File size: 4,478 Bytes
5e4ff2d |
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 |
---
library_name: transformers
base_model: microsoft/graphcodebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cwe-parent-vulnerability-classification-microsoft-graphcodebert-base
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-microsoft-graphcodebert-base
This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8233
- Accuracy: 0.6517
- F1 Macro: 0.3050
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.255 | 1.0 | 25 | 3.2962 | 0.0225 | 0.0083 |
| 3.1345 | 2.0 | 50 | 3.3120 | 0.2697 | 0.0544 |
| 3.0539 | 3.0 | 75 | 3.3627 | 0.3820 | 0.0582 |
| 2.9349 | 4.0 | 100 | 3.3122 | 0.3596 | 0.0921 |
| 2.9555 | 5.0 | 125 | 3.2926 | 0.4045 | 0.1695 |
| 2.7748 | 6.0 | 150 | 3.3514 | 0.4607 | 0.1757 |
| 2.803 | 7.0 | 175 | 3.3219 | 0.5169 | 0.1884 |
| 2.67 | 8.0 | 200 | 3.2696 | 0.4831 | 0.2198 |
| 2.5684 | 9.0 | 225 | 3.2657 | 0.4944 | 0.2445 |
| 2.4226 | 10.0 | 250 | 3.1999 | 0.3371 | 0.1697 |
| 2.4615 | 11.0 | 275 | 3.1954 | 0.4270 | 0.1996 |
| 2.2738 | 12.0 | 300 | 3.1108 | 0.4157 | 0.1954 |
| 2.2423 | 13.0 | 325 | 3.0714 | 0.3933 | 0.1862 |
| 2.2066 | 14.0 | 350 | 3.0598 | 0.3820 | 0.1975 |
| 1.9919 | 15.0 | 375 | 3.0252 | 0.4382 | 0.1992 |
| 1.9622 | 16.0 | 400 | 2.9873 | 0.3708 | 0.1981 |
| 1.9415 | 17.0 | 425 | 2.9783 | 0.4494 | 0.2166 |
| 1.8459 | 18.0 | 450 | 2.9570 | 0.4831 | 0.2304 |
| 1.7008 | 19.0 | 475 | 2.9116 | 0.4607 | 0.2104 |
| 1.6705 | 20.0 | 500 | 2.9134 | 0.4607 | 0.2152 |
| 1.6422 | 21.0 | 525 | 2.9341 | 0.4607 | 0.2554 |
| 1.4982 | 22.0 | 550 | 2.8852 | 0.5056 | 0.2604 |
| 1.5523 | 23.0 | 575 | 2.9029 | 0.5056 | 0.2555 |
| 1.3784 | 24.0 | 600 | 2.8782 | 0.5393 | 0.2840 |
| 1.4479 | 25.0 | 625 | 2.8525 | 0.5730 | 0.2558 |
| 1.2508 | 26.0 | 650 | 2.9039 | 0.5730 | 0.2563 |
| 1.3662 | 27.0 | 675 | 2.8784 | 0.6067 | 0.3081 |
| 1.2199 | 28.0 | 700 | 2.8704 | 0.6180 | 0.2729 |
| 1.1903 | 29.0 | 725 | 2.8577 | 0.6404 | 0.2811 |
| 1.1881 | 30.0 | 750 | 2.8612 | 0.6404 | 0.2890 |
| 1.1572 | 31.0 | 775 | 2.8371 | 0.6292 | 0.2968 |
| 1.0623 | 32.0 | 800 | 2.8413 | 0.6404 | 0.2969 |
| 1.0405 | 33.0 | 825 | 2.8233 | 0.6517 | 0.3050 |
| 1.1084 | 34.0 | 850 | 2.8323 | 0.6404 | 0.3012 |
| 1.0211 | 35.0 | 875 | 2.8341 | 0.6404 | 0.3042 |
| 1.0215 | 36.0 | 900 | 2.8391 | 0.6404 | 0.3006 |
| 0.9438 | 37.0 | 925 | 2.8321 | 0.6404 | 0.3006 |
| 0.9383 | 38.0 | 950 | 2.8266 | 0.6404 | 0.3012 |
| 1.017 | 39.0 | 975 | 2.8236 | 0.6404 | 0.3037 |
| 0.9262 | 40.0 | 1000 | 2.8264 | 0.6404 | 0.3037 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
|