---
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_3
  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_3

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: 0.1155

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 8.243         | 0.2   | 10   | 7.8185          |
| 7.4602        | 0.4   | 20   | 6.3280          |
| 4.794         | 0.6   | 30   | 3.1068          |
| 1.6994        | 0.8   | 40   | 0.6354          |
| 0.543         | 1.0   | 50   | 0.5653          |
| 0.4542        | 1.2   | 60   | 0.4874          |
| 0.4449        | 1.39  | 70   | 0.4225          |
| 0.3623        | 1.59  | 80   | 0.3685          |
| 0.278         | 1.79  | 90   | 0.3283          |
| 0.2385        | 1.99  | 100  | 0.2983          |
| 0.2499        | 2.19  | 110  | 0.2748          |
| 0.2113        | 2.39  | 120  | 0.2590          |
| 0.1966        | 2.59  | 130  | 0.2420          |
| 0.217         | 2.79  | 140  | 0.2242          |
| 0.1731        | 2.99  | 150  | 0.2121          |
| 0.1779        | 3.19  | 160  | 0.2033          |
| 0.1687        | 3.39  | 170  | 0.1909          |
| 0.156         | 3.59  | 180  | 0.1833          |
| 0.1464        | 3.78  | 190  | 0.1763          |
| 0.1637        | 3.98  | 200  | 0.1706          |
| 0.1455        | 4.18  | 210  | 0.1649          |
| 0.128         | 4.38  | 220  | 0.1621          |
| 0.1537        | 4.58  | 230  | 0.1562          |
| 0.1193        | 4.78  | 240  | 0.1502          |
| 0.1323        | 4.98  | 250  | 0.1464          |
| 0.1346        | 5.18  | 260  | 0.1440          |
| 0.1049        | 5.38  | 270  | 0.1411          |
| 0.1265        | 5.58  | 280  | 0.1377          |
| 0.13          | 5.78  | 290  | 0.1363          |
| 0.1059        | 5.98  | 300  | 0.1335          |
| 0.1141        | 6.18  | 310  | 0.1300          |
| 0.1097        | 6.37  | 320  | 0.1297          |
| 0.1088        | 6.57  | 330  | 0.1287          |
| 0.106         | 6.77  | 340  | 0.1261          |
| 0.1011        | 6.97  | 350  | 0.1243          |
| 0.0999        | 7.17  | 360  | 0.1235          |
| 0.1081        | 7.37  | 370  | 0.1223          |
| 0.0999        | 7.57  | 380  | 0.1207          |
| 0.1057        | 7.77  | 390  | 0.1203          |
| 0.0937        | 7.97  | 400  | 0.1192          |
| 0.0842        | 8.17  | 410  | 0.1195          |
| 0.0907        | 8.37  | 420  | 0.1182          |
| 0.1109        | 8.57  | 430  | 0.1176          |
| 0.0901        | 8.76  | 440  | 0.1170          |
| 0.1005        | 8.96  | 450  | 0.1162          |
| 0.0961        | 9.16  | 460  | 0.1159          |
| 0.0927        | 9.36  | 470  | 0.1156          |
| 0.0916        | 9.56  | 480  | 0.1158          |
| 0.0908        | 9.76  | 490  | 0.1156          |
| 0.0909        | 9.96  | 500  | 0.1155          |


### Framework versions

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