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

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: 0.5601

## 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1716        | 0.1809 | 100  | 0.6639          |
| 0.6253        | 0.3618 | 200  | 0.5865          |
| 0.5772        | 0.5427 | 300  | 0.5753          |
| 0.5823        | 0.7237 | 400  | 0.5703          |
| 0.5862        | 0.9046 | 500  | 0.5673          |
| 0.5804        | 1.0855 | 600  | 0.5652          |
| 0.5776        | 1.2664 | 700  | 0.5641          |
| 0.5721        | 1.4473 | 800  | 0.5630          |
| 0.5725        | 1.6282 | 900  | 0.5623          |
| 0.5708        | 1.8091 | 1000 | 0.5615          |
| 0.5714        | 1.9900 | 1100 | 0.5611          |
| 0.5685        | 2.1710 | 1200 | 0.5607          |
| 0.5618        | 2.3519 | 1300 | 0.5605          |
| 0.5789        | 2.5328 | 1400 | 0.5605          |
| 0.5716        | 2.7137 | 1500 | 0.5600          |
| 0.5626        | 2.8946 | 1600 | 0.5601          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1