Instructions to use zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow") model = AutoModelForImageClassification.from_pretrained("zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow") - Notebooks
- Google Colab
- Kaggle
swin-tiny-patch4-window7-224-finetuned-black_widow
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1422
- Accuracy: 0.945
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1728 | 0.96 | 12 | 0.1506 | 0.935 |
| 0.1408 | 2.0 | 25 | 0.1422 | 0.945 |
| 0.1669 | 2.96 | 37 | 0.1289 | 0.945 |
| 0.1618 | 4.0 | 50 | 0.1126 | 0.945 |
| 0.1383 | 4.8 | 60 | 0.1200 | 0.94 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for zkdeng/swin-tiny-patch4-window7-224-finetuned-black_widow
Base model
microsoft/swin-tiny-patch4-window7-224