---
license: other
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- generator
model-index:
- name: Meta-Llama-3-8B-VIGGO-qlora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Meta-Llama-3-8B-VIGGO-qlora

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6168

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.03
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5174        | 0.99  | 25   | 0.5002          |
| 0.4168        | 1.98  | 50   | 0.4846          |
| 0.3898        | 2.97  | 75   | 0.4930          |
| 0.3179        | 4.0   | 101  | 0.5523          |
| 0.2378        | 4.95  | 125  | 0.6168          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2