---
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: hf_phi3_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/jy8rtirf)
# hf_phi3_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: 1.3171

## 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: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 16
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 1.4828        | 0.1489 | 500   | 1.4306          |
| 1.4047        | 0.2978 | 1000  | 1.3980          |
| 1.3611        | 0.4468 | 1500  | 1.3835          |
| 1.3653        | 0.5957 | 2000  | 1.3709          |
| 1.3171        | 0.7446 | 2500  | 1.3665          |
| 1.3089        | 0.8935 | 3000  | 1.3626          |
| 1.312         | 1.0425 | 3500  | 1.3608          |
| 1.2771        | 1.1914 | 4000  | 1.3556          |
| 1.3031        | 1.3403 | 4500  | 1.3570          |
| 1.284         | 1.4892 | 5000  | 1.3508          |
| 1.2697        | 1.6382 | 5500  | 1.3477          |
| 1.2594        | 1.7871 | 6000  | 1.3453          |
| 1.254         | 1.9360 | 6500  | 1.3413          |
| 1.2652        | 2.0849 | 7000  | 1.3426          |
| 1.2529        | 2.2338 | 7500  | 1.3435          |
| 1.2544        | 2.3828 | 8000  | 1.3382          |
| 1.2511        | 2.5317 | 8500  | 1.3396          |
| 1.2548        | 2.6806 | 9000  | 1.3361          |
| 1.2483        | 2.8295 | 9500  | 1.3351          |
| 1.2442        | 2.9785 | 10000 | 1.3382          |
| 1.2426        | 3.1274 | 10500 | 1.3344          |
| 1.2265        | 3.2763 | 11000 | 1.3361          |
| 1.2255        | 3.4252 | 11500 | 1.3356          |
| 1.2269        | 3.5742 | 12000 | 1.3314          |
| 1.2396        | 3.7231 | 12500 | 1.3298          |
| 1.2303        | 3.8720 | 13000 | 1.3260          |
| 1.2254        | 4.0209 | 13500 | 1.3277          |
| 1.2277        | 4.1698 | 14000 | 1.3272          |
| 1.2295        | 4.3188 | 14500 | 1.3240          |
| 1.2375        | 4.4677 | 15000 | 1.3288          |
| 1.2038        | 4.6166 | 15500 | 1.3224          |
| 1.2322        | 4.7655 | 16000 | 1.3214          |
| 1.2015        | 4.9145 | 16500 | 1.3246          |
| 1.208         | 5.0634 | 17000 | 1.3216          |
| 1.2248        | 5.2123 | 17500 | 1.3193          |
| 1.2155        | 5.3612 | 18000 | 1.3249          |
| 1.2194        | 5.5102 | 18500 | 1.3183          |
| 1.2185        | 5.6591 | 19000 | 1.3196          |
| 1.2119        | 5.8080 | 19500 | 1.3142          |
| 1.2171        | 5.9569 | 20000 | 1.3240          |
| 1.21          | 6.1058 | 20500 | 1.3235          |
| 1.19          | 6.2548 | 21000 | 1.3171          |


### Framework versions

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