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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: arieg/4_100_s_200 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# arieg/4_100_s_200 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0155 |
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- Validation Loss: 0.0151 |
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- Train Accuracy: 1.0 |
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- Epoch: 19 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 0.6483 | 0.2667 | 1.0 | 0 | |
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| 0.1768 | 0.1322 | 1.0 | 1 | |
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| 0.1096 | 0.0960 | 1.0 | 2 | |
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| 0.0850 | 0.0781 | 1.0 | 3 | |
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| 0.0710 | 0.0663 | 1.0 | 4 | |
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| 0.0612 | 0.0576 | 1.0 | 5 | |
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| 0.0534 | 0.0506 | 1.0 | 6 | |
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| 0.0472 | 0.0448 | 1.0 | 7 | |
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| 0.0420 | 0.0400 | 1.0 | 8 | |
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| 0.0376 | 0.0359 | 1.0 | 9 | |
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| 0.0339 | 0.0324 | 1.0 | 10 | |
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| 0.0306 | 0.0294 | 1.0 | 11 | |
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| 0.0278 | 0.0267 | 1.0 | 12 | |
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| 0.0253 | 0.0244 | 1.0 | 13 | |
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| 0.0232 | 0.0223 | 1.0 | 14 | |
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| 0.0212 | 0.0205 | 1.0 | 15 | |
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| 0.0196 | 0.0189 | 1.0 | 16 | |
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| 0.0180 | 0.0175 | 1.0 | 17 | |
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| 0.0167 | 0.0162 | 1.0 | 18 | |
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| 0.0155 | 0.0151 | 1.0 | 19 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- TensorFlow 2.14.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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