---
base_model: meta-llama/Llama-2-7b-hf
library_name: peft
license: llama2
tags:
- generated_from_trainer
model-index:
- name: llama-2-qlora-finetuned
  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. -->

# llama-2-qlora-finetuned

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8009

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 1    | 2.9311          |
| No log        | 2.0   | 2    | 2.8476          |
| No log        | 3.0   | 3    | 2.8009          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 2.19.1
- Tokenizers 0.20.1