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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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- vision |
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- image-segmentation |
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model-index: |
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- name: mit-b0-finetuned-sidewalk-semantic |
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results: [] |
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datasets: |
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- segments/sidewalk-semantic |
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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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# mit-b0-finetuned-sidewalk-semantic |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.2125 |
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- Validation Loss: 0.5151 |
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- Epoch: 49 |
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## Model description |
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The model was fine-tuned from [this model](https://huggingface.co/nvidia/mit-b0). More information about the model is available |
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[here](https://huggingface.co/docs/transformers/model_doc/segformer). |
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## Intended uses & limitations |
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This fine-tuned model is just for demonstration purposes. Before using it in production, it should be thoroughly inspected and adjusted |
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if needed. |
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## Training and evaluation data |
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[`segments/sidewalk-semantic`](https://huggingface.co/datasets/segments/sidewalk-semantic) |
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## Training procedure |
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More information is available here: [deep-diver/segformer-tf-transformers](https://github.com/deep-diver/segformer-tf-transformers). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'Adam', 'learning_rate': 6e-05, 'decay': 0.0, '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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| 2.0785 | 1.1753 | 0 | |
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| 1.1312 | 0.8807 | 1 | |
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| 0.9315 | 0.7585 | 2 | |
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| 0.7952 | 0.7261 | 3 | |
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| 0.7273 | 0.6701 | 4 | |
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| 0.6603 | 0.6396 | 5 | |
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| 0.6198 | 0.6238 | 6 | |
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| 0.5958 | 0.5925 | 7 | |
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| 0.5378 | 0.5714 | 8 | |
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| 0.5236 | 0.5786 | 9 | |
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| 0.4960 | 0.5588 | 10 | |
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| 0.4633 | 0.5624 | 11 | |
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| 0.4562 | 0.5450 | 12 | |
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| 0.4167 | 0.5438 | 13 | |
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| 0.4100 | 0.5248 | 14 | |
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| 0.3947 | 0.5354 | 15 | |
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| 0.3867 | 0.5069 | 16 | |
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| 0.3803 | 0.5285 | 17 | |
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| 0.3696 | 0.5318 | 18 | |
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| 0.3386 | 0.5162 | 19 | |
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| 0.3349 | 0.5312 | 20 | |
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| 0.3233 | 0.5304 | 21 | |
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| 0.3328 | 0.5178 | 22 | |
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| 0.3140 | 0.5131 | 23 | |
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| 0.3081 | 0.5049 | 24 | |
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| 0.3046 | 0.5011 | 25 | |
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| 0.3209 | 0.5197 | 26 | |
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| 0.2966 | 0.5151 | 27 | |
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| 0.2829 | 0.5166 | 28 | |
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| 0.2968 | 0.5210 | 29 | |
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| 0.2818 | 0.5300 | 30 | |
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| 0.2739 | 0.5221 | 31 | |
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| 0.2602 | 0.5340 | 32 | |
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| 0.2570 | 0.5124 | 33 | |
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| 0.2557 | 0.5234 | 34 | |
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| 0.2593 | 0.5098 | 35 | |
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| 0.2582 | 0.5329 | 36 | |
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| 0.2439 | 0.5373 | 37 | |
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| 0.2413 | 0.5141 | 38 | |
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| 0.2423 | 0.5210 | 39 | |
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| 0.2340 | 0.5043 | 40 | |
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| 0.2244 | 0.5300 | 41 | |
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| 0.2246 | 0.4978 | 42 | |
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| 0.2270 | 0.5385 | 43 | |
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| 0.2254 | 0.5125 | 44 | |
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| 0.2176 | 0.5510 | 45 | |
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| 0.2194 | 0.5384 | 46 | |
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| 0.2136 | 0.5186 | 47 | |
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| 0.2121 | 0.5356 | 48 | |
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| 0.2125 | 0.5151 | 49 | |
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### Framework versions |
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- Transformers 4.21.0.dev0 |
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- TensorFlow 2.8.0 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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