---
license: other
tags:
- generated_from_keras_callback
model-index:
- name: nateraw/mit-b0-finetuned-sidewalks-v2
  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. -->

# nateraw/mit-b0-finetuned-sidewalks-v2

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: 0.8462
- Validation Loss: 0.6135
- Validation Mean Iou: 0.2551
- Validation Mean Accuracy: 0.2960
- Validation Overall Accuracy: 0.8200
- Validation Per Category Iou: [0.         0.66967645 0.80571406 0.56416239 0.66692248 0.24744912
        nan 0.23994505 0.28962463 0.         0.76504783 0.
 0.         0.         0.         0.14111353 0.         0.
 0.6924468  0.         0.27988701 0.41876094 0.                nan
 0.         0.14755829 0.         0.         0.81614463 0.68429711
 0.87710938 0.         0.         0.11234171 0.        ]
- Validation Per Category Accuracy: [0.         0.83805933 0.94928385 0.59586511 0.72913519 0.30595504
        nan 0.3128234  0.34805831 0.         0.87847495 0.
 0.         0.         0.         0.14205167 0.         0.
 0.87543619 0.         0.36001144 0.49498574 0.                nan
 0.         0.18179115 0.         0.         0.92867923 0.7496178
 0.92220166 0.         0.         0.15398549 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 |
|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----:|
| 1.4089     | 0.8220          | 0.1975              | 0.2427                   | 0.7701                      | [0.         0.58353931 0.7655921  0.04209491 0.53135026 0.11779776
        nan 0.07709853 0.15950712 0.         0.69634813 0.
 0.         0.         0.         0.         0.         0.
 0.61456822 0.         0.24971248 0.27129675 0.                nan
 0.         0.07697324 0.         0.         0.78576516 0.61267064
 0.84564576 0.         0.         0.08904216 0.        ] | [0.         0.88026971 0.93475302 0.04216372 0.5484085  0.13285614
        nan 0.08669707 0.19044773 0.         0.90089024 0.
 0.         0.         0.         0.         0.         0.
 0.76783975 0.         0.42102101 0.28659817 0.                nan
 0.         0.08671771 0.         0.         0.89590301 0.74932576
 0.9434814  0.         0.         0.14245566 0.        ] | 0     |
| 0.8462     | 0.6135          | 0.2551              | 0.2960                   | 0.8200                      | [0.         0.66967645 0.80571406 0.56416239 0.66692248 0.24744912
        nan 0.23994505 0.28962463 0.         0.76504783 0.
 0.         0.         0.         0.14111353 0.         0.
 0.6924468  0.         0.27988701 0.41876094 0.                nan
 0.         0.14755829 0.         0.         0.81614463 0.68429711
 0.87710938 0.         0.         0.11234171 0.        ] | [0.         0.83805933 0.94928385 0.59586511 0.72913519 0.30595504
        nan 0.3128234  0.34805831 0.         0.87847495 0.
 0.         0.         0.         0.14205167 0.         0.
 0.87543619 0.         0.36001144 0.49498574 0.                nan
 0.         0.18179115 0.         0.         0.92867923 0.7496178
 0.92220166 0.         0.         0.15398549 0.        ]  | 1     |


### Framework versions

- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.0
- Tokenizers 0.13.2