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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: akar49/mri_classifier |
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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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# akar49/mri_classifier |
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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: 0.1032 |
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- Validation Loss: 0.1556 |
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- Train Accuracy: 0.9367 |
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- Epoch: 14 |
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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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'momentum': 0.0, 'nesterov': False} |
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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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| 0.6447 | 0.6133 | 0.7004 | 0 | |
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| 0.5405 | 0.5010 | 0.8256 | 1 | |
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| 0.4181 | 0.3917 | 0.8650 | 2 | |
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| 0.3122 | 0.3189 | 0.9058 | 3 | |
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| 0.2474 | 0.3069 | 0.8875 | 4 | |
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| 0.2021 | 0.2733 | 0.9044 | 5 | |
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| 0.1745 | 0.2455 | 0.9100 | 6 | |
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| 0.1591 | 0.2203 | 0.9212 | 7 | |
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| 0.1450 | 0.2350 | 0.9142 | 8 | |
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| 0.1397 | 0.2122 | 0.9198 | 9 | |
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| 0.1227 | 0.2098 | 0.9212 | 10 | |
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| 0.1169 | 0.1754 | 0.9325 | 11 | |
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| 0.1080 | 0.1782 | 0.9339 | 12 | |
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| 0.0971 | 0.1705 | 0.9353 | 13 | |
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| 0.1032 | 0.1556 | 0.9367 | 14 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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