metadata

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 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 1.5309
Validation Loss: 0.9380
Validation Mean Iou: 0.1674
Validation Mean Accuracy: 0.2153
Validation Overall Accuracy: 0.7545
Validation Per Category Iou: [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]
Validation Per Category Accuracy: [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]
Epoch: 0

Model description

More information needed

More information needed

More information needed

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

Train Loss	Validation Loss	Validation Mean Iou	Validation Mean Accuracy	Validation Overall Accuracy	Validation Per Category Iou
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