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