---
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: 2.0540

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.3461        | 0.05  | 500   | 4.6252          |
| 3.028         | 0.1   | 1000  | 3.2745          |
| 2.978         | 0.15  | 1500  | 2.8286          |
| 3.2116        | 0.2   | 2000  | 2.5426          |
| 2.9872        | 0.25  | 2500  | 2.4032          |
| 2.5853        | 0.3   | 3000  | 2.3376          |
| 2.6977        | 0.35  | 3500  | 2.2992          |
| 2.5997        | 0.4   | 4000  | 2.2394          |
| 2.3712        | 0.45  | 4500  | 2.1834          |
| 2.1944        | 0.5   | 5000  | 2.1589          |
| 2.4029        | 0.55  | 5500  | 2.1265          |
| 2.3307        | 0.6   | 6000  | 2.1207          |
| 2.45          | 0.65  | 6500  | 2.0951          |
| 2.3575        | 0.7   | 7000  | 2.0987          |
| 2.3894        | 0.75  | 7500  | 2.0740          |
| 2.741         | 0.8   | 8000  | 2.0610          |
| 1.6001        | 0.85  | 8500  | 2.0542          |
| 2.5929        | 0.9   | 9000  | 2.0488          |
| 2.0965        | 0.95  | 9500  | 2.0473          |
| 2.6814        | 1.0   | 10000 | 2.0540          |


### Framework versions

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