---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-mini-QLoRA
  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. -->

# phi-3-mini-QLoRA

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5739

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0193        | 0.0181 | 10   | 1.0582          |
| 1.0408        | 0.0362 | 20   | 1.0129          |
| 0.9957        | 0.0543 | 30   | 0.9095          |
| 0.8047        | 0.0724 | 40   | 0.7711          |
| 0.699         | 0.0905 | 50   | 0.6689          |
| 0.6143        | 0.1085 | 60   | 0.6385          |
| 0.6472        | 0.1266 | 70   | 0.6175          |
| 0.6077        | 0.1447 | 80   | 0.6073          |
| 0.6028        | 0.1628 | 90   | 0.6012          |
| 0.5929        | 0.1809 | 100  | 0.5978          |
| 0.6117        | 0.1990 | 110  | 0.5948          |
| 0.5904        | 0.2171 | 120  | 0.5925          |
| 0.5852        | 0.2352 | 130  | 0.5909          |
| 0.5662        | 0.2533 | 140  | 0.5895          |
| 0.6183        | 0.2714 | 150  | 0.5880          |
| 0.5872        | 0.2895 | 160  | 0.5873          |
| 0.5807        | 0.3076 | 170  | 0.5863          |
| 0.6169        | 0.3256 | 180  | 0.5853          |
| 0.5705        | 0.3437 | 190  | 0.5841          |
| 0.6143        | 0.3618 | 200  | 0.5835          |
| 0.5705        | 0.3799 | 210  | 0.5828          |
| 0.5683        | 0.3980 | 220  | 0.5821          |
| 0.6077        | 0.4161 | 230  | 0.5818          |
| 0.586         | 0.4342 | 240  | 0.5811          |
| 0.5724        | 0.4523 | 250  | 0.5804          |
| 0.5941        | 0.4704 | 260  | 0.5799          |
| 0.5989        | 0.4885 | 270  | 0.5798          |
| 0.5582        | 0.5066 | 280  | 0.5793          |
| 0.5798        | 0.5246 | 290  | 0.5792          |
| 0.5545        | 0.5427 | 300  | 0.5785          |
| 0.597         | 0.5608 | 310  | 0.5783          |
| 0.6093        | 0.5789 | 320  | 0.5779          |
| 0.5736        | 0.5970 | 330  | 0.5778          |
| 0.5698        | 0.6151 | 340  | 0.5772          |
| 0.5659        | 0.6332 | 350  | 0.5769          |
| 0.5877        | 0.6513 | 360  | 0.5764          |
| 0.5837        | 0.6694 | 370  | 0.5763          |
| 0.5858        | 0.6875 | 380  | 0.5761          |
| 0.5877        | 0.7056 | 390  | 0.5760          |
| 0.5802        | 0.7237 | 400  | 0.5756          |
| 0.6009        | 0.7417 | 410  | 0.5754          |
| 0.5713        | 0.7598 | 420  | 0.5751          |
| 0.5509        | 0.7779 | 430  | 0.5751          |
| 0.5646        | 0.7960 | 440  | 0.5750          |
| 0.5458        | 0.8141 | 450  | 0.5748          |
| 0.5694        | 0.8322 | 460  | 0.5746          |
| 0.576         | 0.8503 | 470  | 0.5744          |
| 0.5864        | 0.8684 | 480  | 0.5742          |
| 0.5645        | 0.8865 | 490  | 0.5741          |
| 0.5531        | 0.9046 | 500  | 0.5742          |
| 0.6176        | 0.9227 | 510  | 0.5742          |
| 0.5987        | 0.9408 | 520  | 0.5742          |
| 0.5703        | 0.9588 | 530  | 0.5740          |
| 0.6023        | 0.9769 | 540  | 0.5740          |
| 0.5637        | 0.9950 | 550  | 0.5739          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0