AIVision
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the chest-xray-classification dataset. It achieves the following results on the evaluation set:
- Loss: 0.1591
- Accuracy: 0.9425
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2661 | 0.99 | 63 | 0.1591 | 0.9425 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
- 8
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for Shamus/AIVision
Base model
google/vit-base-patch16-224-in21kEvaluation results
- Accuracy on chest-xray-classificationvalidation set self-reported0.942