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-sar
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: 0.9880478087649402
swin-tiny-patch4-window7-224-finetuned-sar
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: 0.0351
- Accuracy: 0.9880
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: 0.0001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3706 | 1.0 | 53 | 0.1639 | 0.9442 |
| 0.3062 | 2.0 | 106 | 0.1337 | 0.9509 |
| 0.264 | 3.0 | 159 | 0.0671 | 0.9748 |
| 0.1861 | 4.0 | 212 | 0.0470 | 0.9854 |
| 0.2131 | 5.0 | 265 | 0.0351 | 0.9880 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.2
- Tokenizers 0.13.3