---
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 ejschwartz/oo-method-test-split dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3303
- Accuracy: 0.9161
- Best Accuracy: 0.9161

## 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: 2.386135927313411e-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: 887

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Best Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|
| 0.3788        | 0.02  | 178  | 0.6188          | 0.8470   | 0.8470        |
| 0.1456        | 0.04  | 356  | 0.6572          | 0.8519   | 0.8519        |
| 0.17          | 0.05  | 534  | 0.4926          | 0.8798   | 0.8798        |
| 0.1162        | 0.07  | 712  | 0.3303          | 0.9161   | 0.9161        |


### Framework versions

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