metadata
license: mit
base_model: openmmlab/upernet-swin-small
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: upernet-swin-small-finetuned
results: []
upernet-swin-small-finetuned
This model is a fine-tuned version of openmmlab/upernet-swin-small on the jpodivin/plantorgans dataset. It achieves the following results on the evaluation set:
- Loss: 0.2914
- Mean Iou: 0.4182
- Mean Accuracy: 0.5282
- Overall Accuracy: 0.7341
- Accuracy Void: nan
- Accuracy Fruit: 0.8590
- Accuracy Leaf: 0.7032
- Accuracy Flower: 0.0
- Accuracy Stem: 0.5505
- Iou Void: 0.0
- Iou Fruit: 0.8554
- Iou Leaf: 0.6976
- Iou Flower: 0.0
- Iou Stem: 0.5381
- Median Iou: 0.5381
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: 0.0006
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Void | Accuracy Fruit | Accuracy Leaf | Accuracy Flower | Accuracy Stem | Iou Void | Iou Fruit | Iou Leaf | Iou Flower | Iou Stem | Median Iou |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.8566 | 1.0 | 575 | 0.3365 | 0.3723 | 0.4705 | 0.6560 | nan | 0.8000 | 0.6122 | 0.0 | 0.4699 | 0.0 | 0.7976 | 0.6041 | 0.0 | 0.4598 | 0.4598 |
| 0.3338 | 2.0 | 1150 | 0.3030 | 0.3922 | 0.4937 | 0.7155 | nan | 0.8558 | 0.7024 | 0.0 | 0.4166 | 0.0 | 0.8517 | 0.6972 | 0.0 | 0.4119 | 0.4119 |
| 0.3477 | 3.0 | 1725 | 0.2914 | 0.4182 | 0.5282 | 0.7341 | nan | 0.8590 | 0.7032 | 0.0 | 0.5505 | 0.0 | 0.8554 | 0.6976 | 0.0 | 0.5381 | 0.5381 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0