File size: 1,769 Bytes
2a7e8e8 7076d2e 2a7e8e8 38d2e45 5457689 25373ed 122bcbf 25373ed 82a36b9 2a7e8e8 25373ed 7762f07 25373ed 7762f07 25373ed 7762f07 25373ed 7762f07 25373ed 7762f07 25373ed 2a7e8e8 ac0ee23 25373ed 2a7e8e8 b35fc4c e244c56 25373ed |
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 |
---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vulnerability-severity-classification-roberta-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. -->
# vulnerability-severity-classification-roberta-base
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5068
- Accuracy: 0.8288
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.7177 | 1.0 | 27141 | 0.6449 | 0.7401 |
| 0.449 | 2.0 | 54282 | 0.5911 | 0.7727 |
| 0.4575 | 3.0 | 81423 | 0.5174 | 0.8015 |
| 0.4397 | 4.0 | 108564 | 0.4977 | 0.8193 |
| 0.3868 | 5.0 | 135705 | 0.5068 | 0.8288 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
|