---
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: oo-method-test-model-bylibrary
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# oo-method-test-model-bylibrary

This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1651
- Accuracy: 0.9439
- Best Accuracy: 0.9439

## 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: 1.238e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 915

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Best Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|
| 0.4914        | 0.19  | 183  | 0.2747          | 0.8956   | 0.8956        |
| 0.2639        | 0.37  | 366  | 0.3623          | 0.8925   | 0.8956        |
| 0.2105        | 0.56  | 549  | 0.2257          | 0.9224   | 0.9224        |
| 0.1669        | 0.74  | 732  | 0.1651          | 0.9439   | 0.9439        |
| 0.1037        | 0.93  | 915  | 0.1676          | 0.9408   | 0.9439        |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3