--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer model-index: - name: distilbert-base-uncased-three_v2 results: [] --- # distilbert-base-uncased-three_v2 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1119 - Overall Precision: 0.6887 - Overall Recall: 0.7043 - Overall F1: 0.6964 - Overall Accuracy: 0.9661 - Accountname F1: 0.9754 - Accountnumber F1: 0.9909 - Age F1: 0.8968 - Amount F1: 0.9696 - Bic F1: 0.8958 - Bitcoinaddress F1: 0.9558 - Buildingnumber F1: 0.6231 - City F1: 0.4939 - Companyname F1: 0.7855 - County F1: 0.9636 - Creditcardcvv F1: 0.8203 - Creditcardissuer F1: 0.9870 - Creditcardnumber F1: 0.8612 - Currency F1: 0.7425 - Currencycode F1: 0.7627 - Currencyname F1: 0.0982 - Currencysymbol F1: 0.9107 - Date F1: 0.7740 - Dob F1: 0.5599 - Email F1: 0.6672 - Ethereumaddress F1: 1.0 - Eyecolor F1: 0.9311 - Firstname F1: 0.9272 - Gender F1: 0.9687 - Height F1: 0.9770 - Iban F1: 0.9728 - Ip F1: 0.3270 - Ipv4 F1: 0.8654 - Ipv6 F1: 0.7183 - Jobarea F1: 0.9173 - Jobtitle F1: 0.6473 - Jobtype F1: 0.9296 - Lastname F1: 0.4612 - Litecoinaddress F1: 0.8625 - Mac F1: 0.9881 - Maskednumber F1: 0.8622 - Middlename F1: 0.9260 - Nearbygpscoordinate F1: 0.6963 - Ordinaldirection F1: 0.9745 - Password F1: 0.4805 - Phoneimei F1: 0.9862 - Phonenumber F1: 0.6201 - Pin F1: 0.8720 - Prefix F1: 0.9302 - Secondaryaddress F1: 0.5961 - Sex F1: 0.6282 - Ssn F1: 0.5050 - State F1: 0.5606 - Street F1: 0.7082 - Time F1: 0.5796 - Url F1: 0.9878 - Useragent F1: 0.9852 - Username F1: 0.7521 - Vehiclevin F1: 0.9646 - Vehiclevrm F1: 0.9668 - Zipcode F1: 0.5227 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.2 - num_epochs: 7 ### Training results | 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 | |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:| | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | | 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 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.2+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1