---
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
model-index:
- name: CodeBert-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. -->

# CodeBert-finetuned-the-stack-bash

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.6895

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 8.1473        | 0.05  | 500   | 7.4270          |
| 6.9372        | 0.1   | 1000  | 6.9409          |
| 6.167         | 0.15  | 1500  | 6.6749          |
| 7.9745        | 0.2   | 2000  | 6.4053          |
| 7.2576        | 0.25  | 2500  | 6.2217          |
| 6.451         | 0.3   | 3000  | 6.0992          |
| 6.3218        | 0.35  | 3500  | 6.0231          |
| 6.3115        | 0.4   | 4000  | 6.0302          |
| 6.6343        | 0.45  | 4500  | 5.8745          |
| 6.1515        | 0.5   | 5000  | 5.8281          |
| 6.3992        | 0.55  | 5500  | 5.7614          |
| 6.8421        | 0.6   | 6000  | 5.8745          |
| 6.0542        | 0.65  | 6500  | 5.7452          |
| 5.3206        | 0.7   | 7000  | 5.7668          |
| 6.121         | 0.75  | 7500  | 5.6950          |
| 6.5956        | 0.8   | 8000  | 5.6926          |
| 5.8667        | 0.85  | 8500  | 5.6904          |
| 6.0287        | 0.9   | 9000  | 5.6803          |
| 5.8417        | 0.95  | 9500  | 5.6747          |
| 6.9719        | 1.0   | 10000 | 5.6895          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0