Model save

README.md

@@ -0,0 +1,128 @@
+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: distilbert_finetuned_ai4privacy
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distilbert_finetuned_ai4privacy
+
+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: 0.0108
+- Overall Precision: 0.9724
+- Overall Recall: 0.9774
+- Overall F1: 0.9749
+- Overall Accuracy: 0.9977
+- Accountname F1: 1.0
+- Accountnumber F1: 1.0
+- Amount F1: 0.9375
+- Bic F1: 1.0
+- Bitcoinaddress F1: 0.9880
+- Buildingnumber F1: 0.95
+- City F1: 0.9987
+- Company Name F1: 0.9954
+- County F1: 1.0
+- Creditcardcvv F1: 0.9821
+- Creditcardissuer F1: 0.9809
+- Creditcardnumber F1: 0.9924
+- Currency F1: 0.8018
+- Currencycode F1: 0.8229
+- Currencyname F1: 0.5534
+- Currencysymbol F1: 0.3548
+- Date F1: 0.9975
+- Displayname F1: 0.5862
+- Email F1: 1.0
+- Ethereumaddress F1: 1.0
+- Firstname F1: 0.9465
+- Fullname F1: 0.9974
+- Gender F1: 0.9574
+- Iban F1: 1.0
+- Ip F1: 0.5957
+- Ipv4 F1: 0.8660
+- Ipv6 F1: 0.9524
+- Jobarea F1: 0.9789
+- Jobdescriptor F1: 0.6842
+- Jobtitle F1: 0.9554
+- Jobtype F1: 0.8872
+- Lastname F1: 0.9091
+- Litecoinaddress F1: 0.9934
+- Mac F1: 1.0
+- Maskednumber F1: 0.9816
+- Middlename F1: 0.7065
+- Name F1: 0.9998
+- Nearbygpscoordinate F1: 0.0
+- Number F1: 1.0
+- Ordinaldirection F1: 0.0
+- Password F1: 1.0
+- Phoneimei F1: 1.0
+- Phone Number F1: 0.9811
+- Pin F1: 0.9600
+- Prefix F1: 0.9593
+- Secondaryaddress F1: 0.9940
+- Sex F1: 0.9557
+- Sextype F1: 0.0
+- Ssn F1: 0.9928
+- State F1: 0.9991
+- Street F1: 0.9701
+- Streetaddress F1: 0.9813
+- Suffix F1: 0.8690
+- Time F1: 0.9963
+- Url F1: 1.0
+- Useragent F1: 1.0
+- Username F1: 0.9743
+- Vehiclevin F1: 1.0
+- Vehiclevrm F1: 1.0
+- Zipcode F1: 0.9922
+
+## 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: 32
+- eval_batch_size: 32
+- 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 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Company Name F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Displayname F1 | Email F1 | Ethereumaddress F1 | Firstname F1 | Fullname F1 | Gender F1 | Iban F1 | Ip F1  | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobdescriptor F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Name F1 | Nearbygpscoordinate F1 | Number F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phone Number F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Sextype F1 | Ssn F1 | State F1 | Street F1 | Streetaddress F1 | Suffix F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:---------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:--------------:|:--------:|:------------------:|:------------:|:-----------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:----------------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:-------:|:----------------------:|:---------:|:-------------------:|:-----------:|:------------:|:---------------:|:------:|:---------:|:-------------------:|:------:|:----------:|:------:|:--------:|:---------:|:----------------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
+| No log        | 1.0   | 335  | 0.3443          | 0.6624            | 0.6759         | 0.6690     | 0.9184           | 0.0            | 0.6485           | 0.2638    | 0.0    | 0.2738            | 0.0               | 0.7150  | 0.0             | 0.0       | 0.0              | 0.0                 | 0.5613              | 0.1414      | 0.0             | 0.0             | 0.0               | 0.6308  | 0.0            | 0.9532   | 0.6853             | 0.0117       | 0.9139      | 0.0       | 0.3417  | 0.0    | 0.7449  | 0.6448  | 0.4051     | 0.0              | 0.0310      | 0.0        | 0.1213      | 0.0                | 0.7902 | 0.0             | 0.0           | 0.8767  | 0.0                    | 0.3274    | 0.0                 | 0.5161      | 0.6280       | 0.0             | 0.0    | 0.0       | 0.0                 | 0.0    | 0.0        | 0.0190 | 0.4854   | 0.0       | 0.6674           | 0.0       | 0.0     | 0.9036 | 0.7860       | 0.2556      | 0.4880        | 0.0           | 0.3714     |
+| 1.2173        | 2.0   | 670  | 0.1653          | 0.7670            | 0.8297         | 0.7971     | 0.9390           | 0.7480         | 0.8087           | 0.5992    | 0.5043 | 0.3596            | 0.3211            | 0.9374  | 0.1393          | 0.5392    | 0.0              | 0.0                 | 0.6133              | 0.2427      | 0.0             | 0.1531          | 0.0               | 0.9701  | 0.0            | 0.9986   | 0.7518             | 0.7461       | 0.9780      | 0.0563    | 0.5263  | 0.2877 | 0.8325  | 0.0     | 0.7690     | 0.0              | 0.7387      | 0.0        | 0.4478      | 0.0152             | 0.9854 | 0.0             | 0.0           | 0.9681  | 0.0                    | 0.4675    | 0.0                 | 0.5889      | 0.9691       | 0.0             | 0.0    | 0.7262    | 0.0982              | 0.0600 | 0.0        | 0.0630 | 0.6859   | 0.2877    | 0.8083           | 0.0       | 0.9167  | 0.9909 | 0.9406       | 0.8548      | 0.6415        | 0.6057        | 0.7128     |
+| 0.1551        | 3.0   | 1005 | 0.0729          | 0.8510            | 0.8956         | 0.8727     | 0.9740           | 0.9416         | 0.8710           | 0.8631    | 0.9550 | 0.8028            | 0.5606            | 0.9934  | 0.8534          | 0.9547    | 0.3333           | 0.6438              | 0.0                 | 0.3124      | 0.2951          | 0.1404          | 0.0               | 0.9825  | 0.0            | 0.9997   | 0.9858             | 0.8164       | 0.9880      | 0.5979    | 1.0     | 0.0    | 0.8718  | 0.4470  | 0.9217     | 0.0              | 0.8533      | 0.4524     | 0.5618      | 0.4000             | 1.0    | 0.0201          | 0.1304        | 0.9923  | 0.0                    | 0.3713    | 0.0                 | 0.9249      | 0.9792       | 0.6865          | 0.1538 | 0.7942    | 0.8571              | 0.8641 | 0.0        | 0.5938 | 0.9879   | 0.6811    | 0.8807           | 0.0435    | 0.9783  | 0.9939 | 0.9862       | 0.9040      | 0.9867        | 0.9323        | 0.8300     |
+| 0.1551        | 4.0   | 1340 | 0.0424          | 0.9312            | 0.9436         | 0.9374     | 0.9843           | 0.9921         | 0.9928           | 0.8899    | 0.9107 | 0.8121            | 0.7573            | 0.9953  | 0.9450          | 0.9966    | 0.9138           | 0.8718              | 0.8514              | 0.6389      | 0.5921          | 0.0182          | 0.0               | 0.9874  | 0.0            | 0.9989   | 0.9581             | 0.8856       | 0.9903      | 0.6739    | 0.9778  | 0.0163 | 0.8696  | 0.7732  | 0.9492     | 0.2037           | 0.9128      | 0.7073     | 0.7077      | 0.6705             | 0.9901 | 0.6875          | 0.5193        | 0.9972  | 0.0                    | 0.9749    | 0.0                 | 0.9595      | 0.9895       | 0.9132          | 0.6575 | 0.8811    | 0.9822              | 0.8920 | 0.0        | 1.0    | 0.9956   | 0.8383    | 0.9181           | 0.5694    | 0.9963  | 1.0    | 1.0          | 0.9481      | 0.9396        | 0.9921        | 0.9846     |
+| 0.065         | 5.0   | 1675 | 0.0341          | 0.9446            | 0.9582         | 0.9514     | 0.9894           | 0.992          | 0.9976           | 0.9165    | 1.0    | 0.9421            | 0.8397            | 0.9987  | 0.9815          | 1.0       | 0.9244           | 0.9419              | 0.9438              | 0.6724      | 0.7447          | 0.3274          | 0.1481            | 0.9874  | 0.0727         | 1.0      | 1.0                | 0.9071       | 0.9915      | 0.9032    | 1.0     | 0.0979 | 0.8645  | 0.7668  | 0.9753     | 0.5180           | 0.9170      | 0.7790     | 0.7843      | 0.8917             | 1.0    | 0.8765          | 0.5761        | 0.9992  | 0.0                    | 0.9898    | 0.0                 | 0.9842      | 1.0          | 0.9630          | 0.7632 | 0.9101    | 0.9822              | 0.9372 | 0.0        | 1.0    | 0.9983   | 0.8399    | 0.9347           | 0.6581    | 0.9963  | 1.0    | 0.9630       | 0.9447      | 0.9933        | 1.0           | 0.9948     |
+| 0.0346        | 6.0   | 2010 | 0.0136          | 0.9671            | 0.9736         | 0.9703     | 0.9968           | 0.9921         | 1.0              | 0.9327    | 1.0    | 0.9880            | 0.9182            | 0.9984  | 0.9907          | 1.0       | 0.9649           | 0.9809              | 0.9403              | 0.7669      | 0.8046          | 0.4433          | 0.3051            | 0.9899  | 0.4483         | 0.9997   | 1.0                | 0.9379       | 0.9973      | 0.9474    | 1.0     | 0.6272 | 0.8673  | 0.9639  | 0.9789     | 0.6928           | 0.9453      | 0.8617     | 0.8995      | 0.9934             | 1.0    | 0.9186          | 0.6632        | 0.9996  | 0.0                    | 0.9898    | 0.0                 | 0.9937      | 0.9947       | 0.9765          | 0.9067 | 0.9507    | 0.9881              | 0.9505 | 0.0        | 1.0    | 0.9983   | 0.9222    | 0.9633           | 0.8571    | 0.9963  | 1.0    | 1.0          | 0.9689      | 1.0           | 1.0           | 0.9896     |
+| 0.0346        | 7.0   | 2345 | 0.0108          | 0.9724            | 0.9774         | 0.9749     | 0.9977           | 1.0            | 1.0              | 0.9375    | 1.0    | 0.9880            | 0.95              | 0.9987  | 0.9954          | 1.0       | 0.9821           | 0.9809              | 0.9924              | 0.8018      | 0.8229          | 0.5534          | 0.3548            | 0.9975  | 0.5862         | 1.0      | 1.0                | 0.9465       | 0.9974      | 0.9574    | 1.0     | 0.5957 | 0.8660  | 0.9524  | 0.9789     | 0.6842           | 0.9554      | 0.8872     | 0.9091      | 0.9934             | 1.0    | 0.9816          | 0.7065        | 0.9998  | 0.0                    | 1.0       | 0.0                 | 1.0         | 1.0          | 0.9811          | 0.9600 | 0.9593    | 0.9940              | 0.9557 | 0.0        | 0.9928 | 0.9991   | 0.9701    | 0.9813           | 0.8690    | 0.9963  | 1.0    | 1.0          | 0.9743      | 1.0           | 1.0           | 0.9922     |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 1.13.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.13.3

all_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 7.0,
+    "total_flos": 2624828110088400.0,
+    "train_loss": 0.3166055935532299,
+    "train_runtime": 27922.8087,
+    "train_samples": 42768,
+    "train_samples_per_second": 2.681,
+    "train_steps_per_second": 0.084
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 7.0,
+    "total_flos": 2624828110088400.0,
+    "train_loss": 0.3166055935532299,
+    "train_runtime": 27922.8087,
+    "train_samples": 42768,
+    "train_samples_per_second": 2.681,
+    "train_steps_per_second": 0.084
+}

trainer_state.json

@@ -0,0 +1,628 @@
+{
+  "best_metric": 0.010772046633064747,
+  "best_model_checkpoint": "distilbert_finetuned_ai4privacy/checkpoint-2345",
+  "epoch": 7.0,
+  "eval_steps": 500,
+  "global_step": 2345,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
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+      "eval_ACCOUNTNUMBER_f1": 0.6485436893203884,
+      "eval_AMOUNT_f1": 0.2637795275590551,
+      "eval_BIC_f1": 0.0,
+      "eval_BITCOINADDRESS_f1": 0.2738301559792028,
+      "eval_BUILDINGNUMBER_f1": 0.0,
+      "eval_CITY_f1": 0.7149532710280374,
+      "eval_COMPANY_NAME_f1": 0.0,
+      "eval_COUNTY_f1": 0.0,
+      "eval_CREDITCARDCVV_f1": 0.0,
+      "eval_CREDITCARDISSUER_f1": 0.0,
+      "eval_CREDITCARDNUMBER_f1": 0.5613207547169812,
+      "eval_CURRENCYCODE_f1": 0.0,
+      "eval_CURRENCYNAME_f1": 0.0,
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+      "eval_CURRENCY_f1": 0.1414141414141414,
+      "eval_DATE_f1": 0.6307692307692306,
+      "eval_DISPLAYNAME_f1": 0.0,
+      "eval_EMAIL_f1": 0.9532453245324533,
+      "eval_ETHEREUMADDRESS_f1": 0.6853146853146852,
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+      "eval_FULLNAME_f1": 0.9138788426763111,
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+      "eval_IPV4_f1": 0.7449209932279909,
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+      "eval_JOBDESCRIPTOR_f1": 0.0,
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+      "eval_SECONDARYADDRESS_f1": 0.09815950920245399,
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+      "eval_SEX_f1": 0.06000000000000001,
+      "eval_SSN_f1": 0.06299212598425197,
+      "eval_STATE_f1": 0.685887708649469,
+      "eval_STREETADDRESS_f1": 0.8083441981747066,
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+      "eval_SUFFIX_f1": 0.0,
+      "eval_TIME_f1": 0.9166666666666666,
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+      "eval_USERNAME_f1": 0.8547854785478548,
+      "eval_VEHICLEVIN_f1": 0.6415094339622641,
+      "eval_VEHICLEVRM_f1": 0.6057142857142858,
+      "eval_ZIPCODE_f1": 0.7127882599580712,
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+      "eval_overall_recall": 0.8297433671531659,
+      "eval_runtime": 954.314,
+      "eval_samples_per_second": 11.205,
+      "eval_steps_per_second": 0.351,
+      "step": 670
+    },
+    {
+      "epoch": 2.99,
+      "learning_rate": 3.5847547974413645e-05,
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+      "step": 1000
+    },
+    {
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