Instructions to use c14kevincardenas/deit-base-patch16-224-limb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/deit-base-patch16-224-limb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/deit-base-patch16-224-limb") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("c14kevincardenas/deit-base-patch16-224-limb") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/deit-base-patch16-224-limb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
deit-base-patch16-224-limb
This model is a fine-tuned version of facebook/deit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2550
- Accuracy: 0.3336
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2014
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3853 | 1.0 | 215 | 1.3855 | 0.2743 |
| 1.3712 | 2.0 | 430 | 1.3562 | 0.2998 |
| 1.3041 | 3.0 | 645 | 1.3019 | 0.3344 |
| 1.2769 | 4.0 | 860 | 1.2560 | 0.3427 |
| 1.257 | 5.0 | 1075 | 1.2550 | 0.3336 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for c14kevincardenas/deit-base-patch16-224-limb
Base model
facebook/deit-base-patch16-224