---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- generator
model-index:
- name: swinv2-base-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-base-panorama-IQA

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the isiqa-2019-hf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0246
- Srocc: 0.0896
- Lcc: 0.1773

## 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: 16
- eval_batch_size: 32
- seed: 10
- gradient_accumulation_steps: 4
- 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    | 0.2685          | -0.1661 | -0.1400 |
| No log        | 2.0     | 7    | 0.0675          | -0.2071 | -0.1319 |
| 0.223         | 2.8571  | 10   | 0.1380          | -0.1972 | -0.1144 |
| 0.223         | 4.0     | 14   | 0.0639          | -0.2362 | -0.1162 |
| 0.223         | 4.8571  | 17   | 0.0601          | -0.1760 | -0.1097 |
| 0.0607        | 6.0     | 21   | 0.0627          | -0.1290 | -0.0852 |
| 0.0607        | 6.8571  | 24   | 0.0543          | -0.1050 | -0.0791 |
| 0.0607        | 8.0     | 28   | 0.0408          | -0.0683 | -0.0702 |
| 0.0212        | 8.8571  | 31   | 0.0419          | -0.0692 | -0.0567 |
| 0.0212        | 10.0    | 35   | 0.0343          | -0.0370 | -0.0274 |
| 0.0212        | 10.8571 | 38   | 0.0307          | -0.0339 | -0.0013 |
| 0.0168        | 12.0    | 42   | 0.0299          | -0.0281 | 0.0233  |
| 0.0168        | 12.8571 | 45   | 0.0300          | -0.0428 | 0.0326  |
| 0.0168        | 14.0    | 49   | 0.0286          | -0.0238 | 0.0517  |
| 0.0143        | 14.8571 | 52   | 0.0283          | -0.0186 | 0.0601  |
| 0.0143        | 16.0    | 56   | 0.0273          | -0.0024 | 0.0868  |
| 0.0143        | 16.8571 | 59   | 0.0257          | 0.0283  | 0.1119  |
| 0.013         | 18.0    | 63   | 0.0247          | 0.0542  | 0.1404  |
| 0.013         | 18.8571 | 66   | 0.0247          | 0.0703  | 0.1533  |
| 0.0111        | 20.0    | 70   | 0.0246          | 0.0800  | 0.1670  |
| 0.0111        | 20.8571 | 73   | 0.0246          | 0.0896  | 0.1773  |
| 0.0111        | 22.0    | 77   | 0.0257          | 0.0998  | 0.1835  |
| 0.0104        | 22.8571 | 80   | 0.0255          | 0.1017  | 0.1943  |
| 0.0104        | 24.0    | 84   | 0.0255          | 0.1149  | 0.2085  |
| 0.0104        | 24.8571 | 87   | 0.0255          | 0.1245  | 0.2155  |
| 0.0088        | 26.0    | 91   | 0.0262          | 0.1319  | 0.2258  |


### Framework versions

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