---
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: 0.1176

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.1178        | 0.2   | 10   | 7.7550          |
| 7.3762        | 0.4   | 20   | 6.3827          |
| 4.9217        | 0.6   | 30   | 3.2172          |
| 1.7792        | 0.8   | 40   | 0.6700          |
| 0.5779        | 1.0   | 50   | 0.5969          |
| 0.4824        | 1.2   | 60   | 0.5149          |
| 0.4689        | 1.39  | 70   | 0.4440          |
| 0.3833        | 1.59  | 80   | 0.3862          |
| 0.2916        | 1.79  | 90   | 0.3364          |
| 0.2435        | 1.99  | 100  | 0.3013          |
| 0.2538        | 2.19  | 110  | 0.2779          |
| 0.2147        | 2.39  | 120  | 0.2619          |
| 0.1982        | 2.59  | 130  | 0.2453          |
| 0.2183        | 2.79  | 140  | 0.2275          |
| 0.1737        | 2.99  | 150  | 0.2148          |
| 0.1794        | 3.19  | 160  | 0.2068          |
| 0.1692        | 3.39  | 170  | 0.1949          |
| 0.1573        | 3.59  | 180  | 0.1864          |
| 0.1478        | 3.78  | 190  | 0.1788          |
| 0.164         | 3.98  | 200  | 0.1732          |
| 0.1454        | 4.18  | 210  | 0.1676          |
| 0.1279        | 4.38  | 220  | 0.1653          |
| 0.1544        | 4.58  | 230  | 0.1595          |
| 0.1206        | 4.78  | 240  | 0.1524          |
| 0.1334        | 4.98  | 250  | 0.1486          |
| 0.1342        | 5.18  | 260  | 0.1472          |
| 0.1061        | 5.38  | 270  | 0.1442          |
| 0.1265        | 5.58  | 280  | 0.1427          |
| 0.131         | 5.78  | 290  | 0.1389          |
| 0.1067        | 5.98  | 300  | 0.1374          |
| 0.1158        | 6.18  | 310  | 0.1331          |
| 0.1114        | 6.37  | 320  | 0.1323          |
| 0.1104        | 6.57  | 330  | 0.1311          |
| 0.108         | 6.77  | 340  | 0.1281          |
| 0.1015        | 6.97  | 350  | 0.1271          |
| 0.1           | 7.17  | 360  | 0.1262          |
| 0.1091        | 7.37  | 370  | 0.1242          |
| 0.1013        | 7.57  | 380  | 0.1230          |
| 0.1074        | 7.77  | 390  | 0.1233          |
| 0.0946        | 7.97  | 400  | 0.1226          |
| 0.0854        | 8.17  | 410  | 0.1222          |
| 0.0914        | 8.37  | 420  | 0.1205          |
| 0.1117        | 8.57  | 430  | 0.1198          |
| 0.0922        | 8.76  | 440  | 0.1194          |
| 0.1012        | 8.96  | 450  | 0.1185          |
| 0.0964        | 9.16  | 460  | 0.1185          |
| 0.0948        | 9.36  | 470  | 0.1181          |
| 0.0943        | 9.56  | 480  | 0.1178          |
| 0.0915        | 9.76  | 490  | 0.1176          |
| 0.0924        | 9.96  | 500  | 0.1176          |


### Framework versions

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