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--- |
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license: other |
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base_model: nvidia/segformer-b0-finetuned-ade-512-512 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Segformer-MRIseg_model |
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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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# Segformer-MRIseg_model |
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This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0049 |
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- Validation Loss: 0.0133 |
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- Epoch: 59 |
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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': 'Adam', '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, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 0.2537 | 0.0685 | 0 | |
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| 0.0849 | 0.0639 | 1 | |
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| 0.0664 | 0.0532 | 2 | |
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| 0.0580 | 0.0503 | 3 | |
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| 0.0536 | 0.0497 | 4 | |
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| 0.0476 | 0.0396 | 5 | |
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| 0.0437 | 0.0477 | 6 | |
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| 0.0359 | 0.0397 | 7 | |
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| 0.0312 | 0.0289 | 8 | |
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| 0.0256 | 0.0322 | 9 | |
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| 0.0241 | 0.0279 | 10 | |
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| 0.0220 | 0.0229 | 11 | |
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| 0.0180 | 0.0226 | 12 | |
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| 0.0160 | 0.0192 | 13 | |
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| 0.0165 | 0.0227 | 14 | |
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| 0.0151 | 0.0194 | 15 | |
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| 0.0146 | 0.0184 | 16 | |
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| 0.0132 | 0.0177 | 17 | |
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| 0.0121 | 0.0211 | 18 | |
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| 0.0111 | 0.0197 | 19 | |
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| 0.0107 | 0.0175 | 20 | |
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| 0.0116 | 0.0131 | 21 | |
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| 0.0115 | 0.0181 | 22 | |
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| 0.0094 | 0.0153 | 23 | |
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| 0.0099 | 0.0140 | 24 | |
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| 0.0098 | 0.0151 | 25 | |
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| 0.0084 | 0.0126 | 26 | |
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| 0.0080 | 0.0140 | 27 | |
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| 0.0071 | 0.0128 | 28 | |
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| 0.0067 | 0.0169 | 29 | |
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| 0.0061 | 0.0131 | 30 | |
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| 0.0063 | 0.0207 | 31 | |
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| 0.0067 | 0.0129 | 32 | |
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| 0.0062 | 0.0152 | 33 | |
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| 0.0056 | 0.0148 | 34 | |
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| 0.0056 | 0.0171 | 35 | |
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| 0.0051 | 0.0154 | 36 | |
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| 0.0049 | 0.0172 | 37 | |
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| 0.0049 | 0.0180 | 38 | |
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| 0.0056 | 0.0168 | 39 | |
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| 0.0050 | 0.0142 | 40 | |
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| 0.0048 | 0.0165 | 41 | |
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| 0.0051 | 0.0195 | 42 | |
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| 0.0048 | 0.0232 | 43 | |
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| 0.0042 | 0.0208 | 44 | |
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| 0.0041 | 0.0249 | 45 | |
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| 0.0044 | 0.0220 | 46 | |
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| 0.0041 | 0.0234 | 47 | |
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| 0.0042 | 0.0198 | 48 | |
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| 0.0040 | 0.0282 | 49 | |
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| 0.0039 | 0.0251 | 50 | |
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| 0.0039 | 0.0302 | 51 | |
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| 0.0041 | 0.0219 | 52 | |
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| 0.0040 | 0.0187 | 53 | |
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| 0.0039 | 0.0203 | 54 | |
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| 0.0043 | 0.0180 | 55 | |
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| 0.0051 | 0.0150 | 56 | |
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| 0.0079 | 0.0205 | 57 | |
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| 0.0052 | 0.0152 | 58 | |
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| 0.0049 | 0.0133 | 59 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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