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---
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
should probably proofread and complete it, then remove this comment. -->
# 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: 0.0719
- F1: 0.9900
- Accuracy: 0.99
- Precision: 0.9902
- Recall: 0.99
## 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: 256
- eval_batch_size: 256
- 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 |
| 0.0 | 12.5 | 50 | 0.0716 | 0.9900 | 0.99 | 0.9902 | 0.99 |
| 0.0 | 25.0 | 100 | 0.0719 | 0.9900 | 0.99 | 0.9902 | 0.99 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
|