metadata
license: mit
base_model: openmmlab/upernet-swin-small
tags:
- generated_from_trainer
model-index:
- name: upernet-swin-small-finetuned
results: []
datasets:
- jpodivin/plantorgans
upernet-swin-small-finetuned
This model is a fine-tuned version of openmmlab/upernet-swin-small on an jpodivin/plantorgans. It achieves the following results on the evaluation set:
- Loss: 0.2923
- Mean Iou: 0.4108
- Mean Accuracy: 0.5178
- Overall Accuracy: 0.7337
- Accuracy Void: nan
- Accuracy Fruit: 0.8691
- Accuracy Leaf: 0.7085
- Accuracy Flower: 0.0
- Accuracy Stem: 0.4937
- Iou Void: 0.0
- Iou Fruit: 0.8653
- Iou Leaf: 0.7034
- Iou Flower: 0.0
- Iou Stem: 0.4855
- Median Iou: 0.4855
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2456 | 1.0 | 460 | 0.3706 | 0.4121 | 0.5223 | 0.7804 | nan | 0.8522 | 0.8235 | 0.0 | 0.4134 | 0.0 | 0.8452 | 0.8099 | 0.0 | 0.4053 | 0.4053 |
| 0.246 | 2.0 | 920 | 0.3135 | 0.3821 | 0.4813 | 0.6912 | nan | 0.8038 | 0.6825 | 0.0 | 0.4388 | 0.0 | 0.8016 | 0.6772 | 0.0 | 0.4319 | 0.4319 |
| 0.3118 | 3.0 | 1380 | 0.2923 | 0.4108 | 0.5178 | 0.7337 | nan | 0.8691 | 0.7085 | 0.0 | 0.4937 | 0.0 | 0.8653 | 0.7034 | 0.0 | 0.4855 | 0.4855 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0