---
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-medium
  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-medium

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: 0.7329

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2884        | 1.0   | 105  | 1.2658          |
| 2.0727        | 2.0   | 210  | 1.0205          |
| 1.9709        | 3.0   | 315  | 0.9518          |
| 1.8768        | 4.0   | 420  | 0.9206          |
| 1.7711        | 5.0   | 525  | 0.8761          |
| 1.6379        | 6.0   | 630  | 0.8487          |
| 1.4834        | 7.0   | 735  | 0.8200          |
| 1.3144        | 8.0   | 840  | 0.8076          |
| 1.1514        | 9.0   | 945  | 0.7972          |
| 1.0148        | 10.0  | 1050 | 0.7865          |
| 0.8944        | 11.0  | 1155 | 0.7846          |
| 0.7844        | 12.0  | 1260 | 0.7767          |
| 0.699         | 13.0  | 1365 | 0.7688          |
| 0.6215        | 14.0  | 1470 | 0.7631          |
| 0.5602        | 15.0  | 1575 | 0.7584          |
| 0.503         | 16.0  | 1680 | 0.7548          |
| 0.4597        | 17.0  | 1785 | 0.7514          |
| 0.4226        | 18.0  | 1890 | 0.7484          |
| 0.3903        | 19.0  | 1995 | 0.7441          |
| 0.3646        | 20.0  | 2100 | 0.7390          |
| 0.3407        | 21.0  | 2205 | 0.7385          |
| 0.3237        | 22.0  | 2310 | 0.7357          |
| 0.3108        | 23.0  | 2415 | 0.7343          |
| 0.2999        | 24.0  | 2520 | 0.7337          |
| 0.2917        | 25.0  | 2625 | 0.7333          |
| 0.2868        | 26.0  | 2730 | 0.7324          |
| 0.2815        | 27.0  | 2835 | 0.7327          |
| 0.28          | 28.0  | 2940 | 0.7315          |
| 0.2785        | 29.0  | 3045 | 0.7322          |
| 0.2791        | 30.0  | 3150 | 0.7329          |


### Framework versions

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