
<!-- 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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# lora-out

This model is a fine-tuned version of [codellama/CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4172

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7046        | 0.01  | 1    | 0.6695          |
| 0.6348        | 0.05  | 7    | 0.6183          |
| 0.5056        | 0.1   | 14   | 0.4993          |
| 0.5127        | 0.15  | 21   | 0.4682          |
| 0.4663        | 0.2   | 28   | 0.4552          |
| 0.5534        | 0.25  | 35   | 0.4419          |
| 0.5231        | 0.3   | 42   | 0.4369          |
| 0.5045        | 0.35  | 49   | 0.4338          |
| 0.5444        | 0.4   | 56   | 0.4314          |
| 0.4922        | 0.45  | 63   | 0.4296          |
| 0.487         | 0.5   | 70   | 0.4261          |
| 0.4627        | 0.55  | 77   | 0.4230          |
| 0.5143        | 0.6   | 84   | 0.4210          |
| 0.4429        | 0.65  | 91   | 0.4199          |
| 0.4491        | 0.71  | 98   | 0.4193          |
| 0.4808        | 0.76  | 105  | 0.4188          |
| 0.483         | 0.81  | 112  | 0.4176          |
| 0.5513        | 0.86  | 119  | 0.4177          |
| 0.4574        | 0.91  | 126  | 0.4170          |
| 0.4723        | 0.96  | 133  | 0.4172          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
## Training procedure


### Framework versions


- PEFT 0.6.0

{"license": "llama2", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "codellama/CodeLlama-13b-Instruct-hf", "model-index": [{"name": "lora-out", "results": []}]}
peft pytorch tensorboard llama generated_from_trainer base_model:codellama/CodeLlama-13b-Instruct-hf license:llama2 region:us