---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: swinv2-tiny-panorama-IQA
  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. -->

# swinv2-tiny-panorama-IQA

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co./microsoft/swinv2-tiny-patch4-window8-256) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0202
- Srocc: 0.2511
- Lcc: 0.4399

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 10
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50.0

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Srocc   | Lcc     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| No log        | 0.8571  | 3    | 0.1484          | 0.1044  | 0.1970  |
| No log        | 2.0     | 7    | 0.0292          | 0.1107  | 0.1713  |
| 0.1442        | 2.8571  | 10   | 0.0548          | 0.0279  | 0.1178  |
| 0.1442        | 4.0     | 14   | 0.0310          | -0.0628 | 0.0689  |
| 0.1442        | 4.8571  | 17   | 0.0476          | -0.0618 | 0.0550  |
| 0.0425        | 6.0     | 21   | 0.0297          | -0.0978 | 0.0051  |
| 0.0425        | 6.8571  | 24   | 0.0259          | -0.0906 | -0.0039 |
| 0.0425        | 8.0     | 28   | 0.0294          | -0.0270 | 0.0079  |
| 0.0242        | 8.8571  | 31   | 0.0237          | -0.0146 | 0.0323  |
| 0.0242        | 10.0    | 35   | 0.0226          | 0.0152  | 0.0809  |
| 0.0242        | 10.8571 | 38   | 0.0236          | 0.0339  | 0.1158  |
| 0.0146        | 12.0    | 42   | 0.0213          | 0.0562  | 0.1753  |
| 0.0146        | 12.8571 | 45   | 0.0199          | 0.0678  | 0.2241  |
| 0.0146        | 14.0    | 49   | 0.0205          | 0.0981  | 0.2702  |
| 0.0116        | 14.8571 | 52   | 0.0190          | 0.1245  | 0.3000  |
| 0.0116        | 16.0    | 56   | 0.0195          | 0.1595  | 0.3511  |
| 0.0116        | 16.8571 | 59   | 0.0194          | 0.1829  | 0.3804  |
| 0.0096        | 18.0    | 63   | 0.0183          | 0.2144  | 0.4030  |
| 0.0096        | 18.8571 | 66   | 0.0195          | 0.2120  | 0.4086  |
| 0.0075        | 20.0    | 70   | 0.0188          | 0.2164  | 0.4127  |
| 0.0075        | 20.8571 | 73   | 0.0209          | 0.2222  | 0.4224  |
| 0.0075        | 22.0    | 77   | 0.0175          | 0.2288  | 0.4304  |
| 0.0076        | 22.8571 | 80   | 0.0211          | 0.2432  | 0.4326  |
| 0.0076        | 24.0    | 84   | 0.0189          | 0.2346  | 0.4327  |
| 0.0076        | 24.8571 | 87   | 0.0188          | 0.2294  | 0.4313  |
| 0.006         | 26.0    | 91   | 0.0223          | 0.2390  | 0.4343  |
| 0.006         | 26.8571 | 94   | 0.0202          | 0.2511  | 0.4399  |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1