segformer-finetuned-sidewalk-10k-steps
This model is a fine-tuned version of nvidia/mit-b0 on the Manduzamzam/practice2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6829
- Mean Iou: 0.0140
- Mean Accuracy: 0.0279
- Overall Accuracy: 0.0279
- Accuracy Background: nan
- Accuracy Object: 0.0279
- Iou Background: 0.0
- Iou Object: 0.0279
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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Object | Iou Background | Iou Object |
|---|---|---|---|---|---|---|---|---|---|---|
| No log | 0.71 | 10 | 0.6829 | 0.0140 | 0.0279 | 0.0279 | nan | 0.0279 | 0.0 | 0.0279 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.14.5
- Tokenizers 0.14.0