arieg/bw_spec_cls_4_01_s_200
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: 0.0046
- Train Sparse Categorical Accuracy: 1.0
- Validation Loss: 0.0045
- Validation Sparse Categorical Accuracy: 1.0
- Epoch: 39
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': 28800, '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 | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
---|---|---|---|---|
0.7335 | 0.9306 | 0.3009 | 1.0 | 0 |
0.1862 | 1.0 | 0.1287 | 1.0 | 1 |
0.1060 | 1.0 | 0.0894 | 1.0 | 2 |
0.0803 | 1.0 | 0.0719 | 1.0 | 3 |
0.0664 | 1.0 | 0.0611 | 1.0 | 4 |
0.0570 | 1.0 | 0.0530 | 1.0 | 5 |
0.0498 | 1.0 | 0.0468 | 1.0 | 6 |
0.0440 | 1.0 | 0.0415 | 1.0 | 7 |
0.0392 | 1.0 | 0.0372 | 1.0 | 8 |
0.0352 | 1.0 | 0.0334 | 1.0 | 9 |
0.0317 | 1.0 | 0.0302 | 1.0 | 10 |
0.0287 | 1.0 | 0.0274 | 1.0 | 11 |
0.0261 | 1.0 | 0.0250 | 1.0 | 12 |
0.0238 | 1.0 | 0.0228 | 1.0 | 13 |
0.0218 | 1.0 | 0.0209 | 1.0 | 14 |
0.0200 | 1.0 | 0.0193 | 1.0 | 15 |
0.0184 | 1.0 | 0.0178 | 1.0 | 16 |
0.0170 | 1.0 | 0.0164 | 1.0 | 17 |
0.0157 | 1.0 | 0.0152 | 1.0 | 18 |
0.0146 | 1.0 | 0.0141 | 1.0 | 19 |
0.0136 | 1.0 | 0.0132 | 1.0 | 20 |
0.0126 | 1.0 | 0.0123 | 1.0 | 21 |
0.0118 | 1.0 | 0.0115 | 1.0 | 22 |
0.0111 | 1.0 | 0.0108 | 1.0 | 23 |
0.0104 | 1.0 | 0.0101 | 1.0 | 24 |
0.0097 | 1.0 | 0.0095 | 1.0 | 25 |
0.0091 | 1.0 | 0.0089 | 1.0 | 26 |
0.0086 | 1.0 | 0.0084 | 1.0 | 27 |
0.0081 | 1.0 | 0.0079 | 1.0 | 28 |
0.0077 | 1.0 | 0.0075 | 1.0 | 29 |
0.0072 | 1.0 | 0.0071 | 1.0 | 30 |
0.0069 | 1.0 | 0.0067 | 1.0 | 31 |
0.0065 | 1.0 | 0.0064 | 1.0 | 32 |
0.0062 | 1.0 | 0.0060 | 1.0 | 33 |
0.0058 | 1.0 | 0.0057 | 1.0 | 34 |
0.0056 | 1.0 | 0.0055 | 1.0 | 35 |
0.0053 | 1.0 | 0.0052 | 1.0 | 36 |
0.0050 | 1.0 | 0.0049 | 1.0 | 37 |
0.0048 | 1.0 | 0.0047 | 1.0 | 38 |
0.0046 | 1.0 | 0.0045 | 1.0 | 39 |
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