---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: fine-tuning-Phi2-with-webglm-qa-with-lora_7
  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. -->

# fine-tuning-Phi2-with-webglm-qa-with-lora_7

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0950

## 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: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.3505        | 0.31  | 20   | 6.2863          |
| 4.0914        | 0.63  | 40   | 0.9255          |
| 0.6517        | 0.94  | 60   | 0.5762          |
| 0.4621        | 1.26  | 80   | 0.4062          |
| 0.3128        | 1.57  | 100  | 0.3056          |
| 0.2536        | 1.89  | 120  | 0.2604          |
| 0.2227        | 2.2   | 140  | 0.2247          |
| 0.1901        | 2.52  | 160  | 0.2041          |
| 0.176         | 2.83  | 180  | 0.1812          |
| 0.1453        | 3.14  | 200  | 0.1683          |
| 0.1557        | 3.46  | 220  | 0.1592          |
| 0.1441        | 3.77  | 240  | 0.1488          |
| 0.1282        | 4.09  | 260  | 0.1430          |
| 0.1215        | 4.4   | 280  | 0.1348          |
| 0.1217        | 4.72  | 300  | 0.1323          |
| 0.117         | 5.03  | 320  | 0.1271          |
| 0.109         | 5.35  | 340  | 0.1255          |
| 0.1094        | 5.66  | 360  | 0.1210          |
| 0.1057        | 5.97  | 380  | 0.1175          |
| 0.0937        | 6.29  | 400  | 0.1158          |
| 0.0942        | 6.6   | 420  | 0.1159          |
| 0.1007        | 6.92  | 440  | 0.1125          |
| 0.0876        | 7.23  | 460  | 0.1119          |
| 0.0894        | 7.55  | 480  | 0.1099          |
| 0.0827        | 7.86  | 500  | 0.1072          |
| 0.0894        | 8.18  | 520  | 0.1069          |
| 0.0805        | 8.49  | 540  | 0.1075          |
| 0.0782        | 8.81  | 560  | 0.1043          |
| 0.0881        | 9.12  | 580  | 0.1034          |
| 0.0839        | 9.43  | 600  | 0.1015          |
| 0.0694        | 9.75  | 620  | 0.1000          |
| 0.068         | 10.06 | 640  | 0.1007          |
| 0.072         | 10.38 | 660  | 0.0994          |
| 0.0709        | 10.69 | 680  | 0.0985          |
| 0.0712        | 11.01 | 700  | 0.0986          |
| 0.0673        | 11.32 | 720  | 0.0999          |
| 0.0669        | 11.64 | 740  | 0.0974          |
| 0.0706        | 11.95 | 760  | 0.0981          |
| 0.0641        | 12.26 | 780  | 0.0969          |
| 0.0652        | 12.58 | 800  | 0.0964          |
| 0.0668        | 12.89 | 820  | 0.0962          |
| 0.0617        | 13.21 | 840  | 0.0972          |
| 0.0628        | 13.52 | 860  | 0.0960          |
| 0.0637        | 13.84 | 880  | 0.0949          |
| 0.0633        | 14.15 | 900  | 0.0951          |
| 0.0577        | 14.47 | 920  | 0.0953          |
| 0.0646        | 14.78 | 940  | 0.0947          |
| 0.06          | 15.09 | 960  | 0.0946          |
| 0.0584        | 15.41 | 980  | 0.0949          |
| 0.0638        | 15.72 | 1000 | 0.0950          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0