---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-13b-hf
model-index:
- name: codellama13B-noautogen-StaproCoder
  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. -->

# codellama13B-noautogen-StaproCoder

This model is a fine-tuned version of [codellama/CodeLlama-13b-hf](https://huggingface.co/codellama/CodeLlama-13b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3758

## 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: 0.0005
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.417         | 0.05  | 100  | 0.5468          |
| 0.5187        | 0.1   | 200  | 0.4993          |
| 0.3279        | 0.15  | 300  | 0.4787          |
| 0.452         | 0.2   | 400  | 0.4551          |
| 0.4738        | 0.25  | 500  | 0.4402          |
| 0.4338        | 0.3   | 600  | 0.4263          |
| 0.4024        | 0.35  | 700  | 0.4183          |
| 0.4268        | 0.4   | 800  | 0.4082          |
| 0.3572        | 0.45  | 900  | 0.4014          |
| 0.3584        | 0.5   | 1000 | 0.3967          |
| 0.359         | 0.55  | 1100 | 0.3913          |
| 0.3023        | 0.6   | 1200 | 0.3865          |
| 0.2707        | 0.65  | 1300 | 0.3820          |
| 0.2918        | 0.7   | 1400 | 0.3790          |
| 0.3188        | 0.75  | 1500 | 0.3757          |
| 0.167         | 0.8   | 1600 | 0.3741          |
| 0.2962        | 0.85  | 1700 | 0.3742          |
| 0.2603        | 0.9   | 1800 | 0.3747          |
| 0.2544        | 0.95  | 1900 | 0.3755          |
| 0.254         | 1.0   | 2000 | 0.3758          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2