---
base_model: huggingface/CodeBERTa-small-v1
tags:
- generated_from_trainer
model-index:
- name: huggingfaceCodeBerta-finetuned-the-stack-bash
  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. -->

# huggingfaceCodeBerta-finetuned-the-stack-bash

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: 2.4191

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.3233        | 0.05  | 500   | 3.4143          |
| 3.2135        | 0.1   | 1000  | 3.0184          |
| 3.1977        | 0.15  | 1500  | 2.8537          |
| 2.9303        | 0.2   | 2000  | 2.7396          |
| 3.1618        | 0.25  | 2500  | 2.6954          |
| 2.9122        | 0.3   | 3000  | 2.6338          |
| 2.8965        | 0.35  | 3500  | 2.5881          |
| 2.599         | 0.4   | 4000  | 2.5677          |
| 2.8213        | 0.45  | 4500  | 2.5247          |
| 2.516         | 0.5   | 5000  | 2.5118          |
| 2.8975        | 0.55  | 5500  | 2.4817          |
| 2.3503        | 0.6   | 6000  | 2.4803          |
| 2.1736        | 0.65  | 6500  | 2.4650          |
| 2.8777        | 0.7   | 7000  | 2.4394          |
| 2.5809        | 0.75  | 7500  | 2.4391          |
| 2.6986        | 0.8   | 8000  | 2.4199          |
| 3.2199        | 0.85  | 8500  | 2.4354          |
| 2.3214        | 0.9   | 9000  | 2.4174          |
| 0.7788        | 0.95  | 9500  | 2.4156          |
| 2.6361        | 1.0   | 10000 | 2.4191          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1