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: 0.9966577540106952
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: 0.0271
- Accuracy: 0.9967
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.0898 | 1.0 | 327 | 0.0707 | 0.9757 |
| 0.0221 | 2.0 | 654 | 0.0278 | 0.9920 |
| 0.06 | 3.0 | 981 | 0.0345 | 0.9913 |
| 0.0094 | 4.0 | 1309 | 0.0300 | 0.9947 |
| 0.0004 | 5.0 | 1636 | 0.0398 | 0.9942 |
| 0.0035 | 6.0 | 1963 | 0.0136 | 0.9975 |
| 0.0246 | 7.0 | 2290 | 0.0339 | 0.9940 |
| 0.0012 | 8.0 | 2618 | 0.0316 | 0.9958 |
| 0.0 | 9.0 | 2945 | 0.0302 | 0.9964 |
| 0.0 | 10.0 | 3272 | 0.0201 | 0.9973 |
| 0.0003 | 11.0 | 3599 | 0.0222 | 0.9955 |
| 0.0 | 12.0 | 3927 | 0.0218 | 0.9962 |
| 0.0001 | 13.0 | 4254 | 0.0293 | 0.9962 |
| 0.0002 | 14.0 | 4581 | 0.0272 | 0.9962 |
| 0.0 | 14.99 | 4905 | 0.0271 | 0.9967 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0