---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: LoftQ/Meta-Llama-3-8B-Instruct-4bit-64rank
model-index:
- name: llama3-8b-instruct-qlora-large
  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. -->

# llama3-8b-instruct-qlora-large

This model is a fine-tuned version of [LoftQ/Meta-Llama-3-8B-Instruct-4bit-64rank](https://huggingface.co/LoftQ/Meta-Llama-3-8B-Instruct-4bit-64rank) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8530

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3454        | 1.0   | 158  | 1.2439          |
| 2.1288        | 2.0   | 316  | 1.0900          |
| 2.0335        | 3.0   | 474  | 1.0394          |
| 1.9315        | 4.0   | 632  | 0.9995          |
| 1.804         | 5.0   | 790  | 0.9605          |
| 1.6583        | 6.0   | 948  | 0.9411          |
| 1.4994        | 7.0   | 1106 | 0.9283          |
| 1.3388        | 8.0   | 1264 | 0.9158          |
| 1.1894        | 9.0   | 1422 | 0.9103          |
| 1.0616        | 10.0  | 1580 | 0.9027          |
| 0.9461        | 11.0  | 1738 | 0.8963          |
| 0.8447        | 12.0  | 1896 | 0.8922          |
| 0.7575        | 13.0  | 2054 | 0.8887          |
| 0.6817        | 14.0  | 2212 | 0.8803          |
| 0.6192        | 15.0  | 2370 | 0.8761          |
| 0.5669        | 16.0  | 2528 | 0.8715          |
| 0.5196        | 17.0  | 2686 | 0.8719          |
| 0.479         | 18.0  | 2844 | 0.8683          |
| 0.4473        | 19.0  | 3002 | 0.8662          |
| 0.4202        | 20.0  | 3160 | 0.8624          |
| 0.397         | 21.0  | 3318 | 0.8590          |
| 0.377         | 22.0  | 3476 | 0.8573          |
| 0.3622        | 23.0  | 3634 | 0.8558          |
| 0.3514        | 24.0  | 3792 | 0.8548          |
| 0.3434        | 25.0  | 3950 | 0.8543          |
| 0.3349        | 26.0  | 4108 | 0.8541          |
| 0.332         | 27.0  | 4266 | 0.8538          |
| 0.328         | 28.0  | 4424 | 0.8541          |
| 0.3286        | 29.0  | 4582 | 0.8532          |
| 0.3279        | 30.0  | 4740 | 0.8530          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1