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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
|