metadata
license: apache-2.0
base_model: 100rab25/swin-tiny-patch4-window7-224-spa_saloon_classification
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-spa_saloon_classification-spa-saloon
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: 0.9825783972125436
swin-tiny-patch4-window7-224-spa_saloon_classification-spa-saloon
This model is a fine-tuned version of 100rab25/swin-tiny-patch4-window7-224-spa_saloon_classification on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0797
- Accuracy: 0.9826
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 |
|---|---|---|---|---|
| 0.2585 | 0.99 | 20 | 0.1616 | 0.9408 |
| 0.2042 | 1.98 | 40 | 0.2162 | 0.9338 |
| 0.1464 | 2.96 | 60 | 0.1001 | 0.9721 |
| 0.1621 | 4.0 | 81 | 0.0915 | 0.9791 |
| 0.1469 | 4.99 | 101 | 0.0797 | 0.9826 |
| 0.1272 | 5.98 | 121 | 0.0753 | 0.9756 |
| 0.0985 | 6.96 | 141 | 0.0860 | 0.9791 |
| 0.1013 | 8.0 | 162 | 0.1178 | 0.9652 |
| 0.111 | 8.99 | 182 | 0.1036 | 0.9652 |
| 0.0737 | 9.88 | 200 | 0.0982 | 0.9686 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0