---
base_model: meta-llama/Meta-Llama-3-8B-Instruct
library_name: peft
license: llama3
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama-qLoRA
  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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/dyr3k44h)
# llama-qLoRA

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9238

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2796        | 0.2022 | 100  | 1.2957          |
| 1.132         | 0.4044 | 200  | 1.1329          |
| 1.0712        | 0.6067 | 300  | 1.0974          |
| 1.0711        | 0.8089 | 400  | 1.0586          |
| 0.9632        | 1.0111 | 500  | 1.0059          |
| 0.9462        | 1.2133 | 600  | 0.9607          |
| 0.965         | 1.4156 | 700  | 0.9520          |
| 0.9302        | 1.6178 | 800  | 0.9470          |
| 0.9227        | 1.8200 | 900  | 0.9418          |
| 0.9023        | 2.0222 | 1000 | 0.9375          |
| 0.9093        | 2.2245 | 1100 | 0.9339          |
| 0.9202        | 2.4267 | 1200 | 0.9300          |
| 0.9061        | 2.6289 | 1300 | 0.9263          |
| 0.915         | 2.8311 | 1400 | 0.9238          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1