--- license: other tags: - generated_from_keras_callback model-index: - name: sayakpaul/mit-b0-finetuned-sidewalks results: [] --- # sayakpaul/mit-b0-finetuned-sidewalks This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.8850 - Validation Loss: 0.7741 - Validation Mean Iou: 0.2215 - Validation Mean Accuracy: 0.2711 - Validation Overall Accuracy: 0.7807 - Validation Per Category Iou: [0. 0.56319416 0.79436978 0.22447649 0.37746306 0.2182132 nan 0.17433499 0.35240193 0. 0.64391654 0. 0. nan 0. 0. 0. 0. 0.61824159 0. 0.36925143 0.09610409 0. nan 0. 0.23049759 0. 0. 0.79662258 0.72121144 0.85940151 0. 0.00144295 0.04769959 0. ] - Validation Per Category Accuracy: [0. 0.7334003 0.94650286 0.24751216 0.4478931 0.27208929 nan 0.22448353 0.45667969 0. 0.92555657 0. 0. nan 0. 0. 0. 0. 0.85871282 0. 0.43579563 0.09928831 0. nan 0. 0.25660062 0. 0. 0.93127726 0.85151776 0.9323404 0. 0.00144459 0.05442322 0. ] - Epoch: 1 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'Adam', 'learning_rate': 6e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Per Category Iou | Validation Per Category Accuracy | Epoch | |:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----:| | 1.5309 | 0.9380 | 0.1674 | 0.2153 | 0.7545 | [0.00000000e+00 5.50637719e-01 7.61499932e-01 6.48396077e-04 3.56923200e-01 9.75833116e-02 0.00000000e+00 2.82588573e-02 5.28802378e-02 0.00000000e+00 5.93637894e-01 0.00000000e+00 0.00000000e+00 nan 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.53393589e-01 0.00000000e+00 1.50378244e-01 1.75413833e-02 0.00000000e+00 nan 0.00000000e+00 2.76097981e-02 0.00000000e+00 0.00000000e+00 7.86211179e-01 7.05492777e-01 8.34315629e-01 0.00000000e+00 0.00000000e+00 7.43899822e-03 0.00000000e+00] | [0.00000000e+00 7.08723416e-01 9.71019213e-01 6.48665345e-04 4.09438347e-01 1.09468057e-01 nan 3.05932982e-02 5.44133505e-02 0.00000000e+00 8.74063503e-01 0.00000000e+00 0.00000000e+00 nan 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00 8.66648886e-01 0.00000000e+00 1.61194155e-01 1.77691783e-02 0.00000000e+00 nan 0.00000000e+00 2.81195635e-02 0.00000000e+00 0.00000000e+00 9.17500033e-01 8.30294930e-01 9.02491399e-01 0.00000000e+00 0.00000000e+00 7.77243386e-03 0.00000000e+00] | 0 | | 0.8850 | 0.7741 | 0.2215 | 0.2711 | 0.7807 | [0. 0.56319416 0.79436978 0.22447649 0.37746306 0.2182132 nan 0.17433499 0.35240193 0. 0.64391654 0. 0. nan 0. 0. 0. 0. 0.61824159 0. 0.36925143 0.09610409 0. nan 0. 0.23049759 0. 0. 0.79662258 0.72121144 0.85940151 0. 0.00144295 0.04769959 0. ] | [0. 0.7334003 0.94650286 0.24751216 0.4478931 0.27208929 nan 0.22448353 0.45667969 0. 0.92555657 0. 0. nan 0. 0. 0. 0. 0.85871282 0. 0.43579563 0.09928831 0. nan 0. 0.25660062 0. 0. 0.93127726 0.85151776 0.9323404 0. 0.00144459 0.05442322 0. ] | 1 | ### Framework versions - Transformers 4.24.0 - TensorFlow 2.9.2 - Datasets 2.6.1 - Tokenizers 0.13.1