---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: hf_llama3_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. -->

[<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/hmosousa/huggingface/runs/d375v2e7)
# hf_llama3_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: 1.2972

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 5
- gradient_accumulation_steps: 32
- total_train_batch_size: 640
- total_eval_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4042        | 0.1862 | 500  | 1.3990          |
| 1.3445        | 0.3723 | 1000 | 1.3608          |
| 1.291         | 0.5585 | 1500 | 1.3493          |
| 1.264         | 0.7446 | 2000 | 1.3381          |
| 1.2438        | 0.9308 | 2500 | 1.3257          |
| 1.2333        | 1.1169 | 3000 | 1.3242          |
| 1.2084        | 1.3031 | 3500 | 1.3167          |
| 1.2227        | 1.4892 | 4000 | 1.3178          |
| 1.2151        | 1.6754 | 4500 | 1.3092          |
| 1.2114        | 1.8615 | 5000 | 1.3060          |
| 1.1645        | 2.0477 | 5500 | 1.3068          |
| 1.1793        | 2.2338 | 6000 | 1.3026          |
| 1.1809        | 2.4200 | 6500 | 1.3014          |
| 1.1934        | 2.6061 | 7000 | 1.2935          |
| 1.175         | 2.7923 | 7500 | 1.2953          |
| 1.1629        | 2.9784 | 8000 | 1.2954          |
| 1.1559        | 3.1646 | 8500 | 1.2972          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1