---
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
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# 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