---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- scitldr
model-index:
- name: Llama-3-8B-Summarization-QLoRa
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3-8B-Summarization-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 scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4051

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.226         | 0.5020 | 500  | 2.3232          |
| 2.2207        | 1.0040 | 1000 | 2.3130          |
| 1.6901        | 1.5060 | 1500 | 2.4051          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1