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vit-base-patch16-224-in21k-finetunedRCC_Classifier
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: 2.5623
- Accuracy: 0.6074
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0019 | 1.0 | 155 | 2.0291 | 0.6532 |
| 0.0013 | 2.0 | 310 | 2.4863 | 0.6074 |
| 0.001 | 3.0 | 465 | 2.5623 | 0.6074 |
Framework versions
- Transformers 4.34.1
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.14.1
