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---
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
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: 0.4198
## 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
|