metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
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: 0.8666666666666667
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: 0.3718
- Accuracy: 0.8667
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.92 | 3 | 0.6033 | 0.6889 |
| No log | 1.85 | 6 | 0.5412 | 0.7111 |
| No log | 2.77 | 9 | 0.4459 | 0.7778 |
| 0.5428 | 4.0 | 13 | 0.4544 | 0.8444 |
| 0.5428 | 4.92 | 16 | 0.3929 | 0.9111 |
| 0.5428 | 5.85 | 19 | 0.3823 | 0.8667 |
| 0.4248 | 6.77 | 22 | 0.3531 | 0.8889 |
| 0.4248 | 8.0 | 26 | 0.3560 | 0.8889 |
| 0.4248 | 8.92 | 29 | 0.3694 | 0.8667 |
| 0.382 | 9.23 | 30 | 0.3718 | 0.8667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0