---
library_name: peft
license: other
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: 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. -->

# 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 the flock_task4_tranning dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1499

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0681        | 0.0501 | 50   | 1.2795          |
| 1.0394        | 0.1002 | 100  | 1.2304          |
| 0.9251        | 0.1502 | 150  | 1.2384          |
| 1.0063        | 0.2003 | 200  | 1.2121          |
| 0.9905        | 0.2504 | 250  | 1.2024          |
| 0.9761        | 0.3005 | 300  | 1.1887          |
| 0.8606        | 0.3505 | 350  | 1.1863          |
| 0.9137        | 0.4006 | 400  | 1.1841          |
| 0.9647        | 0.4507 | 450  | 1.1794          |
| 0.9091        | 0.5008 | 500  | 1.1720          |
| 0.8968        | 0.5508 | 550  | 1.1639          |
| 0.9193        | 0.6009 | 600  | 1.1597          |
| 0.8827        | 0.6510 | 650  | 1.1622          |
| 0.895         | 0.7011 | 700  | 1.1525          |
| 0.9329        | 0.7511 | 750  | 1.1563          |
| 0.8991        | 0.8012 | 800  | 1.1525          |
| 0.8639        | 0.8513 | 850  | 1.1508          |
| 0.8723        | 0.9014 | 900  | 1.1498          |
| 0.9658        | 0.9514 | 950  | 1.1497          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0