---
base_model: meta-llama/Meta-Llama-3-8B-Instruct
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama-LoRA
  results: []
---

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should probably proofread and complete it, then remove this comment. -->

[<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/okaj5ajj)
# llama-LoRA

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: 0.9302

## 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: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4647        | 0.2022 | 100  | 1.4659          |
| 1.1287        | 0.4044 | 200  | 1.1280          |
| 1.0504        | 0.6067 | 300  | 1.0737          |
| 1.0202        | 0.8089 | 400  | 1.0079          |
| 0.9151        | 1.0111 | 500  | 0.9598          |
| 0.9341        | 1.2133 | 600  | 0.9523          |
| 0.9559        | 1.4156 | 700  | 0.9460          |
| 0.9236        | 1.6178 | 800  | 0.9425          |
| 0.9179        | 1.8200 | 900  | 0.9388          |
| 0.901         | 2.0222 | 1000 | 0.9361          |
| 0.9085        | 2.2245 | 1100 | 0.9335          |
| 0.9222        | 2.4267 | 1200 | 0.9322          |
| 0.9105        | 2.6289 | 1300 | 0.9308          |
| 0.92          | 2.8311 | 1400 | 0.9302          |


### Framework versions

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