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--- |
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license: other |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: sayakpaul/mit-b0-finetuned-sidewalks |
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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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# sayakpaul/mit-b0-finetuned-sidewalks |
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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: 0.8850 |
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- Validation Loss: 0.7741 |
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- Validation Mean Iou: 0.2215 |
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- Validation Mean Accuracy: 0.2711 |
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- Validation Overall Accuracy: 0.7807 |
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- Validation Per Category Iou: [0. 0.56319416 0.79436978 0.22447649 0.37746306 0.2182132 |
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nan 0.17433499 0.35240193 0. 0.64391654 0. |
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0. nan 0. 0. 0. 0. |
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0.61824159 0. 0.36925143 0.09610409 0. nan |
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0. 0.23049759 0. 0. 0.79662258 0.72121144 |
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0.85940151 0. 0.00144295 0.04769959 0. ] |
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- Validation Per Category Accuracy: [0. 0.7334003 0.94650286 0.24751216 0.4478931 0.27208929 |
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nan 0.22448353 0.45667969 0. 0.92555657 0. |
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0. nan 0. 0. 0. 0. |
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0.85871282 0. 0.43579563 0.09928831 0. nan |
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0. 0.25660062 0. 0. 0.93127726 0.85151776 |
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0.9323404 0. 0.00144459 0.05442322 0. ] |
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- Epoch: 1 |
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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', '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 | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Per Category Iou | Validation Per Category Accuracy | Epoch | |
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|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----:| |
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| 1.5309 | 0.9380 | 0.1674 | 0.2153 | 0.7545 | [0.00000000e+00 5.50637719e-01 7.61499932e-01 6.48396077e-04 |
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3.56923200e-01 9.75833116e-02 0.00000000e+00 2.82588573e-02 |
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5.28802378e-02 0.00000000e+00 5.93637894e-01 0.00000000e+00 |
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0.00000000e+00 nan 0.00000000e+00 0.00000000e+00 |
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0.00000000e+00 0.00000000e+00 5.53393589e-01 0.00000000e+00 |
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1.50378244e-01 1.75413833e-02 0.00000000e+00 nan |
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0.00000000e+00 2.76097981e-02 0.00000000e+00 0.00000000e+00 |
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7.86211179e-01 7.05492777e-01 8.34315629e-01 0.00000000e+00 |
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0.00000000e+00 7.43899822e-03 0.00000000e+00] | [0.00000000e+00 7.08723416e-01 9.71019213e-01 6.48665345e-04 |
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4.09438347e-01 1.09468057e-01 nan 3.05932982e-02 |
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5.44133505e-02 0.00000000e+00 8.74063503e-01 0.00000000e+00 |
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0.00000000e+00 nan 0.00000000e+00 0.00000000e+00 |
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0.00000000e+00 0.00000000e+00 8.66648886e-01 0.00000000e+00 |
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1.61194155e-01 1.77691783e-02 0.00000000e+00 nan |
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0.00000000e+00 2.81195635e-02 0.00000000e+00 0.00000000e+00 |
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9.17500033e-01 8.30294930e-01 9.02491399e-01 0.00000000e+00 |
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0.00000000e+00 7.77243386e-03 0.00000000e+00] | 0 | |
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| 0.8850 | 0.7741 | 0.2215 | 0.2711 | 0.7807 | [0. 0.56319416 0.79436978 0.22447649 0.37746306 0.2182132 |
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nan 0.17433499 0.35240193 0. 0.64391654 0. |
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0. nan 0. 0. 0. 0. |
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0.61824159 0. 0.36925143 0.09610409 0. nan |
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0. 0.23049759 0. 0. 0.79662258 0.72121144 |
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0.85940151 0. 0.00144295 0.04769959 0. ] | [0. 0.7334003 0.94650286 0.24751216 0.4478931 0.27208929 |
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nan 0.22448353 0.45667969 0. 0.92555657 0. |
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0. nan 0. 0. 0. 0. |
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0.85871282 0. 0.43579563 0.09928831 0. nan |
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0. 0.25660062 0. 0. 0.93127726 0.85151776 |
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0.9323404 0. 0.00144459 0.05442322 0. ] | 1 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- TensorFlow 2.9.2 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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