---
library_name: peft
license: mit
base_model: microsoft/phi-2
tags:
- base_model:adapter:microsoft/phi-2
- transformers
pipeline_tag: text-generation
model-index:
- name: phi-2-IA3_1-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-IA3_1-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: 4.4994

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 6.003         | 0.1333 | 100  | 6.1547          |
| 5.798         | 0.2667 | 200  | 5.8543          |
| 5.4963        | 0.4    | 300  | 5.5766          |
| 5.4936        | 0.5333 | 400  | 5.3316          |
| 5.2081        | 0.6667 | 500  | 5.1551          |
| 4.8002        | 0.8    | 600  | 5.0209          |
| 4.7734        | 0.9333 | 700  | 4.9287          |
| 4.9121        | 1.0667 | 800  | 4.8604          |
| 4.8736        | 1.2    | 900  | 4.8028          |
| 4.4034        | 1.3333 | 1000 | 4.7485          |
| 4.7587        | 1.4667 | 1100 | 4.6937          |
| 4.3786        | 1.6    | 1200 | 4.6457          |
| 4.3765        | 1.7333 | 1300 | 4.6145          |
| 4.6507        | 1.8667 | 1400 | 4.5827          |
| 4.8214        | 2.0    | 1500 | 4.5567          |
| 4.1151        | 2.1333 | 1600 | 4.5434          |
| 4.6073        | 2.2667 | 1700 | 4.5267          |
| 3.9566        | 2.4    | 1800 | 4.5202          |
| 4.7471        | 2.5333 | 1900 | 4.5094          |
| 4.5244        | 2.6667 | 2000 | 4.5046          |
| 4.3776        | 2.8    | 2100 | 4.5010          |
| 4.3815        | 2.9333 | 2200 | 4.4994          |


### Framework versions

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