---
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- generator
model-index:
- name: swinv2-large-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-large-panorama-IQA

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the isiqa-2019-hf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0352
- Srocc: 0.0683
- Lcc: 0.1820

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 10
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50.0

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Srocc   | Lcc     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| No log        | 0.8889  | 3    | 0.4401          | -0.1586 | -0.1147 |
| No log        | 1.7778  | 6    | 0.2206          | -0.2675 | -0.1545 |
| 0.3084        | 2.9630  | 10   | 0.1910          | -0.2754 | -0.1813 |
| 0.3084        | 3.8519  | 13   | 0.2334          | -0.2170 | -0.1511 |
| 0.3084        | 4.7407  | 16   | 0.1484          | -0.2    | -0.1310 |
| 0.0852        | 5.9259  | 20   | 0.1259          | -0.1021 | -0.0852 |
| 0.0852        | 6.8148  | 23   | 0.1552          | -0.0709 | -0.0595 |
| 0.0852        | 8.0     | 27   | 0.0942          | -0.0948 | -0.0584 |
| 0.0406        | 8.8889  | 30   | 0.0841          | -0.0480 | -0.0550 |
| 0.0406        | 9.7778  | 33   | 0.0886          | -0.0576 | -0.0448 |
| 0.0406        | 10.9630 | 37   | 0.0721          | -0.0773 | -0.0474 |
| 0.023         | 11.8519 | 40   | 0.0697          | -0.0446 | -0.0364 |
| 0.023         | 12.7407 | 43   | 0.0577          | -0.0217 | -0.0091 |
| 0.023         | 13.9259 | 47   | 0.0666          | -0.0314 | 0.0112  |
| 0.0136        | 14.8148 | 50   | 0.0525          | -0.0501 | 0.0060  |
| 0.0136        | 16.0    | 54   | 0.0626          | -0.0178 | 0.0504  |
| 0.0136        | 16.8889 | 57   | 0.0438          | 0.0159  | 0.0827  |
| 0.0113        | 17.7778 | 60   | 0.0503          | 0.0741  | 0.1074  |
| 0.0113        | 18.9630 | 64   | 0.0429          | 0.0818  | 0.1129  |
| 0.0113        | 19.8519 | 67   | 0.0455          | 0.0874  | 0.1188  |
| 0.0097        | 20.7407 | 70   | 0.0597          | 0.0926  | 0.1316  |
| 0.0097        | 21.9259 | 74   | 0.0397          | 0.0614  | 0.1446  |
| 0.0097        | 22.8148 | 77   | 0.0529          | 0.0778  | 0.1637  |
| 0.0084        | 24.0    | 81   | 0.0366          | 0.0716  | 0.1761  |
| 0.0084        | 24.8889 | 84   | 0.0352          | 0.0683  | 0.1820  |
| 0.0084        | 25.7778 | 87   | 0.0491          | 0.0970  | 0.1848  |
| 0.0078        | 26.9630 | 91   | 0.0396          | 0.0984  | 0.1831  |
| 0.0078        | 27.8519 | 94   | 0.0395          | 0.1012  | 0.1856  |
| 0.0078        | 28.7407 | 97   | 0.0426          | 0.1097  | 0.1956  |
| 0.0063        | 29.9259 | 101  | 0.0370          | 0.1002  | 0.1984  |


### Framework versions

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