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This model is a fine-tuned version of nvidia/mit-b5 on the mraottth/all_locations_pooled dataset. It achieves the following results on the evaluation set:
- Loss: 0.0189
- Mean Iou: 0.4050
- Mean Accuracy: 0.8101
- Overall Accuracy: 0.8101
- Accuracy Unlabeled: nan
- Accuracy Trash: 0.8101
- Iou Unlabeled: 0.0
- Iou Trash: 0.8101
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:
- learning_rate: 6e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Trash | Iou Unlabeled | Iou Trash |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.0592 | 1.0 | 90 | 0.0387 | 0.3723 | 0.7446 | 0.7446 | nan | 0.7446 | 0.0 | 0.7446 |
| 0.0402 | 2.0 | 180 | 0.0281 | 0.4123 | 0.8247 | 0.8247 | nan | 0.8247 | 0.0 | 0.8247 |
| 0.0209 | 3.0 | 270 | 0.0246 | 0.3691 | 0.7382 | 0.7382 | nan | 0.7382 | 0.0 | 0.7382 |
| 0.0117 | 4.0 | 360 | 0.0210 | 0.3882 | 0.7763 | 0.7763 | nan | 0.7763 | 0.0 | 0.7763 |
| 0.019 | 5.0 | 450 | 0.0198 | 0.3822 | 0.7644 | 0.7644 | nan | 0.7644 | 0.0 | 0.7644 |
| 0.0445 | 6.0 | 540 | 0.0199 | 0.3771 | 0.7542 | 0.7542 | nan | 0.7542 | 0.0 | 0.7542 |
| 0.0195 | 7.0 | 630 | 0.0191 | 0.4177 | 0.8354 | 0.8354 | nan | 0.8354 | 0.0 | 0.8354 |
| 0.008 | 8.0 | 720 | 0.0191 | 0.4060 | 0.8119 | 0.8119 | nan | 0.8119 | 0.0 | 0.8119 |
| 0.0268 | 9.0 | 810 | 0.0188 | 0.4083 | 0.8166 | 0.8166 | nan | 0.8166 | 0.0 | 0.8166 |
| 0.0061 | 10.0 | 900 | 0.0189 | 0.4050 | 0.8101 | 0.8101 | nan | 0.8101 | 0.0 | 0.8101 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
