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-blank_img
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: 0.9777131782945736
swin-tiny-patch4-window7-224-blank_img
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: 0.0748
- Accuracy: 0.9777
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 |
|---|---|---|---|---|
| 0.0898 | 0.99 | 72 | 0.1245 | 0.9428 |
| 0.152 | 1.99 | 145 | 0.0811 | 0.9748 |
| 0.1235 | 3.0 | 218 | 0.0958 | 0.9700 |
| 0.1065 | 4.0 | 291 | 0.0748 | 0.9777 |
| 0.1115 | 4.99 | 363 | 0.0947 | 0.9729 |
| 0.0804 | 5.99 | 436 | 0.0888 | 0.9758 |
| 0.0722 | 7.0 | 509 | 0.0827 | 0.9758 |
| 0.061 | 8.0 | 582 | 0.0899 | 0.9758 |
| 0.0706 | 8.99 | 654 | 0.0916 | 0.9758 |
| 0.0633 | 9.9 | 720 | 0.0937 | 0.9758 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0