---
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-LoRA
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/hmehdi-endosoft/Phi3-mini-ft-python-code/runs/x5jzugdy)
# 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: 0.6516

## 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: 16
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.6795        | 0.3578 | 500  | 0.6740          |
| 0.6663        | 0.7156 | 1000 | 0.6629          |
| 0.6509        | 1.0733 | 1500 | 0.6576          |
| 0.6374        | 1.4311 | 2000 | 0.6553          |
| 0.6364        | 1.7889 | 2500 | 0.6528          |
| 0.6228        | 2.1467 | 3000 | 0.6526          |
| 0.6197        | 2.5045 | 3500 | 0.6519          |
| 0.6194        | 2.8623 | 4000 | 0.6516          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1