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---
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: 0.6320
- Validation Loss: 0.5173
- Validation Mean Iou: 0.2894
- Validation Mean Accuracy: 0.3454
- Validation Overall Accuracy: 0.8435
- Validation Per Category Iou: [0. 0.70789146 0.84902296 0.65266358 0.76099965 0.32934391
nan 0.29576422 0.43988204 0. 0.79276447 0.
0. 0. 0. 0.42668367 0. 0.
0.71717911 0. 0.32151249 0.50084444 0. nan
0. 0.18711455 0. 0. 0.82903803 0.68990498
0.8990059 0. 0.00213015 0.14819771 0. ]
- Validation Per Category Accuracy: [0. 0.84048763 0.93514369 0.68355212 0.88302113 0.458816
nan 0.38623272 0.69456442 0. 0.92379471 0.
0. 0. 0. 0.50677438 0. 0.
0.90362965 0. 0.4662386 0.57368294 0. nan
0. 0.23281768 0. 0. 0.9001526 0.86786434
0.95195314 0. 0.00333751 0.18532191 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 | 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 |
| 0.7134 | 0.5660 | 0.2780 | 0.3320 | 0.8286 | [0. 0.64791461 0.83800512 0.67301044 0.68120631 0.27361472
nan 0.26715802 0.43596999 0. 0.78649287 0.
0. 0. 0. 0.41256964 0. 0.
0.71114766 0. 0.31646321 0.44682442 0. nan
0. 0.17132551 0. 0. 0.81845697 0.67536699
0.88940936 0. 0. 0.1304862 0. ] | [0. 0.85958877 0.92084269 0.82341633 0.74725972 0.33495972
nan 0.40755277 0.56591531 0. 0.90641721 0.
0. 0. 0. 0.48144408 0. 0.
0.88294811 0. 0.46962078 0.47517397 0. nan
0. 0.20631607 0. 0. 0.90956851 0.85856042
0.94107052 0. 0. 0.16669713 0. ] | 2 |
| 0.6320 | 0.5173 | 0.2894 | 0.3454 | 0.8435 | [0. 0.70789146 0.84902296 0.65266358 0.76099965 0.32934391
nan 0.29576422 0.43988204 0. 0.79276447 0.
0. 0. 0. 0.42668367 0. 0.
0.71717911 0. 0.32151249 0.50084444 0. nan
0. 0.18711455 0. 0. 0.82903803 0.68990498
0.8990059 0. 0.00213015 0.14819771 0. ] | [0. 0.84048763 0.93514369 0.68355212 0.88302113 0.458816
nan 0.38623272 0.69456442 0. 0.92379471 0.
0. 0. 0. 0.50677438 0. 0.
0.90362965 0. 0.4662386 0.57368294 0. nan
0. 0.23281768 0. 0. 0.9001526 0.86786434
0.95195314 0. 0.00333751 0.18532191 0. ] | 3 |
### Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.0
- Tokenizers 0.13.2
|