---
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-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-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: 0.5844
- Accuracy Score: 0.6537
- F1 Score: 0.5784
- Precision Score: 0.5171
- Recall Score: 0.6562

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | F1 Score | Precision Score | Recall Score |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:--------:|:---------------:|:------------:|
| 0.6795        | 1.0   | 342  | 0.6435          | 0.6120         | 0.3099   | 0.1896          | 0.8470       |
| 0.6168        | 2.0   | 684  | 0.5960          | 0.6395         | 0.4316   | 0.2980          | 0.7824       |
| 0.5605        | 3.0   | 1026 | 0.5844          | 0.6537         | 0.5784   | 0.5171          | 0.6562       |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0