---
library_name: peft
base_model: NousResearch/CodeLlama-13b-hf
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 7cf17d3f-f651-4c8e-aa52-d0e2f77c0e72
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<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>

# 7cf17d3f-f651-4c8e-aa52-d0e2f77c0e72

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: 0.1060

## 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: 0.000211
- 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   | 0.1469          |
| 0.6418        | 0.0544 | 100  | 0.1823          |
| 0.2147        | 0.0816 | 150  | 0.1364          |
| 0.4591        | 0.1088 | 200  | 0.1453          |
| 0.1612        | 0.1360 | 250  | 0.1354          |
| 0.4845        | 0.1632 | 300  | 0.1224          |
| 0.1837        | 0.1904 | 350  | 0.1175          |
| 0.534         | 0.2176 | 400  | 0.1064          |
| 0.1899        | 0.2448 | 450  | 0.1069          |
| 0.4517        | 0.2720 | 500  | 0.1060          |


### Framework versions

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