aspends/binary_tumor_classifier
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:
- Train Loss: 0.0614
- Validation Loss: 1.8879
- Train Accuracy: 0.5166
- Epoch: 4
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 6585, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Validation Loss | Train Accuracy | Epoch |
---|---|---|---|
0.3737 | 1.3685 | 0.4864 | 0 |
0.1417 | 1.5816 | 0.5136 | 1 |
0.1013 | 1.6942 | 0.5196 | 2 |
0.0573 | 1.8671 | 0.5257 | 3 |
0.0614 | 1.8879 | 0.5166 | 4 |
Framework versions
- Transformers 4.34.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1
- Downloads last month
- 58
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for aspends/binary_tumor_classifier
Base model
google/vit-base-patch16-224-in21k