peft pytorch tensorboard llama generated_from_trainer base_model:codellama/CodeLlama-13b-Instruct-hf license:llama2 region:us
---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-13b-Instruct-hf
model-index:
- name: lora-out
  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/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: 0.4198

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6555        | 0.01  | 1    | 0.6550          |
| 0.6532        | 0.05  | 7    | 0.6035          |
| 0.5278        | 0.1   | 14   | 0.4977          |
| 0.5466        | 0.15  | 21   | 0.4736          |
| 0.4832        | 0.2   | 28   | 0.4637          |
| 0.5069        | 0.25  | 35   | 0.4492          |
| 0.4864        | 0.3   | 42   | 0.4436          |
| 0.4625        | 0.35  | 49   | 0.4379          |
| 0.4792        | 0.4   | 56   | 0.4336          |
| 0.4608        | 0.45  | 63   | 0.4302          |
| 0.4738        | 0.5   | 70   | 0.4266          |
| 0.4839        | 0.55  | 77   | 0.4245          |
| 0.4791        | 0.6   | 84   | 0.4227          |
| 0.4701        | 0.65  | 91   | 0.4233          |
| 0.4612        | 0.7   | 98   | 0.4225          |
| 0.4419        | 0.75  | 105  | 0.4212          |
| 0.4705        | 0.8   | 112  | 0.4199          |
| 0.4422        | 0.85  | 119  | 0.4198          |
| 0.4889        | 0.9   | 126  | 0.4198          |
| 0.4914        | 0.95  | 133  | 0.4195          |
| 0.4799        | 1.0   | 140  | 0.4198          |


### 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
