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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: ModernBERT-base-ft-code-defect-detection-10e-4k
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. -->
# ModernBERT-base-ft-code-defect-detection-10e-4k
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0516
- Accuracy Score: 0.6369
- F1 Score: 0.6091
- Precision Score: 0.6159
- Recall Score: 0.6025
## 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: 8e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | F1 Score | Precision Score | Recall Score |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:--------:|:---------------:|:------------:|
| 0.6768 | 1.0 | 342 | 0.6130 | 0.6358 | 0.5728 | 0.5315 | 0.6210 |
| 0.5902 | 2.0 | 684 | 0.5828 | 0.6654 | 0.5421 | 0.4311 | 0.7301 |
| 0.5346 | 3.0 | 1026 | 0.5995 | 0.6585 | 0.4744 | 0.3355 | 0.8096 |
| 0.4583 | 4.0 | 1368 | 0.6115 | 0.6812 | 0.6085 | 0.5394 | 0.6979 |
| 0.3722 | 5.0 | 1710 | 0.6749 | 0.6482 | 0.6197 | 0.6239 | 0.6156 |
| 0.2896 | 6.0 | 2052 | 0.8197 | 0.6490 | 0.6087 | 0.5944 | 0.6237 |
| 0.2234 | 7.0 | 2394 | 0.9451 | 0.6490 | 0.6019 | 0.5777 | 0.6282 |
| 0.1655 | 8.0 | 2736 | 1.1632 | 0.6354 | 0.6115 | 0.6247 | 0.5989 |
| 0.1151 | 9.0 | 3078 | 1.4168 | 0.6387 | 0.6063 | 0.6056 | 0.6070 |
| 0.0684 | 10.0 | 3420 | 2.0516 | 0.6369 | 0.6091 | 0.6159 | 0.6025 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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