---
base_model: huggyllama/llama-7b
library_name: transformers
license: mit
tags:
- peft
- lora
- dora
model-index:
- name: llama-3-8-fine-tuned-dora
  results: []
datasets:
- timdettmers/openassistant-guanaco
pipeline_tag: text-generation
---

<!-- 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. -->

# llama-3-8-fine-tuned-dora

![huggyllama](https://miro.medium.com/v2/resize:fit:1358/0*UBaord-00Sm4asfW.png)

This model is a fine-tuned version of [huggyllama/llama-7b](https://huggingface.co/huggyllama/llama-7b) on on [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset.
For LoraConfig we set the `use_dora=True` for the Dora decomposition and comparison with Lora. 

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1