amunchet/rorshark-vit-base
image classificationtransformerstransformerstensorboardsafetensorsvitimage-classificationvisionapache-2.0
HuggingFace460.0K
rorshark-vit-base
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0393
- Accuracy: 0.9923
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- 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 |
|---|---|---|---|---|
| 0.0597 | 1.0 | 368 | 0.0546 | 0.9865 |
| 0.2009 | 2.0 | 736 | 0.0531 | 0.9865 |
| 0.0114 | 3.0 | 1104 | 0.0418 | 0.9904 |
| 0.0998 | 4.0 | 1472 | 0.0425 | 0.9904 |
| 0.1244 | 5.0 | 1840 | 0.0393 | 0.9923 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0