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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: fine-tuned-roberta-nosql-injection |
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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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# fine-tuned-roberta-nosql-injection |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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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: 2e-05 |
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- train_batch_size: 4 |
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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: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 75 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.2572 | 1.0 | 158 | 0.2235 | |
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| 0.1175 | 2.0 | 316 | 0.0325 | |
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| 0.0454 | 3.0 | 474 | 0.1079 | |
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| 0.05 | 4.0 | 632 | 0.0212 | |
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| 0.0677 | 5.0 | 790 | 0.0713 | |
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| 0.0821 | 6.0 | 948 | 0.0007 | |
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| 0.0259 | 7.0 | 1106 | 0.0277 | |
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| 0.0422 | 8.0 | 1264 | 0.0068 | |
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| 0.0282 | 9.0 | 1422 | 0.0492 | |
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| 0.0273 | 10.0 | 1580 | 0.0008 | |
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| 0.0272 | 11.0 | 1738 | 0.0256 | |
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| 0.0859 | 12.0 | 1896 | 0.0000 | |
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| 0.0271 | 13.0 | 2054 | 0.0001 | |
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| 0.0058 | 14.0 | 2212 | 0.0583 | |
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| 0.0121 | 15.0 | 2370 | 0.0257 | |
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| 0.0189 | 16.0 | 2528 | 0.0631 | |
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| 0.0275 | 17.0 | 2686 | 0.0186 | |
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| 0.006 | 18.0 | 2844 | 0.0027 | |
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| 0.025 | 19.0 | 3002 | 0.0349 | |
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| 0.0377 | 20.0 | 3160 | 0.0004 | |
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| 0.0108 | 21.0 | 3318 | 0.0091 | |
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| 0.0233 | 22.0 | 3476 | 0.0772 | |
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| 0.0216 | 23.0 | 3634 | 0.0000 | |
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| 0.0255 | 24.0 | 3792 | 0.0607 | |
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| 0.0211 | 25.0 | 3950 | 0.0251 | |
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| 0.037 | 26.0 | 4108 | 0.0223 | |
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| 0.0057 | 27.0 | 4266 | 0.0375 | |
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| 0.0464 | 28.0 | 4424 | 0.0659 | |
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| 0.0446 | 29.0 | 4582 | 0.0235 | |
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| 0.0453 | 30.0 | 4740 | 0.0278 | |
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| 0.0033 | 31.0 | 4898 | 0.0417 | |
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| 0.0104 | 32.0 | 5056 | 0.0544 | |
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| 0.0084 | 33.0 | 5214 | 0.0000 | |
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| 0.0004 | 34.0 | 5372 | 0.0247 | |
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| 0.0185 | 35.0 | 5530 | 0.0002 | |
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| 0.0165 | 36.0 | 5688 | 0.0000 | |
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| 0.0381 | 37.0 | 5846 | 0.0000 | |
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| 0.0281 | 38.0 | 6004 | 0.0000 | |
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| 0.006 | 39.0 | 6162 | 0.0085 | |
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| 0.0083 | 40.0 | 6320 | 0.0000 | |
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| 0.0101 | 41.0 | 6478 | 0.0006 | |
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| 0.0282 | 42.0 | 6636 | 0.0003 | |
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| 0.0202 | 43.0 | 6794 | 0.0205 | |
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| 0.0053 | 44.0 | 6952 | 0.0275 | |
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| 0.0293 | 45.0 | 7110 | 0.0485 | |
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| 0.0119 | 46.0 | 7268 | 0.0000 | |
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| 0.0045 | 47.0 | 7426 | 0.0000 | |
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| 0.0066 | 48.0 | 7584 | 0.0268 | |
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| 0.0191 | 49.0 | 7742 | 0.0103 | |
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| 0.0007 | 50.0 | 7900 | 0.0386 | |
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| 0.0072 | 51.0 | 8058 | 0.0000 | |
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| 0.0031 | 52.0 | 8216 | 0.0000 | |
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| 0.0037 | 53.0 | 8374 | 0.0225 | |
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| 0.0135 | 54.0 | 8532 | 0.0003 | |
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| 0.0015 | 55.0 | 8690 | 0.0002 | |
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| 0.0066 | 56.0 | 8848 | 0.0025 | |
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| 0.0281 | 57.0 | 9006 | 0.0145 | |
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| 0.012 | 58.0 | 9164 | 0.0000 | |
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| 0.0065 | 59.0 | 9322 | 0.0000 | |
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| 0.0054 | 60.0 | 9480 | 0.0082 | |
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| 0.0104 | 61.0 | 9638 | 0.0000 | |
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| 0.0005 | 62.0 | 9796 | 0.0303 | |
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| 0.005 | 63.0 | 9954 | 0.0000 | |
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| 0.0092 | 64.0 | 10112 | 0.0412 | |
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| 0.0055 | 65.0 | 10270 | 0.0191 | |
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| 0.0092 | 66.0 | 10428 | 0.0158 | |
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| 0.0065 | 67.0 | 10586 | 0.0087 | |
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| 0.0004 | 68.0 | 10744 | 0.0000 | |
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| 0.0068 | 69.0 | 10902 | 0.0044 | |
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| 0.0043 | 70.0 | 11060 | 0.0022 | |
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| 0.0055 | 71.0 | 11218 | 0.0009 | |
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| 0.0063 | 72.0 | 11376 | 0.0000 | |
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| 0.0022 | 73.0 | 11534 | 0.0006 | |
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| 0.0116 | 74.0 | 11692 | 0.0014 | |
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| 0.0043 | 75.0 | 11850 | 0.0000 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.11.0 |
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