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: 0.6505
Validation Loss: 0.6601
Validation Mean Iou: 0.2774
Validation Mean Accuracy: 0.3400
Validation Overall Accuracy: 0.8158
Validation Per Category Iou: [0. 0.67274147 0.83098512 0.46721789 0.48492165 0.28810209 nan 0.30676731 0.41116935 0. 0.73679658 0.

           nan 0.         0.47421792 0.         0.

0.66232704 0. 0.40729478 0.27226345 0. nan 0. 0.22211219 0.00310618 0. 0.81170746 0.73786496 0.88368738 0. 0.07716099 0.12776685 0. ]

Validation Per Category Accuracy: [0. 0.80048159 0.93309497 0.558633 0.56439564 0.38053253 nan 0.46424754 0.60183499 0. 0.92479351 0.

           nan 0.         0.60493457 0.         0.

0.88399244 0. 0.55428873 0.34754253 0. nan 0. 0.25438648 0.00310618 0. 0.90931833 0.91190458 0.94609539 0. 0.08323588 0.15250888 0. ]

Epoch: 3

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
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.

           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 | | 0.7280 | 0.6948 | 0.2608 | 0.3178 | 0.8009 | [0. 0.5833859 0.81088427 0.37870695 0.42920979 0.26901769 nan 0.26967864 0.37309309 0. 0.73143999 0. 0. nan 0. 0.30875952 0. 0. 0.64460152 0. 0.36681761 0.20754432 0. nan 0. 0.27251923 0.01267829 0. 0.82057447 0.76705857 0.86538224 0. 0.13369659 0.09996937 0. ] | [0. 0.71016102 0.95278314 0.44786052 0.50520329 0.32109583 nan 0.37049571 0.63857903 0. 0.88589428 0. 0. nan 0. 0.34012586 0. 0. 0.88972948 0. 0.49551485 0.25354461 0. nan 0. 0.3309279 0.01267829 0. 0.93305477 0.86649237 0.94355496 0. 0.14937745 0.12218876 0. ] | 2 | | 0.6505 | 0.6601 | 0.2774 | 0.3400 | 0.8158 | [0. 0.67274147 0.83098512 0.46721789 0.48492165 0.28810209 nan 0.30676731 0.41116935 0. 0.73679658 0. 0. nan 0. 0.47421792 0. 0. 0.66232704 0. 0.40729478 0.27226345 0. nan 0. 0.22211219 0.00310618 0. 0.81170746 0.73786496 0.88368738 0. 0.07716099 0.12776685 0. ] | [0. 0.80048159 0.93309497 0.558633 0.56439564 0.38053253 nan 0.46424754 0.60183499 0. 0.92479351 0. 0. nan 0. 0.60493457 0. 0. 0.88399244 0. 0.55428873 0.34754253 0. nan 0. 0.25438648 0.00310618 0. 0.90931833 0.91190458 0.94609539 0. 0.08323588 0.15250888 0. ] | 3 |

Framework versions

Transformers 4.24.0
TensorFlow 2.9.2
Datasets 2.6.1
Tokenizers 0.13.1