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--- |
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license: mit |
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base_model: microsoft/deberta-v3-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deberta-v3-base_finetuned_bluegennx_run2 |
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results: [] |
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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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# deberta-v3-base_finetuned_bluegennx_run2 |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0737 |
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- Overall Precision: 0.7273 |
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- Overall Recall: 0.7428 |
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- Overall F1: 0.7350 |
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- Overall Accuracy: 0.9752 |
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- Aadhar F1: 0.8128 |
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- Age F1: 0.4700 |
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- City F1: 0.7686 |
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- Country F1: 0.7226 |
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- Creditcardcvv F1: 0.7531 |
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- Creditcardnumber F1: 0.8109 |
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- Date F1: 0.7126 |
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- Dateofbirth F1: 0.7262 |
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- Email F1: 0.6935 |
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- Expiry F1: 0.6621 |
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- Organization F1: 0.7623 |
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- Pan F1: 0.7772 |
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- Person F1: 0.7568 |
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- Phonenumber F1: 0.8194 |
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- Secondary F1: 0.6278 |
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- State F1: 0.7735 |
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- Time F1: 0.7856 |
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- Url F1: 0.5824 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 8 |
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- eval_batch_size: 8 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Aadhar F1 | Age F1 | City F1 | Country F1 | Creditcardcvv F1 | Creditcardnumber F1 | Date F1 | Dateofbirth F1 | Email F1 | Expiry F1 | Organization F1 | Pan F1 | Person F1 | Phonenumber F1 | Secondary F1 | State F1 | Time F1 | Url F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:---------:|:------:|:-------:|:----------:|:----------------:|:-------------------:|:-------:|:--------------:|:--------:|:---------:|:---------------:|:------:|:---------:|:--------------:|:------------:|:--------:|:-------:|:------:| |
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| 0.1576 | 1.0 | 3893 | 0.1289 | 0.5166 | 0.5445 | 0.5302 | 0.9559 | 0.6073 | 0.1745 | 0.5790 | 0.5463 | 0.5707 | 0.6816 | 0.4834 | 0.4489 | 0.4808 | 0.5009 | 0.6085 | 0.5667 | 0.5383 | 0.5811 | 0.4273 | 0.6592 | 0.5824 | 0.2314 | |
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| 0.1075 | 2.0 | 7786 | 0.1151 | 0.5991 | 0.6001 | 0.5996 | 0.9610 | 0.7012 | 0.2439 | 0.6649 | 0.5689 | 0.6735 | 0.6950 | 0.5229 | 0.6065 | 0.5176 | 0.4904 | 0.6910 | 0.7248 | 0.5493 | 0.6810 | 0.5406 | 0.6382 | 0.6816 | 0.3492 | |
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| 0.0804 | 3.0 | 11679 | 0.0841 | 0.6783 | 0.7045 | 0.6911 | 0.9709 | 0.7826 | 0.3554 | 0.7372 | 0.6909 | 0.7276 | 0.7621 | 0.6459 | 0.7272 | 0.6303 | 0.6235 | 0.7329 | 0.7324 | 0.6816 | 0.7855 | 0.5912 | 0.7620 | 0.7529 | 0.4652 | |
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| 0.0532 | 4.0 | 15572 | 0.0737 | 0.7273 | 0.7428 | 0.7350 | 0.9752 | 0.8128 | 0.4700 | 0.7686 | 0.7226 | 0.7531 | 0.8109 | 0.7126 | 0.7262 | 0.6935 | 0.6621 | 0.7623 | 0.7772 | 0.7568 | 0.8194 | 0.6278 | 0.7735 | 0.7856 | 0.5824 | |
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| 0.0381 | 5.0 | 19465 | 0.0753 | 0.7372 | 0.7589 | 0.7479 | 0.9768 | 0.8278 | 0.4925 | 0.7705 | 0.7185 | 0.7832 | 0.8258 | 0.7231 | 0.7605 | 0.7027 | 0.6676 | 0.7700 | 0.8011 | 0.7591 | 0.8305 | 0.6558 | 0.7828 | 0.7978 | 0.6144 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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