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---
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 |