peft safetensors generated_from_trainer base_model:microsoft/phi-2 license:mit region:us
---
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_2
  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_2

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: 0.0749

## 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.2   | 10   | 8.2244          |
| No log        | 0.4   | 20   | 7.4785          |
| No log        | 0.6   | 30   | 5.5477          |
| No log        | 0.8   | 40   | 2.9270          |
| 5.8579        | 1.0   | 50   | 0.6602          |
| 5.8579        | 1.2   | 60   | 0.5707          |
| 5.8579        | 1.39  | 70   | 0.5056          |
| 5.8579        | 1.59  | 80   | 0.4537          |
| 5.8579        | 1.79  | 90   | 0.4048          |
| 0.4258        | 1.99  | 100  | 0.3539          |
| 0.4258        | 2.19  | 110  | 0.3117          |
| 0.4258        | 2.39  | 120  | 0.2848          |
| 0.4258        | 2.59  | 130  | 0.2589          |
| 0.4258        | 2.79  | 140  | 0.2344          |
| 0.2253        | 2.99  | 150  | 0.2160          |
| 0.2253        | 3.19  | 160  | 0.2037          |
| 0.2253        | 3.39  | 170  | 0.1890          |
| 0.2253        | 3.59  | 180  | 0.1794          |
| 0.2253        | 3.78  | 190  | 0.1695          |
| 0.1573        | 3.98  | 200  | 0.1607          |
| 0.1573        | 4.18  | 210  | 0.1544          |
| 0.1573        | 4.38  | 220  | 0.1518          |
| 0.1573        | 4.58  | 230  | 0.1441          |
| 0.1573        | 4.78  | 240  | 0.1365          |
| 0.1251        | 4.98  | 250  | 0.1302          |
| 0.1251        | 5.18  | 260  | 0.1286          |
| 0.1251        | 5.38  | 270  | 0.1258          |
| 0.1251        | 5.58  | 280  | 0.1228          |
| 0.1251        | 5.78  | 290  | 0.1203          |
| 0.1059        | 5.98  | 300  | 0.1159          |
| 0.1059        | 6.18  | 310  | 0.1116          |
| 0.1059        | 6.37  | 320  | 0.1112          |
| 0.1059        | 6.57  | 330  | 0.1092          |
| 0.1059        | 6.77  | 340  | 0.1046          |
| 0.0905        | 6.97  | 350  | 0.1032          |
| 0.0905        | 7.17  | 360  | 0.1028          |
| 0.0905        | 7.37  | 370  | 0.1005          |
| 0.0905        | 7.57  | 380  | 0.1011          |
| 0.0905        | 7.77  | 390  | 0.0991          |
| 0.0816        | 7.97  | 400  | 0.0973          |
| 0.0816        | 8.17  | 410  | 0.0965          |
| 0.0816        | 8.37  | 420  | 0.0954          |
| 0.0816        | 8.57  | 430  | 0.0949          |
| 0.0816        | 8.76  | 440  | 0.0938          |
| 0.0722        | 8.96  | 450  | 0.0915          |
| 0.0722        | 9.16  | 460  | 0.0907          |
| 0.0722        | 9.36  | 470  | 0.0900          |
| 0.0722        | 9.56  | 480  | 0.0893          |
| 0.0722        | 9.76  | 490  | 0.0877          |
| 0.0656        | 9.96  | 500  | 0.0872          |
| 0.0656        | 10.16 | 510  | 0.0868          |
| 0.0656        | 10.36 | 520  | 0.0867          |
| 0.0656        | 10.56 | 530  | 0.0874          |
| 0.0656        | 10.76 | 540  | 0.0863          |
| 0.0614        | 10.96 | 550  | 0.0849          |
| 0.0614        | 11.16 | 560  | 0.0834          |
| 0.0614        | 11.35 | 570  | 0.0829          |
| 0.0614        | 11.55 | 580  | 0.0827          |
| 0.0614        | 11.75 | 590  | 0.0817          |
| 0.0553        | 11.95 | 600  | 0.0817          |
| 0.0553        | 12.15 | 610  | 0.0824          |
| 0.0553        | 12.35 | 620  | 0.0826          |
| 0.0553        | 12.55 | 630  | 0.0810          |
| 0.0553        | 12.75 | 640  | 0.0814          |
| 0.053         | 12.95 | 650  | 0.0804          |
| 0.053         | 13.15 | 660  | 0.0807          |
| 0.053         | 13.35 | 670  | 0.0792          |
| 0.053         | 13.55 | 680  | 0.0792          |
| 0.053         | 13.75 | 690  | 0.0792          |
| 0.0495        | 13.94 | 700  | 0.0788          |
| 0.0495        | 14.14 | 710  | 0.0783          |
| 0.0495        | 14.34 | 720  | 0.0784          |
| 0.0495        | 14.54 | 730  | 0.0779          |
| 0.0495        | 14.74 | 740  | 0.0776          |
| 0.0477        | 14.94 | 750  | 0.0773          |
| 0.0477        | 15.14 | 760  | 0.0787          |
| 0.0477        | 15.34 | 770  | 0.0772          |
| 0.0477        | 15.54 | 780  | 0.0763          |
| 0.0477        | 15.74 | 790  | 0.0759          |
| 0.0456        | 15.94 | 800  | 0.0766          |
| 0.0456        | 16.14 | 810  | 0.0770          |
| 0.0456        | 16.33 | 820  | 0.0774          |
| 0.0456        | 16.53 | 830  | 0.0770          |
| 0.0456        | 16.73 | 840  | 0.0764          |
| 0.0438        | 16.93 | 850  | 0.0754          |
| 0.0438        | 17.13 | 860  | 0.0759          |
| 0.0438        | 17.33 | 870  | 0.0762          |
| 0.0438        | 17.53 | 880  | 0.0758          |
| 0.0438        | 17.73 | 890  | 0.0761          |
| 0.0415        | 17.93 | 900  | 0.0758          |
| 0.0415        | 18.13 | 910  | 0.0754          |
| 0.0415        | 18.33 | 920  | 0.0754          |
| 0.0415        | 18.53 | 930  | 0.0753          |
| 0.0415        | 18.73 | 940  | 0.0751          |
| 0.0408        | 18.92 | 950  | 0.0752          |
| 0.0408        | 19.12 | 960  | 0.0750          |
| 0.0408        | 19.32 | 970  | 0.0749          |
| 0.0408        | 19.52 | 980  | 0.0749          |
| 0.0408        | 19.72 | 990  | 0.0749          |
| 0.0403        | 19.92 | 1000 | 0.0749          |


### Framework versions

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