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README.md +124 -0
all_results.json +74 -0
eval_results.json +68 -0
model.safetensors +1 -1
train_results.json +9 -0
trainer_state.json +700 -0

README.md ADDED Viewed

	@@ -0,0 +1,124 @@

+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: distilbert-base-uncased-three_v2
+  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-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

all_results.json ADDED Viewed

	@@ -0,0 +1,74 @@

+{
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+    "eval_ACCOUNTNAME_f1": 0.975378787878788,
+    "eval_ACCOUNTNUMBER_f1": 0.9909255898366606,
+    "eval_AGE_f1": 0.896842105263158,
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+    "train_steps_per_second": 0.708
+}

eval_results.json ADDED Viewed

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+    "eval_steps_per_second": 2.104
+}

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train_results.json ADDED Viewed

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+{
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trainer_state.json ADDED Viewed

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+{
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