vit-base-gpu
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: 0.1093
- Accuracy: 0.9736
- Confusion Matrix: [[60, 6], [0, 161]]
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 285
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Confusion Matrix |
|---|---|---|---|---|---|
| 0.1208 | 1.7544 | 100 | 0.1628 | 0.9648 | [[58, 8], [0, 161]] |
| 0.0908 | 3.5088 | 200 | 0.1093 | 0.9736 | [[60, 6], [0, 161]] |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for jerlawson13/vit-base-gpu
Base model
google/vit-base-patch16-224-in21k