---
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_task5_tranning dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0052

## 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: 0.05
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5231        | 2.5   | 10   | 1.6286          |
| 1.4069        | 5.0   | 20   | 1.4773          |
| 1.2518        | 7.5   | 30   | 1.3657          |
| 1.3069        | 10.0  | 40   | 1.2441          |
| 1.0816        | 12.5  | 50   | 1.0924          |
| 1.0063        | 15.0  | 60   | 0.9201          |
| 0.666         | 17.5  | 70   | 0.7236          |
| 0.5723        | 20.0  | 80   | 0.5105          |
| 0.3671        | 22.5  | 90   | 0.3136          |
| 0.2108        | 25.0  | 100  | 0.1737          |
| 0.1203        | 27.5  | 110  | 0.0830          |
| 0.069         | 30.0  | 120  | 0.0397          |
| 0.0233        | 32.5  | 130  | 0.0212          |
| 0.0158        | 35.0  | 140  | 0.0129          |
| 0.0104        | 37.5  | 150  | 0.0093          |
| 0.0081        | 40.0  | 160  | 0.0076          |
| 0.0073        | 42.5  | 170  | 0.0066          |
| 0.0072        | 45.0  | 180  | 0.0060          |
| 0.0062        | 47.5  | 190  | 0.0056          |
| 0.0063        | 50.0  | 200  | 0.0054          |
| 0.0068        | 52.5  | 210  | 0.0053          |
| 0.0064        | 55.0  | 220  | 0.0052          |
| 0.0061        | 57.5  | 230  | 0.0052          |
| 0.0056        | 60.0  | 240  | 0.0052          |


### Framework versions

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