---
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: []
pipeline_tag: text-generation
---

<!-- 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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1546

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.2359        | 0.1416 | 50   | 1.9291          |
| 1.5215        | 0.2833 | 100  | 1.2761          |
| 1.287         | 0.4249 | 150  | 1.2268          |
| 1.2613        | 0.5666 | 200  | 1.2073          |
| 1.2341        | 0.7082 | 250  | 1.1996          |
| 1.2037        | 0.8499 | 300  | 1.1953          |
| 1.2117        | 0.9915 | 350  | 1.1871          |
| 1.2023        | 1.1331 | 400  | 1.1813          |
| 1.1635        | 1.2748 | 450  | 1.1770          |
| 1.1689        | 1.4164 | 500  | 1.1732          |
| 1.2013        | 1.5581 | 550  | 1.1720          |
| 1.1853        | 1.6997 | 600  | 1.1675          |
| 1.1933        | 1.8414 | 650  | 1.1648          |
| 1.1774        | 1.9830 | 700  | 1.1619          |
| 1.1633        | 2.1246 | 750  | 1.1626          |
| 1.1756        | 2.2663 | 800  | 1.1593          |
| 1.1597        | 2.4079 | 850  | 1.1587          |
| 1.1599        | 2.5496 | 900  | 1.1562          |
| 1.1145        | 2.6912 | 950  | 1.1567          |
| 1.162         | 2.8329 | 1000 | 1.1553          |
| 1.1507        | 2.9745 | 1050 | 1.1546          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1