---
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-QLoRa1-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-QLoRa1-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: 4.3315

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 4.3884        | 0.1333 | 100  | 4.3373          |
| 4.2606        | 0.2667 | 200  | 4.3355          |
| 4.1367        | 0.4    | 300  | 4.3477          |
| 4.2479        | 0.5333 | 400  | 4.3369          |
| 4.2398        | 0.6667 | 500  | 4.3360          |
| 3.9217        | 0.8    | 600  | 4.3400          |
| 4.0251        | 0.9333 | 700  | 4.3373          |
| 4.3893        | 1.0667 | 800  | 4.3477          |
| 4.4014        | 1.2    | 900  | 4.3426          |
| 3.8868        | 1.3333 | 1000 | 4.3346          |
| 4.3634        | 1.4667 | 1100 | 4.3389          |
| 3.9379        | 1.6    | 1200 | 4.3337          |
| 4.0013        | 1.7333 | 1300 | 4.3340          |
| 4.3155        | 1.8667 | 1400 | 4.3331          |
| 4.5401        | 2.0    | 1500 | 4.3330          |
| 3.8402        | 2.1333 | 1600 | 4.3335          |
| 4.3658        | 2.2667 | 1700 | 4.3336          |
| 3.6929        | 2.4    | 1800 | 4.3326          |
| 4.482         | 2.5333 | 1900 | 4.3321          |
| 4.2755        | 2.6667 | 2000 | 4.3317          |
| 4.1472        | 2.8    | 2100 | 4.3315          |
| 4.1581        | 2.9333 | 2200 | 4.3315          |


### Framework versions

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