Edison
commited on
Commit
•
4aac43b
1
Parent(s):
b32141a
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,76 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: neuralsentry/distilbert-git-commits-mlm
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
metrics:
|
| 7 |
+
- accuracy
|
| 8 |
+
- precision
|
| 9 |
+
- recall
|
| 10 |
+
- f1
|
| 11 |
+
model-index:
|
| 12 |
+
- name: vulnfixClassification-DistilBERT-DCMB
|
| 13 |
+
results: []
|
| 14 |
+
---
|
| 15 |
+
|
| 16 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 17 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 18 |
+
|
| 19 |
+
# vulnfixClassification-DistilBERT-DCMB
|
| 20 |
+
|
| 21 |
+
This model is a fine-tuned version of [neuralsentry/distilbert-git-commits-mlm](https://huggingface.co/neuralsentry/distilbert-git-commits-mlm) on the None dataset.
|
| 22 |
+
It achieves the following results on the evaluation set:
|
| 23 |
+
- Loss: 0.1769
|
| 24 |
+
- Accuracy: 0.9713
|
| 25 |
+
- Precision: 0.9778
|
| 26 |
+
- Recall: 0.9667
|
| 27 |
+
- F1: 0.9722
|
| 28 |
+
- Roc Auc: 0.9715
|
| 29 |
+
|
| 30 |
+
## Model description
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Intended uses & limitations
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training and evaluation data
|
| 39 |
+
|
| 40 |
+
More information needed
|
| 41 |
+
|
| 42 |
+
## Training procedure
|
| 43 |
+
|
| 44 |
+
### Training hyperparameters
|
| 45 |
+
|
| 46 |
+
The following hyperparameters were used during training:
|
| 47 |
+
- learning_rate: 0.0001
|
| 48 |
+
- train_batch_size: 256
|
| 49 |
+
- eval_batch_size: 256
|
| 50 |
+
- seed: 420
|
| 51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 52 |
+
- lr_scheduler_type: linear
|
| 53 |
+
- num_epochs: 10.0
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
|
| 59 |
+
| 0.2594 | 1.0 | 110 | 0.1452 | 0.9520 | 0.9672 | 0.9395 | 0.9532 | 0.9525 |
|
| 60 |
+
| 0.0966 | 2.0 | 220 | 0.1103 | 0.9644 | 0.9714 | 0.9599 | 0.9656 | 0.9646 |
|
| 61 |
+
| 0.0499 | 3.0 | 330 | 0.1193 | 0.9640 | 0.9679 | 0.9626 | 0.9653 | 0.9641 |
|
| 62 |
+
| 0.0251 | 4.0 | 440 | 0.1289 | 0.9623 | 0.9577 | 0.9703 | 0.9640 | 0.9619 |
|
| 63 |
+
| 0.0132 | 5.0 | 550 | 0.1495 | 0.9660 | 0.9660 | 0.9687 | 0.9673 | 0.9659 |
|
| 64 |
+
| 0.0086 | 6.0 | 660 | 0.1759 | 0.9684 | 0.9830 | 0.9558 | 0.9692 | 0.9689 |
|
| 65 |
+
| 0.0054 | 7.0 | 770 | 0.1568 | 0.9700 | 0.9788 | 0.9632 | 0.9709 | 0.9703 |
|
| 66 |
+
| 0.0023 | 8.0 | 880 | 0.1775 | 0.9707 | 0.9754 | 0.9681 | 0.9717 | 0.9708 |
|
| 67 |
+
| 0.0023 | 9.0 | 990 | 0.1752 | 0.9710 | 0.9794 | 0.9646 | 0.9719 | 0.9713 |
|
| 68 |
+
| 0.0011 | 10.0 | 1100 | 0.1769 | 0.9713 | 0.9778 | 0.9667 | 0.9722 | 0.9715 |
|
| 69 |
+
|
| 70 |
+
|
| 71 |
+
### Framework versions
|
| 72 |
+
|
| 73 |
+
- Transformers 4.31.0
|
| 74 |
+
- Pytorch 2.0.1+cu118
|
| 75 |
+
- Datasets 2.14.2
|
| 76 |
+
- Tokenizers 0.13.3
|