Instructions to use cdstelly/vit-xray-pneumonia-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cdstelly/vit-xray-pneumonia-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cdstelly/vit-xray-pneumonia-classification") 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("cdstelly/vit-xray-pneumonia-classification") model = AutoModelForImageClassification.from_pretrained("cdstelly/vit-xray-pneumonia-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
vit-xray-pneumonia-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1222
- Accuracy: 0.9614
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.073 | 0.9882 | 63 | 0.1030 | 0.9639 |
| 0.0719 | 1.9882 | 126 | 0.1485 | 0.9519 |
| 0.0813 | 2.9882 | 189 | 0.1420 | 0.9494 |
| 0.0602 | 3.9882 | 252 | 0.0957 | 0.9674 |
| 0.0688 | 4.9882 | 315 | 0.1031 | 0.9665 |
| 0.0664 | 5.9882 | 378 | 0.1075 | 0.9657 |
| 0.0525 | 6.9882 | 441 | 0.1222 | 0.9614 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
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Model tree for cdstelly/vit-xray-pneumonia-classification
Base model
google/vit-base-patch16-224-in21k