arieg/spec_cls_80_v2
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: 1.0698
- Validation Loss: 1.0517
- Train Accuracy: 1.0
- Epoch: 9
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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 14400, '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 |
---|---|---|---|
4.2243 | 4.0115 | 0.575 | 0 |
3.6964 | 3.4678 | 0.9125 | 1 |
3.1703 | 2.9932 | 0.9938 | 2 |
2.7155 | 2.5826 | 0.9938 | 3 |
2.3313 | 2.2229 | 1.0 | 4 |
2.0025 | 1.9208 | 1.0 | 5 |
1.7153 | 1.6639 | 1.0 | 6 |
1.4721 | 1.4462 | 1.0 | 7 |
1.2586 | 1.2279 | 1.0 | 8 |
1.0698 | 1.0517 | 1.0 | 9 |
Framework versions
- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google/vit-base-patch16-224-in21k