---
license: other
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: sft
  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. -->

# sft

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 the duie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0501

## 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: 0.0001
- train_batch_size: 24
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.074         | 0.16  | 500  | 0.0621          |
| 0.0625        | 0.31  | 1000 | 0.0562          |
| 0.0581        | 0.47  | 1500 | 0.0543          |
| 0.0626        | 0.62  | 2000 | 0.0530          |
| 0.0597        | 0.78  | 2500 | 0.0524          |
| 0.0619        | 0.93  | 3000 | 0.0500          |
| 0.0445        | 1.09  | 3500 | 0.0499          |
| 0.0501        | 1.25  | 4000 | 0.0492          |
| 0.0487        | 1.4   | 4500 | 0.0490          |
| 0.0501        | 1.56  | 5000 | 0.0485          |
| 0.0516        | 1.71  | 5500 | 0.0472          |
| 0.0458        | 1.87  | 6000 | 0.0468          |
| 0.0381        | 2.03  | 6500 | 0.0482          |
| 0.037         | 2.18  | 7000 | 0.0506          |
| 0.0387        | 2.34  | 7500 | 0.0501          |
| 0.0363        | 2.49  | 8000 | 0.0498          |
| 0.0321        | 2.65  | 8500 | 0.0500          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2