File size: 4,473 Bytes
ebbf898 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-distilbert-base-uncased
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. -->
# cwe-parent-vulnerability-classification-distilbert-base-uncased
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3946
- Accuracy: 0.7416
- F1 Macro: 0.4136
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.2586 | 1.0 | 25 | 3.2817 | 0.0225 | 0.0037 |
| 3.1726 | 2.0 | 50 | 3.2811 | 0.0225 | 0.0037 |
| 3.1195 | 3.0 | 75 | 3.2705 | 0.0225 | 0.0037 |
| 3.0213 | 4.0 | 100 | 3.2327 | 0.0449 | 0.0325 |
| 3.0235 | 5.0 | 125 | 3.2046 | 0.2247 | 0.0830 |
| 2.931 | 6.0 | 150 | 3.2138 | 0.2697 | 0.0725 |
| 2.9104 | 7.0 | 175 | 3.1642 | 0.4382 | 0.1117 |
| 2.779 | 8.0 | 200 | 3.1058 | 0.4831 | 0.1095 |
| 2.7528 | 9.0 | 225 | 3.0725 | 0.5169 | 0.1238 |
| 2.6453 | 10.0 | 250 | 3.0537 | 0.5730 | 0.2290 |
| 2.6262 | 11.0 | 275 | 3.0154 | 0.5618 | 0.2103 |
| 2.4852 | 12.0 | 300 | 2.9611 | 0.5955 | 0.3516 |
| 2.3778 | 13.0 | 325 | 2.9121 | 0.5955 | 0.3256 |
| 2.3381 | 14.0 | 350 | 2.8414 | 0.6067 | 0.3057 |
| 2.2415 | 15.0 | 375 | 2.8161 | 0.6180 | 0.3610 |
| 2.0991 | 16.0 | 400 | 2.7636 | 0.6180 | 0.3520 |
| 2.0469 | 17.0 | 425 | 2.7049 | 0.6180 | 0.3175 |
| 1.9623 | 18.0 | 450 | 2.7100 | 0.6404 | 0.3767 |
| 1.921 | 19.0 | 475 | 2.6304 | 0.6404 | 0.3320 |
| 1.8045 | 20.0 | 500 | 2.6552 | 0.6404 | 0.3130 |
| 1.7417 | 21.0 | 525 | 2.5960 | 0.6517 | 0.3082 |
| 1.7004 | 22.0 | 550 | 2.5777 | 0.6404 | 0.3183 |
| 1.6295 | 23.0 | 575 | 2.5849 | 0.6742 | 0.3602 |
| 1.5823 | 24.0 | 600 | 2.5379 | 0.6742 | 0.345 |
| 1.4711 | 25.0 | 625 | 2.5262 | 0.6742 | 0.3512 |
| 1.4868 | 26.0 | 650 | 2.4962 | 0.7079 | 0.3970 |
| 1.4563 | 27.0 | 675 | 2.4695 | 0.6854 | 0.3438 |
| 1.3601 | 28.0 | 700 | 2.4549 | 0.6854 | 0.3438 |
| 1.2847 | 29.0 | 725 | 2.4691 | 0.7079 | 0.3688 |
| 1.2883 | 30.0 | 750 | 2.4587 | 0.7079 | 0.3966 |
| 1.316 | 31.0 | 775 | 2.4454 | 0.7191 | 0.3623 |
| 1.1845 | 32.0 | 800 | 2.4432 | 0.7416 | 0.4111 |
| 1.24 | 33.0 | 825 | 2.4280 | 0.7079 | 0.3980 |
| 1.1163 | 34.0 | 850 | 2.4179 | 0.7416 | 0.3871 |
| 1.1728 | 35.0 | 875 | 2.4326 | 0.7528 | 0.4201 |
| 1.1013 | 36.0 | 900 | 2.4116 | 0.7416 | 0.4136 |
| 1.1612 | 37.0 | 925 | 2.3985 | 0.7416 | 0.4136 |
| 1.1472 | 38.0 | 950 | 2.3956 | 0.7416 | 0.4136 |
| 1.069 | 39.0 | 975 | 2.3946 | 0.7416 | 0.4136 |
| 1.0865 | 40.0 | 1000 | 2.3983 | 0.7528 | 0.4201 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
|