---
library_name: peft
base_model: NousResearch/CodeLlama-13b-hf
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 204a0a10-1884-474f-b6e0-2d2b14b6a600
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# 204a0a10-1884-474f-b6e0-2d2b14b6a600

This model is a fine-tuned version of [NousResearch/CodeLlama-13b-hf](https://huggingface.co./NousResearch/CodeLlama-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1061

## 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: 0.00021
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0005 | 1    | 0.3389          |
| 0.1967        | 0.0272 | 50   | 0.1475          |
| 0.6546        | 0.0544 | 100  | 0.1661          |
| 0.2137        | 0.0816 | 150  | 0.1331          |
| 0.4927        | 0.1088 | 200  | 0.1521          |
| 0.161         | 0.1360 | 250  | 0.1386          |
| 0.4765        | 0.1632 | 300  | 0.1222          |
| 0.1847        | 0.1904 | 350  | 0.1186          |
| 0.5652        | 0.2176 | 400  | 0.1065          |
| 0.1893        | 0.2448 | 450  | 0.1067          |
| 0.4581        | 0.2720 | 500  | 0.1061          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1