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---
library_name: transformers
license: apache-2.0
base_model: hfl/chinese-macbert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vulnerability-severity-classification-chinese-macbert-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-chinese-macbert-base

This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6118
- Accuracy: 0.7832

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5706        | 1.0   | 3511  | 0.5875          | 0.7503   |
| 0.5364        | 2.0   | 7022  | 0.5596          | 0.7702   |
| 0.5483        | 3.0   | 10533 | 0.5518          | 0.7768   |
| 0.4161        | 4.0   | 14044 | 0.5757          | 0.7838   |
| 0.351         | 5.0   | 17555 | 0.6118          | 0.7832   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1