---
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: 0.0254
- Srocc: 0.1552
- Lcc: 0.2308

## 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    | 0.2656          | -0.1585 | -0.1388 |
| No log        | 2.0     | 7    | 0.0658          | -0.1810 | -0.1277 |
| 0.2144        | 2.8571  | 10   | 0.1341          | -0.1684 | -0.1185 |
| 0.2144        | 4.0     | 14   | 0.0562          | -0.2382 | -0.1379 |
| 0.2144        | 4.8571  | 17   | 0.0616          | -0.1657 | -0.1428 |
| 0.0575        | 6.0     | 21   | 0.0594          | -0.1501 | -0.1185 |
| 0.0575        | 6.8571  | 24   | 0.0513          | -0.1204 | -0.1122 |
| 0.0575        | 8.0     | 28   | 0.0417          | -0.0693 | -0.0987 |
| 0.0201        | 8.8571  | 31   | 0.0406          | -0.0714 | -0.0813 |
| 0.0201        | 10.0    | 35   | 0.0343          | -0.0236 | -0.0385 |
| 0.0201        | 10.8571 | 38   | 0.0315          | 0.0074  | 0.0011  |
| 0.0142        | 12.0    | 42   | 0.0309          | 0.0218  | 0.0326  |
| 0.0142        | 12.8571 | 45   | 0.0310          | 0.0381  | 0.0466  |
| 0.0142        | 14.0    | 49   | 0.0299          | 0.0535  | 0.0681  |
| 0.0097        | 14.8571 | 52   | 0.0314          | 0.0604  | 0.0749  |
| 0.0097        | 16.0    | 56   | 0.0288          | 0.0785  | 0.1049  |
| 0.0097        | 16.8571 | 59   | 0.0283          | 0.0944  | 0.1269  |
| 0.0083        | 18.0    | 63   | 0.0298          | 0.1022  | 0.1448  |
| 0.0083        | 18.8571 | 66   | 0.0274          | 0.1118  | 0.1651  |
| 0.0063        | 20.0    | 70   | 0.0286          | 0.1224  | 0.1703  |
| 0.0063        | 20.8571 | 73   | 0.0283          | 0.1371  | 0.1833  |
| 0.0063        | 22.0    | 77   | 0.0282          | 0.1317  | 0.1944  |
| 0.0059        | 22.8571 | 80   | 0.0277          | 0.1382  | 0.2035  |
| 0.0059        | 24.0    | 84   | 0.0270          | 0.1479  | 0.2146  |
| 0.0059        | 24.8571 | 87   | 0.0263          | 0.1500  | 0.2197  |
| 0.0046        | 26.0    | 91   | 0.0269          | 0.1364  | 0.2199  |
| 0.0046        | 26.8571 | 94   | 0.0259          | 0.1406  | 0.2251  |
| 0.0046        | 28.0    | 98   | 0.0254          | 0.1552  | 0.2308  |
| 0.0039        | 28.8571 | 101  | 0.0267          | 0.1480  | 0.2261  |
| 0.0039        | 30.0    | 105  | 0.0270          | 0.1489  | 0.2247  |
| 0.0039        | 30.8571 | 108  | 0.0261          | 0.1576  | 0.2319  |
| 0.0041        | 32.0    | 112  | 0.0268          | 0.1630  | 0.2311  |
| 0.0041        | 32.8571 | 115  | 0.0282          | 0.1570  | 0.2257  |


### Framework versions

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