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xXiaobuding
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xlm-roberta-base_ai4privacy_en

Token Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: xlm-roberta-base_ai4privacy_en
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # xlm-roberta-base_ai4privacy_en
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1063
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+ - Overall Precision: 0.9013
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+ - Overall Recall: 0.9238
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+ - Overall F1: 0.9124
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+ - Overall Accuracy: 0.9651
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+ - Accountname F1: 0.9932
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+ - Accountnumber F1: 0.9939
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+ - Age F1: 0.9002
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+ - Amount F1: 0.8985
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+ - Bic F1: 0.8820
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+ - Bitcoinaddress F1: 0.9592
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+ - Buildingnumber F1: 0.8566
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+ - City F1: 0.8694
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+ - Companyname F1: 0.9675
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+ - County F1: 0.9727
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+ - Creditcardcvv F1: 0.9067
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+ - Creditcardissuer F1: 0.9775
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+ - Creditcardnumber F1: 0.8987
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+ - Currency F1: 0.7436
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+ - Currencycode F1: 0.7229
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+ - Currencyname F1: 0.2329
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+ - Currencysymbol F1: 0.9477
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+ - Date F1: 0.8368
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+ - Dob F1: 0.6093
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+ - Email F1: 0.992
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+ - Ethereumaddress F1: 0.9931
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+ - Eyecolor F1: 0.9465
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+ - Firstname F1: 0.9244
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+ - Gender F1: 0.9758
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+ - Height F1: 0.9781
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+ - Iban F1: 0.9862
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+ - Ip F1: 0.0575
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+ - Ipv4 F1: 0.8350
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+ - Ipv6 F1: 0.8063
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+ - Jobarea F1: 0.8548
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+ - Jobtitle F1: 0.9789
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+ - Jobtype F1: 0.9298
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+ - Lastname F1: 0.9075
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+ - Litecoinaddress F1: 0.8739
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+ - Mac F1: 0.9849
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+ - Maskednumber F1: 0.8504
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+ - Middlename F1: 0.9595
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+ - Nearbygpscoordinate F1: 0.9955
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+ - Ordinaldirection F1: 0.9723
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+ - Password F1: 0.9469
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+ - Phoneimei F1: 0.9944
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+ - Phonenumber F1: 0.9828
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+ - Pin F1: 0.8348
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+ - Prefix F1: 0.9362
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+ - Secondaryaddress F1: 0.9902
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+ - Sex F1: 0.9722
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+ - Ssn F1: 0.9772
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+ - State F1: 0.9462
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+ - Street F1: 0.8983
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+ - Time F1: 0.9665
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+ - Url F1: 0.9944
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+ - Useragent F1: 0.9859
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+ - Username F1: 0.9385
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+ - Vehiclevin F1: 0.9766
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+ - Vehiclevrm F1: 0.9199
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+ - Zipcode F1: 0.8565
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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+ - eval_batch_size: 2
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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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+ - lr_scheduler_warmup_ratio: 0.2
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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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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+ | 0.2518 | 1.0 | 17398 | 0.2143 | 0.6947 | 0.7367 | 0.7151 | 0.9323 | 0.9707 | 0.9222 | 0.7076 | 0.5415 | 0.6505 | 0.7706 | 0.6596 | 0.2664 | 0.7131 | 0.6703 | 0.6667 | 0.8615 | 0.5074 | 0.4166 | 0.2531 | 0.0170 | 0.7633 | 0.7359 | 0.2656 | 0.9324 | 0.9146 | 0.825 | 0.6515 | 0.8004 | 0.8310 | 0.7544 | 0.0 | 0.7822 | 0.7785 | 0.6935 | 0.9019 | 0.8237 | 0.4787 | 0.5847 | 0.9429 | 0.5205 | 0.1667 | 0.9970 | 0.9538 | 0.8033 | 0.9576 | 0.8437 | 0.5534 | 0.9126 | 0.9428 | 0.96 | 0.8784 | 0.3854 | 0.5525 | 0.8787 | 0.9621 | 0.9099 | 0.7158 | 0.7584 | 0.7146 | 0.6748 |
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+ | 0.1671 | 2.0 | 34796 | 0.1478 | 0.8137 | 0.8681 | 0.8400 | 0.9533 | 0.9832 | 0.9659 | 0.8195 | 0.7536 | 0.7788 | 0.9311 | 0.7936 | 0.6928 | 0.8637 | 0.9132 | 0.7308 | 0.9630 | 0.7972 | 0.4755 | 0.4894 | 0.2028 | 0.8631 | 0.8271 | 0.5392 | 0.9674 | 0.9876 | 0.7395 | 0.8259 | 0.9225 | 0.9235 | 0.9202 | 0.0 | 0.8132 | 0.8014 | 0.7758 | 0.9466 | 0.8900 | 0.7645 | 0.7861 | 0.9744 | 0.7449 | 0.9263 | 0.9955 | 0.9682 | 0.9079 | 0.9793 | 0.9239 | 0.7352 | 0.8539 | 0.9762 | 0.9690 | 0.9488 | 0.6922 | 0.6695 | 0.9484 | 0.9833 | 0.9496 | 0.8646 | 0.9337 | 0.9129 | 0.7705 |
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+ | 0.1137 | 3.0 | 52194 | 0.1194 | 0.8691 | 0.9014 | 0.8849 | 0.9592 | 0.9924 | 0.9836 | 0.8851 | 0.8444 | 0.8802 | 0.7832 | 0.8296 | 0.8442 | 0.9428 | 0.9556 | 0.9079 | 0.9719 | 0.8341 | 0.5643 | 0.6472 | 0.4229 | 0.9137 | 0.8459 | 0.5960 | 0.9799 | 0.9834 | 0.8969 | 0.8974 | 0.9660 | 0.9592 | 0.96 | 0.0046 | 0.8214 | 0.7859 | 0.8490 | 0.9738 | 0.9132 | 0.8641 | 0.6235 | 0.9507 | 0.7521 | 0.9442 | 0.9970 | 0.9806 | 0.9346 | 0.9944 | 0.9670 | 0.8369 | 0.9318 | 0.9913 | 0.9690 | 0.9787 | 0.9154 | 0.8266 | 0.9460 | 0.9889 | 0.9812 | 0.9120 | 0.9570 | 0.9387 | 0.8042 |
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+ | 0.079 | 4.0 | 69592 | 0.1063 | 0.9013 | 0.9238 | 0.9124 | 0.9651 | 0.9932 | 0.9939 | 0.9002 | 0.8985 | 0.8820 | 0.9592 | 0.8566 | 0.8694 | 0.9675 | 0.9727 | 0.9067 | 0.9775 | 0.8987 | 0.7436 | 0.7229 | 0.2329 | 0.9477 | 0.8368 | 0.6093 | 0.992 | 0.9931 | 0.9465 | 0.9244 | 0.9758 | 0.9781 | 0.9862 | 0.0575 | 0.8350 | 0.8063 | 0.8548 | 0.9789 | 0.9298 | 0.9075 | 0.8739 | 0.9849 | 0.8504 | 0.9595 | 0.9955 | 0.9723 | 0.9469 | 0.9944 | 0.9828 | 0.8348 | 0.9362 | 0.9902 | 0.9722 | 0.9772 | 0.9462 | 0.8983 | 0.9665 | 0.9944 | 0.9859 | 0.9385 | 0.9766 | 0.9199 | 0.8565 |
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+ | 0.0762 | 5.0 | 86990 | 0.1087 | 0.9009 | 0.9260 | 0.9133 | 0.9657 | 0.9932 | 0.9914 | 0.9061 | 0.9137 | 0.9049 | 0.9553 | 0.8787 | 0.8822 | 0.9716 | 0.9699 | 0.9267 | 0.9812 | 0.8821 | 0.7145 | 0.7319 | 0.2778 | 0.9553 | 0.8484 | 0.6517 | 0.9908 | 0.9903 | 0.9524 | 0.9288 | 0.9748 | 0.9718 | 0.9925 | 0.13 | 0.8044 | 0.7502 | 0.8678 | 0.9859 | 0.9428 | 0.9176 | 0.8837 | 0.9602 | 0.8415 | 0.9595 | 0.9970 | 0.9806 | 0.9624 | 0.9903 | 0.9775 | 0.8788 | 0.9344 | 0.9913 | 0.9721 | 0.9898 | 0.9441 | 0.8973 | 0.9698 | 0.9937 | 0.9988 | 0.9371 | 0.9825 | 0.9604 | 0.8811 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 2.0.0.post101
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.3