---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-13b-hf
model-index:
- name: codeLlama13B-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-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: 0.1794

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2404        | 0.05  | 100  | 0.2456          |
| 0.289         | 0.1   | 200  | 0.2349          |
| 0.236         | 0.15  | 300  | 0.2281          |
| 0.1928        | 0.2   | 400  | 0.2200          |
| 0.1999        | 0.25  | 500  | 0.2217          |
| 0.1697        | 0.3   | 600  | 0.2134          |
| 0.1825        | 0.35  | 700  | 0.2129          |
| 0.1904        | 0.4   | 800  | 0.2093          |
| 0.159         | 0.45  | 900  | 0.2054          |
| 0.1448        | 0.5   | 1000 | 0.1994          |
| 0.1993        | 0.55  | 1100 | 0.1954          |
| 0.2424        | 0.6   | 1200 | 0.1896          |
| 0.1385        | 0.65  | 1300 | 0.1891          |
| 0.1427        | 0.7   | 1400 | 0.1860          |
| 0.2021        | 0.75  | 1500 | 0.1836          |
| 0.1884        | 0.8   | 1600 | 0.1824          |
| 0.26          | 0.85  | 1700 | 0.1809          |
| 0.1641        | 0.9   | 1800 | 0.1799          |
| 0.1503        | 0.95  | 1900 | 0.1794          |
| 0.1613        | 1.0   | 2000 | 0.1794          |


### Framework versions

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