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: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
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: 0.0133
- Accuracy: 1.0
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8235 | 1.0 | 13 | 0.6034 | 0.9239 |
| 0.5091 | 2.0 | 26 | 0.1870 | 0.9728 |
| 0.273 | 3.0 | 39 | 0.0895 | 0.9946 |
| 0.1401 | 4.0 | 52 | 0.0543 | 0.9946 |
| 0.0936 | 5.0 | 65 | 0.0484 | 0.9891 |
| 0.091 | 6.0 | 78 | 0.0498 | 0.9891 |
| 0.0603 | 7.0 | 91 | 0.0133 | 1.0 |
| 0.0421 | 8.0 | 104 | 0.0196 | 0.9946 |
| 0.0557 | 9.0 | 117 | 0.0172 | 0.9946 |
| 0.0552 | 10.0 | 130 | 0.0103 | 1.0 |
| 0.045 | 11.0 | 143 | 0.0082 | 1.0 |
| 0.0355 | 12.0 | 156 | 0.0071 | 1.0 |
| 0.0491 | 13.0 | 169 | 0.0087 | 1.0 |
| 0.0384 | 14.0 | 182 | 0.0065 | 1.0 |
| 0.0324 | 15.0 | 195 | 0.0061 | 1.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3