segformer-b0-finetuned-segments-pageboundet-finaltry
This model is a fine-tuned version of nvidia/mit-b0 on the vigneshgs7/Boundary_detection_onelasttry dataset. It achieves the following results on the evaluation set:
- Loss: 0.2569
- Mean Iou: nan
- Mean Accuracy: nan
- Overall Accuracy: nan
- Accuracy Object: nan
- Accuracy Surface: nan
- Iou Object: nan
- Iou Surface: nan
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: 2
- eval_batch_size: 2
- 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 Object | Accuracy Surface | Iou Object | Iou Surface |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4616 | 2.0 | 20 | 0.4828 | nan | nan | nan | nan | nan | nan | nan |
| 0.3359 | 4.0 | 40 | 0.3351 | nan | nan | nan | nan | nan | nan | nan |
| 0.2898 | 6.0 | 60 | 0.2885 | nan | nan | nan | nan | nan | nan | nan |
| 0.3041 | 8.0 | 80 | 0.2671 | nan | nan | nan | nan | nan | nan | nan |
| 0.2429 | 10.0 | 100 | 0.2569 | nan | nan | nan | nan | nan | nan | nan |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
nvidia/mit-b0