---
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: 0.0171
- F1: 0.9975
- Accuracy: 0.9975
- Precision: 0.9975
- Recall: 0.9975

## 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
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log        | 0      | 0    | 0.6981          | 0.3337 | 0.5001   | 0.6162    | 0.5001 |
| 0.0294        | 0.1420 | 1000 | 0.0398          | 0.9947 | 0.9947   | 0.9947    | 0.9947 |
| 0.0076        | 0.2841 | 2000 | 0.0211          | 0.9968 | 0.9968   | 0.9968    | 0.9968 |
| 0.0053        | 0.4261 | 3000 | 0.0188          | 0.9973 | 0.9973   | 0.9973    | 0.9973 |
| 0.0056        | 0.5681 | 4000 | 0.0166          | 0.9976 | 0.9976   | 0.9976    | 0.9976 |
| 0.0044        | 0.7101 | 5000 | 0.0172          | 0.9975 | 0.9975   | 0.9975    | 0.9975 |
| 0.0009        | 0.8522 | 6000 | 0.0171          | 0.9975 | 0.9975   | 0.9975    | 0.9975 |
| 0.0052        | 0.9942 | 7000 | 0.0171          | 0.9975 | 0.9975   | 0.9975    | 0.9975 |


### Framework versions

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