---
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_4
  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_4

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: 0.1147

## 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.2444        | 0.2   | 10   | 7.8267          |
| 7.4754        | 0.4   | 20   | 6.3605          |
| 4.8314        | 0.6   | 30   | 3.1457          |
| 1.7327        | 0.8   | 40   | 0.6363          |
| 0.5438        | 1.0   | 50   | 0.5673          |
| 0.4569        | 1.2   | 60   | 0.4906          |
| 0.4491        | 1.39  | 70   | 0.4269          |
| 0.367         | 1.59  | 80   | 0.3729          |
| 0.2821        | 1.79  | 90   | 0.3323          |
| 0.2414        | 1.99  | 100  | 0.3013          |
| 0.2521        | 2.19  | 110  | 0.2772          |
| 0.2135        | 2.39  | 120  | 0.2603          |
| 0.1982        | 2.59  | 130  | 0.2446          |
| 0.2186        | 2.79  | 140  | 0.2278          |
| 0.1741        | 2.99  | 150  | 0.2144          |
| 0.1781        | 3.19  | 160  | 0.2062          |
| 0.1702        | 3.39  | 170  | 0.1928          |
| 0.157         | 3.59  | 180  | 0.1846          |
| 0.1469        | 3.78  | 190  | 0.1770          |
| 0.1644        | 3.98  | 200  | 0.1705          |
| 0.1458        | 4.18  | 210  | 0.1654          |
| 0.1282        | 4.38  | 220  | 0.1623          |
| 0.1537        | 4.58  | 230  | 0.1568          |
| 0.1197        | 4.78  | 240  | 0.1509          |
| 0.1327        | 4.98  | 250  | 0.1464          |
| 0.1349        | 5.18  | 260  | 0.1436          |
| 0.1052        | 5.38  | 270  | 0.1409          |
| 0.127         | 5.58  | 280  | 0.1381          |
| 0.1303        | 5.78  | 290  | 0.1365          |
| 0.1063        | 5.98  | 300  | 0.1338          |
| 0.1145        | 6.18  | 310  | 0.1300          |
| 0.1101        | 6.37  | 320  | 0.1287          |
| 0.1088        | 6.57  | 330  | 0.1280          |
| 0.1062        | 6.77  | 340  | 0.1254          |
| 0.1016        | 6.97  | 350  | 0.1238          |
| 0.1005        | 7.17  | 360  | 0.1232          |
| 0.1084        | 7.37  | 370  | 0.1220          |
| 0.101         | 7.57  | 380  | 0.1204          |
| 0.1065        | 7.77  | 390  | 0.1200          |
| 0.0943        | 7.97  | 400  | 0.1191          |
| 0.0848        | 8.17  | 410  | 0.1184          |
| 0.0913        | 8.37  | 420  | 0.1175          |
| 0.1115        | 8.57  | 430  | 0.1169          |
| 0.091         | 8.76  | 440  | 0.1161          |
| 0.1009        | 8.96  | 450  | 0.1154          |
| 0.0966        | 9.16  | 460  | 0.1150          |
| 0.0931        | 9.36  | 470  | 0.1147          |
| 0.0922        | 9.56  | 480  | 0.1150          |
| 0.0912        | 9.76  | 490  | 0.1148          |
| 0.0915        | 9.96  | 500  | 0.1147          |


### Framework versions

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