---
library_name: transformers
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: CodeBERTa-small-v1-sourcecode-detection-clf
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CodeBERTa-small-v1-sourcecode-detection-clf

This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0041
- F1: 1.0
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0

## 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: 0.0003
- train_batch_size: 320
- eval_batch_size: 320
- seed: 2024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log        | 0     | 0    | 0.6985          | 0.3223 | 0.49     | 0.2401    | 0.49   |
| 0.0001        | 12.5  | 50   | 0.0044          | 1.0    | 1.0      | 1.0       | 1.0    |
| 0.0001        | 25.0  | 100  | 0.0041          | 1.0    | 1.0      | 1.0       | 1.0    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3