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# swin-tiny-patch4-window7-224-finetuned-eurosat

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4697
- Accuracy: 0.8072

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 60

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8889  | 6    | 0.6376          | 0.6899   |
| 0.6757        | 1.9259  | 13   | 0.6053          | 0.6938   |
| 0.5472        | 2.9630  | 20   | 0.5903          | 0.7256   |
| 0.5472        | 4.0     | 27   | 0.5782          | 0.7316   |
| 0.4628        | 4.8889  | 33   | 0.5979          | 0.7455   |
| 0.4181        | 5.9259  | 40   | 0.5735          | 0.7614   |
| 0.4181        | 6.9630  | 47   | 0.5252          | 0.7495   |
| 0.4079        | 8.0     | 54   | 0.5363          | 0.7475   |
| 0.4102        | 8.8889  | 60   | 0.5289          | 0.7495   |
| 0.4102        | 9.9259  | 67   | 0.5227          | 0.7535   |
| 0.373         | 10.9630 | 74   | 0.4677          | 0.7773   |
| 0.3639        | 12.0    | 81   | 0.4978          | 0.7813   |
| 0.3639        | 12.8889 | 87   | 0.4651          | 0.7992   |
| 0.3779        | 13.9259 | 94   | 0.4738          | 0.7913   |
| 0.3476        | 14.9630 | 101  | 0.4697          | 0.8072   |
| 0.3476        | 16.0    | 108  | 0.4719          | 0.7952   |
| 0.3467        | 16.8889 | 114  | 0.4552          | 0.7893   |
| 0.3496        | 17.9259 | 121  | 0.5186          | 0.7714   |
| 0.3496        | 18.9630 | 128  | 0.4575          | 0.7952   |
| 0.3657        | 20.0    | 135  | 0.4764          | 0.7793   |
| 0.3888        | 20.8889 | 141  | 0.5009          | 0.7714   |
| 0.3888        | 21.9259 | 148  | 0.4673          | 0.7813   |
| 0.3236        | 22.9630 | 155  | 0.4931          | 0.7753   |
| 0.3179        | 24.0    | 162  | 0.4837          | 0.7654   |
| 0.3179        | 24.8889 | 168  | 0.4652          | 0.7694   |
| 0.327         | 25.9259 | 175  | 0.5108          | 0.7495   |
| 0.3253        | 26.9630 | 182  | 0.4424          | 0.7833   |
| 0.3253        | 28.0    | 189  | 0.5622          | 0.7336   |
| 0.3382        | 28.8889 | 195  | 0.5068          | 0.7694   |
| 0.331         | 29.9259 | 202  | 0.4530          | 0.7694   |
| 0.331         | 30.9630 | 209  | 0.5205          | 0.7316   |
| 0.3302        | 32.0    | 216  | 0.4386          | 0.7853   |
| 0.2972        | 32.8889 | 222  | 0.5031          | 0.7773   |
| 0.2972        | 33.9259 | 229  | 0.4909          | 0.7575   |
| 0.3121        | 34.9630 | 236  | 0.4766          | 0.7793   |
| 0.2956        | 36.0    | 243  | 0.5262          | 0.7416   |
| 0.2956        | 36.8889 | 249  | 0.5374          | 0.7316   |
| 0.2947        | 37.9259 | 256  | 0.4888          | 0.7674   |
| 0.2662        | 38.9630 | 263  | 0.4881          | 0.7694   |
| 0.2826        | 40.0    | 270  | 0.4669          | 0.7893   |
| 0.2826        | 40.8889 | 276  | 0.4591          | 0.7972   |
| 0.2768        | 41.9259 | 283  | 0.5090          | 0.7575   |
| 0.2836        | 42.9630 | 290  | 0.5250          | 0.7495   |
| 0.2836        | 44.0    | 297  | 0.4748          | 0.7654   |
| 0.2724        | 44.8889 | 303  | 0.4429          | 0.7833   |
| 0.2498        | 45.9259 | 310  | 0.4460          | 0.7893   |
| 0.2498        | 46.9630 | 317  | 0.4722          | 0.7793   |
| 0.2893        | 48.0    | 324  | 0.4799          | 0.7714   |
| 0.2618        | 48.8889 | 330  | 0.4850          | 0.7714   |
| 0.2618        | 49.9259 | 337  | 0.5152          | 0.7495   |
| 0.2664        | 50.9630 | 344  | 0.5347          | 0.7396   |
| 0.27          | 52.0    | 351  | 0.5343          | 0.7416   |
| 0.27          | 52.8889 | 357  | 0.5330          | 0.7416   |
| 0.2539        | 53.3333 | 360  | 0.5320          | 0.7396   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1

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