Instructions to use JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune") 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("JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune") model = AutoModelForImageClassification.from_pretrained("JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
quickdraw-MobileViT-xxs-a
This model is a fine-tuned version of apple/mobilevit-xx-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1512
- Accuracy: 0.7126
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: 0.0008
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5000
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8007 | 0.5688 | 5000 | 1.7490 | 0.5725 |
| 1.5116 | 1.1377 | 10000 | 1.5185 | 0.6256 |
| 1.4298 | 1.7065 | 15000 | 1.4384 | 0.6438 |
| 1.3622 | 2.2753 | 20000 | 1.3908 | 0.6547 |
| 1.332 | 2.8441 | 25000 | 1.3210 | 0.6712 |
| 1.2903 | 3.4130 | 30000 | 1.2758 | 0.6824 |
| 1.2693 | 3.9818 | 35000 | 1.2592 | 0.6864 |
| 1.2391 | 4.5506 | 40000 | 1.2169 | 0.6965 |
| 1.2078 | 5.1195 | 45000 | 1.1928 | 0.7023 |
| 1.1959 | 5.6883 | 50000 | 1.1779 | 0.7059 |
| 1.1749 | 6.2571 | 55000 | 1.1669 | 0.7083 |
| 1.1713 | 6.8259 | 60000 | 1.1564 | 0.7110 |
| 1.1573 | 7.3948 | 65000 | 1.1524 | 0.7123 |
| 1.1555 | 7.9636 | 70000 | 1.1512 | 0.7126 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for JoshuaKelleyDs/quickdraw-MobileVIT-xxs-finetune
Base model
apple/mobilevit-xx-small