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fine-tuned-distilroberta-nosql-injection
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 75
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 79 | 0.3011 |
| 1.3847 | 2.0 | 158 | 0.1010 |
| 0.2018 | 3.0 | 237 | 0.0340 |
| 0.0999 | 4.0 | 316 | 0.0556 |
| 0.0999 | 5.0 | 395 | 0.0001 |
| 0.0509 | 6.0 | 474 | 0.0817 |
| 0.072 | 7.0 | 553 | 0.0001 |
| 0.0425 | 8.0 | 632 | 0.0395 |
| 0.0559 | 9.0 | 711 | 0.1041 |
| 0.0559 | 10.0 | 790 | 0.0014 |
| 0.0336 | 11.0 | 869 | 0.0284 |
| 0.0326 | 12.0 | 948 | 0.0251 |
| 0.0204 | 13.0 | 1027 | 0.0046 |
| 0.0136 | 14.0 | 1106 | 0.0293 |
| 0.0136 | 15.0 | 1185 | 0.0495 |
| 0.0318 | 16.0 | 1264 | 0.0011 |
| 0.0278 | 17.0 | 1343 | 0.0003 |
| 0.0201 | 18.0 | 1422 | 0.0004 |
| 0.0202 | 19.0 | 1501 | 0.0194 |
| 0.0202 | 20.0 | 1580 | 0.0202 |
| 0.0282 | 21.0 | 1659 | 0.0008 |
| 0.0277 | 22.0 | 1738 | 0.0401 |
| 0.0121 | 23.0 | 1817 | 0.0405 |
| 0.0121 | 24.0 | 1896 | 0.0230 |
| 0.0278 | 25.0 | 1975 | 0.0067 |
| 0.023 | 26.0 | 2054 | 0.0879 |
| 0.0247 | 27.0 | 2133 | 0.0168 |
| 0.0348 | 28.0 | 2212 | 0.0373 |
| 0.0348 | 29.0 | 2291 | 0.0466 |
| 0.0157 | 30.0 | 2370 | 0.0376 |
| 0.023 | 31.0 | 2449 | 0.0470 |
| 0.0101 | 32.0 | 2528 | 0.0522 |
| 0.0123 | 33.0 | 2607 | 0.0000 |
| 0.0123 | 34.0 | 2686 | 0.0245 |
| 0.0128 | 35.0 | 2765 | 0.0090 |
| 0.0089 | 36.0 | 2844 | 0.0000 |
| 0.0219 | 37.0 | 2923 | 0.0000 |
| 0.0082 | 38.0 | 3002 | 0.0001 |
| 0.0082 | 39.0 | 3081 | 0.0504 |
| 0.0123 | 40.0 | 3160 | 0.0000 |
| 0.0078 | 41.0 | 3239 | 0.0096 |
| 0.0217 | 42.0 | 3318 | 0.0019 |
| 0.0217 | 43.0 | 3397 | 0.0535 |
| 0.0117 | 44.0 | 3476 | 0.0253 |
| 0.0218 | 45.0 | 3555 | 0.0330 |
| 0.0171 | 46.0 | 3634 | 0.0000 |
| 0.0056 | 47.0 | 3713 | 0.0002 |
| 0.0056 | 48.0 | 3792 | 0.0025 |
| 0.0111 | 49.0 | 3871 | 0.0162 |
| 0.0051 | 50.0 | 3950 | 0.0010 |
| 0.0138 | 51.0 | 4029 | 0.0000 |
| 0.0041 | 52.0 | 4108 | 0.0000 |
| 0.0041 | 53.0 | 4187 | 0.0186 |
| 0.0103 | 54.0 | 4266 | 0.0001 |
| 0.0154 | 55.0 | 4345 | 0.0006 |
| 0.01 | 56.0 | 4424 | 0.0064 |
| 0.0076 | 57.0 | 4503 | 0.0044 |
| 0.0076 | 58.0 | 4582 | 0.0000 |
| 0.0155 | 59.0 | 4661 | 0.0000 |
| 0.0114 | 60.0 | 4740 | 0.0089 |
| 0.0176 | 61.0 | 4819 | 0.0000 |
| 0.0176 | 62.0 | 4898 | 0.0414 |
| 0.0037 | 63.0 | 4977 | 0.0000 |
| 0.0035 | 64.0 | 5056 | 0.0697 |
| 0.0086 | 65.0 | 5135 | 0.0206 |
| 0.0056 | 66.0 | 5214 | 0.0222 |
| 0.0056 | 67.0 | 5293 | 0.0365 |
| 0.0077 | 68.0 | 5372 | 0.0000 |
| 0.0109 | 69.0 | 5451 | 0.0004 |
| 0.0076 | 70.0 | 5530 | 0.0002 |
| 0.0022 | 71.0 | 5609 | 0.0001 |
| 0.0022 | 72.0 | 5688 | 0.0000 |
| 0.0078 | 73.0 | 5767 | 0.0011 |
| 0.0128 | 74.0 | 5846 | 0.0005 |
| 0.0047 | 75.0 | 5925 | 0.0000 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.11.0
