---
license: other
tags:
- generated_from_keras_callback
model-index:
- name: sayakpaul/mit-b0-finetuned-sidewalks
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# 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: 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

## 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     |


### Framework versions

- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.6.1
- Tokenizers 0.13.1