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# swin-base-patch4-window7-224-in22k-finetuned_swinv1-autotags-224

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1186
- Accuracy: 0.9675

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1468        | 0.99  | 61   | 0.8540          | 0.7503   |
| 0.6167        | 1.99  | 122  | 0.3772          | 0.8904   |
| 0.45          | 2.99  | 183  | 0.2963          | 0.9086   |
| 0.2163        | 3.99  | 244  | 0.2172          | 0.9391   |
| 0.209         | 4.99  | 305  | 0.1733          | 0.9431   |
| 0.1558        | 5.99  | 366  | 0.2101          | 0.9310   |
| 0.109         | 6.99  | 427  | 0.1268          | 0.9655   |
| 0.1214        | 7.99  | 488  | 0.1251          | 0.9706   |
| 0.1471        | 8.99  | 549  | 0.1194          | 0.9665   |
| 0.0888        | 9.99  | 610  | 0.1376          | 0.9574   |
| 0.1077        | 10.99 | 671  | 0.1211          | 0.9614   |
| 0.0969        | 11.99 | 732  | 0.1231          | 0.9695   |
| 0.0585        | 12.99 | 793  | 0.1472          | 0.9553   |
| 0.0659        | 13.99 | 854  | 0.1203          | 0.9655   |
| 0.0645        | 14.99 | 915  | 0.1405          | 0.9614   |
| 0.0472        | 15.99 | 976  | 0.1340          | 0.9604   |
| 0.0616        | 16.99 | 1037 | 0.1272          | 0.9655   |
| 0.0609        | 17.99 | 1098 | 0.1121          | 0.9685   |
| 0.0525        | 18.99 | 1159 | 0.1162          | 0.9685   |
| 0.0406        | 19.99 | 1220 | 0.1186          | 0.9675   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.10.2+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2

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