File size: 1,769 Bytes
2a7e8e8 7076d2e 2a7e8e8 38d2e45 5457689 ab9b1ed 122bcbf ab9b1ed 82a36b9 2a7e8e8 ab9b1ed 2a7e8e8 ab9b1ed 2a7e8e8 ab9b1ed 2a7e8e8 ab9b1ed 2a7e8e8 ab9b1ed 2a7e8e8 05a3c54 2a7e8e8 ac0ee23 ab9b1ed 2a7e8e8 85a2228 ab9b1ed |
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: 0.5095
- Accuracy: 0.8245
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.5087 | 1.0 | 26400 | 0.6427 | 0.7397 |
| 0.4433 | 2.0 | 52800 | 0.5840 | 0.7693 |
| 0.5995 | 3.0 | 79200 | 0.5373 | 0.7951 |
| 0.4051 | 4.0 | 105600 | 0.5059 | 0.8154 |
| 0.38 | 5.0 | 132000 | 0.5095 | 0.8245 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.1
|