---
library_name: peft
license: mit
base_model: microsoft/phi-2
tags:
- base_model:adapter:microsoft/phi-2
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: phi-2-LoRa-Python
  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. -->

# phi-2-LoRa-Python

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4864

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.5433        | 0.1333 | 100  | 4.4747          |
| 4.4162        | 0.2667 | 200  | 4.4774          |
| 4.2759        | 0.4    | 300  | 4.4755          |
| 4.4021        | 0.5333 | 400  | 4.4764          |
| 4.3925        | 0.6667 | 500  | 4.4775          |
| 4.6016        | 0.8    | 600  | 4.5976          |
| 4.2527        | 0.9333 | 700  | 4.5484          |
| 4.5823        | 1.0667 | 800  | 4.5037          |
| 4.5826        | 1.2    | 900  | 4.5032          |
| 4.0654        | 1.3333 | 1000 | 4.5073          |
| 4.5386        | 1.4667 | 1100 | 4.4961          |
| 4.1046        | 1.6    | 1200 | 4.4957          |
| 4.1705        | 1.7333 | 1300 | 4.4943          |
| 4.4922        | 1.8667 | 1400 | 4.4918          |
| 4.7333        | 2.0    | 1500 | 4.4901          |
| 3.997         | 2.1333 | 1600 | 4.4889          |
| 4.5407        | 2.2667 | 1700 | 4.4880          |
| 3.8457        | 2.4    | 1800 | 4.4877          |
| 4.6653        | 2.5333 | 1900 | 4.4873          |
| 4.4524        | 2.6667 | 2000 | 4.4865          |
| 4.3138        | 2.8    | 2100 | 4.4870          |
| 4.3203        | 2.9333 | 2200 | 4.4865          |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0