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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-384 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Prahas10/roof-shingles |
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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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# Prahas10/roof-shingles |
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This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1015 |
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- Validation Loss: 0.3231 |
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- Train Accuracy: 0.9083 |
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- Epoch: 29 |
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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', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 4e-05, 'decay_steps': 138270, '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': 0.0001} |
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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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| 3.8367 | 2.9703 | 0.4403 | 0 | |
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| 1.3092 | 1.6169 | 0.7093 | 1 | |
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| 0.4529 | 1.4414 | 0.7112 | 2 | |
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| 0.2229 | 0.8445 | 0.8368 | 3 | |
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| 0.1451 | 0.7074 | 0.8556 | 4 | |
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| 0.1053 | 0.8585 | 0.7992 | 5 | |
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| 0.1175 | 1.0721 | 0.7389 | 6 | |
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| 0.1388 | 0.5802 | 0.8542 | 7 | |
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| 0.0647 | 0.3764 | 0.9083 | 8 | |
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| 0.1049 | 1.0484 | 0.7366 | 9 | |
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| 0.0740 | 0.6191 | 0.8321 | 10 | |
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| 0.0816 | 0.6273 | 0.8283 | 11 | |
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| 0.0981 | 0.2901 | 0.9172 | 12 | |
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| 0.0614 | 0.5081 | 0.8523 | 13 | |
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| 0.0548 | 0.4983 | 0.8612 | 14 | |
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| 0.0652 | 0.8008 | 0.7850 | 15 | |
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| 0.0857 | 0.5845 | 0.8415 | 16 | |
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| 0.0847 | 0.6887 | 0.8184 | 17 | |
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| 0.0645 | 0.6104 | 0.8405 | 18 | |
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| 0.0891 | 0.4770 | 0.8532 | 19 | |
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| 0.0532 | 0.5074 | 0.8500 | 20 | |
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| 0.0483 | 0.8208 | 0.7850 | 21 | |
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| 0.0498 | 0.2679 | 0.9083 | 22 | |
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| 0.0406 | 0.3261 | 0.9036 | 23 | |
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| 0.0578 | 0.6373 | 0.8340 | 24 | |
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| 0.1010 | 0.5037 | 0.8481 | 25 | |
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| 0.0583 | 0.2993 | 0.8984 | 26 | |
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| 0.0398 | 0.1538 | 0.9492 | 27 | |
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| 0.0492 | 0.4397 | 0.8641 | 28 | |
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| 0.1015 | 0.3231 | 0.9083 | 29 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- TensorFlow 2.15.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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