---
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
model-index:
- name: fine-tuned-distilroberta-nosql-injection
  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. -->

# fine-tuned-distilroberta-nosql-injection

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/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