metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: SEMDataset
split: train
args: SEMDataset
metrics:
- name: Accuracy
type: accuracy
value: 0.782051282051282
swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5657
- Accuracy: 0.7821
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1465 | 0.97 | 16 | 1.8341 | 0.3462 |
| 1.7722 | 2.0 | 33 | 1.5865 | 0.4017 |
| 1.6005 | 2.97 | 49 | 1.4867 | 0.4060 |
| 1.429 | 4.0 | 66 | 1.3933 | 0.4487 |
| 1.2294 | 4.97 | 82 | 1.2696 | 0.5385 |
| 1.1224 | 6.0 | 99 | 1.2842 | 0.5641 |
| 0.9776 | 6.97 | 115 | 0.9923 | 0.6197 |
| 0.8678 | 8.0 | 132 | 1.1118 | 0.6368 |
| 0.8125 | 8.97 | 148 | 0.8974 | 0.6624 |
| 0.7022 | 10.0 | 165 | 0.8582 | 0.6838 |
| 0.6047 | 10.97 | 181 | 0.7019 | 0.7393 |
| 0.6223 | 12.0 | 198 | 0.6818 | 0.7308 |
| 0.5331 | 12.97 | 214 | 0.8265 | 0.7051 |
| 0.4995 | 14.0 | 231 | 0.6365 | 0.7521 |
| 0.4132 | 14.97 | 247 | 0.6585 | 0.7308 |
| 0.3978 | 16.0 | 264 | 0.5789 | 0.7692 |
| 0.3388 | 16.97 | 280 | 0.6038 | 0.7650 |
| 0.3376 | 18.0 | 297 | 0.5306 | 0.7821 |
| 0.3455 | 18.97 | 313 | 0.5797 | 0.7692 |
| 0.3207 | 19.39 | 320 | 0.5657 | 0.7821 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3