Segformer
This model is a fine-tuned version of nvidia/mit-b0 on the saad7489/SixKnifesorted dataset. It achieves the following results on the evaluation set:
- Loss: 0.9362
- Mean Iou: 0.4332
- Mean Accuracy: 0.9383
- Overall Accuracy: 0.9270
- Accuracy Bkg: 0.9259
- Accuracy Knife: 0.9508
- Accuracy Gun: nan
- Iou Bkg: 0.9237
- Iou Knife: 0.3758
- Iou Gun: 0.0
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:
- learning_rate: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- 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 Bkg | Accuracy Knife | Accuracy Gun | Iou Bkg | Iou Knife | Iou Gun |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.8846 | 6.6667 | 20 | 0.9362 | 0.4332 | 0.9383 | 0.9270 | 0.9259 | 0.9508 | nan | 0.9237 | 0.3758 | 0.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for saad7489/Segformer
Base model
nvidia/mit-b0