metadata
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-docboundary-nov-13
results: []
segformer-b0-finetuned-segments-docboundary-nov-13
This model is a fine-tuned version of nvidia/mit-b0 on the vigneshgs7/doc-boundary dataset. It achieves the following results on the evaluation set:
- Loss: 0.2806
- Mean Iou: 0.4886
- Mean Accuracy: 0.9771
- Overall Accuracy: 0.9771
- Accuracy Page: nan
- Accuracy Surface: 0.9771
- Iou Page: 0.0
- Iou Surface: 0.9771
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 Page | Accuracy Surface | Iou Page | Iou Surface |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4191 | 2.22 | 20 | 0.5643 | 0.4651 | 0.9301 | 0.9301 | nan | 0.9301 | 0.0 | 0.9301 |
| 0.3141 | 4.44 | 40 | 0.3959 | 0.4866 | 0.9733 | 0.9733 | nan | 0.9733 | 0.0 | 0.9733 |
| 0.2865 | 6.67 | 60 | 0.2889 | 0.4870 | 0.9740 | 0.9740 | nan | 0.9740 | 0.0 | 0.9740 |
| 0.3955 | 8.89 | 80 | 0.2806 | 0.4886 | 0.9771 | 0.9771 | nan | 0.9771 | 0.0 | 0.9771 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1