0.7819
38
+ - Currencyname F1: 0.0943
39
+ - Currencysymbol F1: 0.8871
40
+ - Date F1: 0.8276
41
+ - Dob F1: 0.8951
42
+ - Email F1: 0.9543
43
  - Ethereumaddress F1: 1.0
44
+ - Eyecolor F1: 0.9344
45
+ - Firstname F1: 0.8670
46
+ - Gender F1: 0.9632
47
+ - Height F1: 0.9716
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+ - Iban F1: 0.9468
49
+ - Ip F1: 0.8493
50
+ - Ipv4 F1: 0.8556
51
+ - Ipv6 F1: 0.6738
52
+ - Jobarea F1: 0.8987
53
+ - Jobtitle F1: 0.9577
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+ - Jobtype F1: 0.9303
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+ - Lastname F1: 0.8520
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+ - Litecoinaddress F1: 0.8554
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+ - Mac F1: 0.9928
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+ - Maskednumber F1: 0.8369
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+ - Middlename F1: 0.7513
60
+ - Nearbygpscoordinate F1: 0.9269
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+ - Ordinaldirection F1: 0.9817
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+ - Password F1: 0.8792
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+ - Phoneimei F1: 0.9887
64
+ - Phonenumber F1: 0.9230
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+ - Pin F1: 0.8550
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+ - Prefix F1: 0.9199
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+ - Secondaryaddress F1: 0.9740
68
+ - Sex F1: 0.9667
69
+ - Ssn F1: 0.9150
70
+ - State F1: 0.9738
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+ - Street F1: 0.8667
72
+ - Time F1: 0.9069
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  - Url F1: 0.9878
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+ - Useragent F1: 0.9943
75
+ - Username F1: 0.8805
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+ - Vehiclevin F1: 0.9620
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+ - Vehiclevrm F1: 0.9821
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+ - Zipcode F1: 0.9423
79
 
80
  ## Model description
81
 
 
107
 
108
  | 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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+ | 0.2314 | 1.0 | 1299 | 0.1322 | 0.7381 | 0.8044 | 0.7698 | 0.9699 | 0.8367 | 0.8496 | 0.6806 | 0.5746 | 0.3430 | 0.8041 | 0.8363 | 0.8420 | 0.6640 | 0.3719 | 0.0357 | 0.4493 | 0.4554 | 0.5 | 0.0 | 0.0 | 0.4768 | 0.7367 | 0.8515 | 0.9459 | 0.9908 | 0.1847 | 0.75 | 0.6004 | 0.6974 | 0.7952 | 0.8253 | 0.8246 | 0.7153 | 0.1512 | 0.7939 | 0.4468 | 0.7328 | 0.0 | 0.9026 | 0.4479 | 0.1935 | 0.8676 | 0.4604 | 0.7485 | 0.9364 | 0.8741 | 0.0060 | 0.8869 | 0.8963 | 0.8999 | 0.8115 | 0.8037 | 0.7648 | 0.8413 | 0.9516 | 0.9388 | 0.8054 | 0.3968 | 0.4866 | 0.8015 |
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+ | 0.0799 | 2.0 | 2598 | 0.0761 | 0.8402 | 0.8811 | 0.8602 | 0.9782 | 0.9717 | 0.9659 | 0.8657 | 0.9269 | 0.8091 | 0.9468 | 0.9322 | 0.9342 | 0.7616 | 0.9097 | 0.7692 | 0.9821 | 0.7663 | 0.7208 | 0.5127 | 0.0248 | 0.8171 | 0.7995 | 0.8872 | 0.9503 | 0.9985 | 0.8933 | 0.8138 | 0.9242 | 0.9632 | 0.9326 | 0.8285 | 0.8610 | 0.5590 | 0.8205 | 0.9382 | 0.9207 | 0.8141 | 0.8254 | 0.9928 | 0.7820 | 0.5016 | 0.8957 | 0.9611 | 0.8398 | 0.9838 | 0.9222 | 0.7815 | 0.9156 | 0.9650 | 0.9534 | 0.9125 | 0.9593 | 0.8373 | 0.8884 | 0.9804 | 0.9806 | 0.8505 | 0.9056 | 0.9592 | 0.9209 |
112
+ | 0.0604 | 3.0 | 3897 | 0.0681 | 0.8591 | 0.8945 | 0.8765 | 0.9799 | 0.9829 | 0.9882 | 0.8940 | 0.9528 | 0.8575 | 0.9588 | 0.9468 | 0.9462 | 0.7795 | 0.9411 | 0.8156 | 0.9821 | 0.8064 | 0.7556 | 0.7036 | 0.0317 | 0.8614 | 0.8159 | 0.8861 | 0.9547 | 0.9969 | 0.9311 | 0.8487 | 0.9505 | 0.9718 | 0.9388 | 0.8284 | 0.7476 | 0.7306 | 0.8966 | 0.9562 | 0.9323 | 0.8372 | 0.8718 | 0.9928 | 0.8047 | 0.6657 | 0.9103 | 0.9769 | 0.8639 | 0.9937 | 0.9262 | 0.8207 | 0.9170 | 0.9737 | 0.9663 | 0.9201 | 0.9705 | 0.8333 | 0.9061 | 0.9915 | 0.9909 | 0.8685 | 0.9808 | 0.9671 | 0.9289 |
113
+ | 0.0469 | 4.0 | 5196 | 0.0646 | 0.8692 | 0.9049 | 0.8867 | 0.9812 | 0.9773 | 0.9883 | 0.8924 | 0.9622 | 0.8699 | 0.9496 | 0.9553 | 0.9484 | 0.7802 | 0.9546 | 0.8307 | 0.9822 | 0.8662 | 0.7573 | 0.7819 | 0.0943 | 0.8871 | 0.8276 | 0.8951 | 0.9543 | 1.0 | 0.9344 | 0.8670 | 0.9632 | 0.9716 | 0.9468 | 0.8493 | 0.8556 | 0.6738 | 0.8987 | 0.9577 | 0.9303 | 0.8520 | 0.8554 | 0.9928 | 0.8369 | 0.7513 | 0.9269 | 0.9817 | 0.8792 | 0.9887 | 0.9230 | 0.8550 | 0.9199 | 0.9740 | 0.9667 | 0.9150 | 0.9738 | 0.8667 | 0.9069 | 0.9878 | 0.9943 | 0.8805 | 0.9620 | 0.9821 | 0.9423 |
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+ | 0.0365 | 5.0 | 6495 | 0.0688 | 0.8757 | 0.9066 | 0.8909 | 0.9815 | 0.9877 | 0.9891 | 0.8980 | 0.9720 | 0.8845 | 0.9588 | 0.9591 | 0.9511 | 0.8042 | 0.9555 | 0.8268 | 0.9870 | 0.8498 | 0.7164 | 0.7954 | 0.2376 | 0.9093 | 0.8287 | 0.8881 | 0.9543 | 1.0 | 0.9392 | 0.8648 | 0.9776 | 0.9771 | 0.9657 | 0.8602 | 0.8201 | 0.7170 | 0.9104 | 0.9594 | 0.9336 | 0.8596 | 0.8698 | 0.9928 | 0.8396 | 0.7732 | 0.9266 | 0.9837 | 0.8613 | 0.9799 | 0.9370 | 0.8524 | 0.9232 | 0.9724 | 0.9713 | 0.9317 | 0.9748 | 0.8684 | 0.9145 | 0.9897 | 0.9909 | 0.8822 | 0.9620 | 0.9594 | 0.9490 |
115
+ | 0.0277 | 6.0 | 7794 | 0.0766 | 0.8745 | 0.9120 | 0.8929 | 0.9813 | 0.9877 | 0.9900 | 0.8945 | 0.9746 | 0.8930 | 0.9434 | 0.9551 | 0.9471 | 0.7986 | 0.96 | 0.8303 | 0.9853 | 0.8607 | 0.7025 | 0.8011 | 0.2532 | 0.9124 | 0.8337 | 0.8961 | 0.9518 | 0.9985 | 0.9396 | 0.8713 | 0.9748 | 0.9801 | 0.9543 | 0.8564 | 0.8474 | 0.7036 | 0.9193 | 0.9567 | 0.9320 | 0.8612 | 0.8450 | 0.9952 | 0.8282 | 0.7761 | 0.9323 | 0.9839 | 0.8869 | 0.9925 | 0.9387 | 0.8360 | 0.9268 | 0.9723 | 0.9702 | 0.9372 | 0.9712 | 0.8759 | 0.9190 | 0.9859 | 0.9909 | 0.8835 | 0.9511 | 0.9697 | 0.9430 |
116
+ | 0.0225 | 7.0 | 9093 | 0.0850 | 0.8795 | 0.9113 | 0.8951 | 0.9819 | 0.9896 | 0.9936 | 0.8952 | 0.9746 | 0.8916 | 0.9545 | 0.9595 | 0.9505 | 0.8040 | 0.9581 | 0.8362 | 0.9919 | 0.8677 | 0.7402 | 0.7932 | 0.2246 | 0.9097 | 0.8339 | 0.8964 | 0.9503 | 1.0 | 0.9396 | 0.8748 | 0.9796 | 0.9829 | 0.9604 | 0.8682 | 0.8297 | 0.7449 | 0.9147 | 0.9594 | 0.9281 | 0.8581 | 0.8466 | 0.9952 | 0.8331 | 0.7916 | 0.9373 | 0.9861 | 0.8877 | 0.9925 | 0.9406 | 0.8546 | 0.9289 | 0.9733 | 0.9718 | 0.9330 | 0.9756 | 0.8799 | 0.9217 | 0.9868 | 0.9932 | 0.8802 | 0.9593 | 0.9622 | 0.9459 |
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  ### Framework versions
all_results.json CHANGED
@@ -1,74 +1,74 @@
1
  {
2
  "epoch": 7.0,
3
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