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--- |
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license: other |
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base_model: nvidia/mit-b0 |
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tags: |
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- image-segmentation |
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- vision |
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- generated_from_trainer |
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model-index: |
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- name: baseline_plantorgans_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# baseline_plantorgans_model |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the jpodivin/plantorgans dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5639 |
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- Mean Iou: 0.1095 |
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- Mean Accuracy: 0.1373 |
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- Overall Accuracy: 0.1858 |
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- Accuracy Void: nan |
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- Accuracy Fruit: 0.5208 |
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- Accuracy Leaf: 0.0197 |
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- Accuracy Flower: 0.0 |
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- Accuracy Stem: 0.0087 |
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- Iou Void: 0.0 |
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- Iou Fruit: 0.5192 |
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- Iou Leaf: 0.0197 |
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- Iou Flower: 0.0 |
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- Iou Stem: 0.0087 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3.0 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------:|:--------------:|:-------------:|:---------------:|:-------------:|:--------:|:---------:|:--------:|:----------:|:--------:| |
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| 0.8673 | 1.0 | 719 | 0.4827 | 0.1301 | 0.1639 | 0.2227 | nan | 0.6188 | 0.0271 | 0.0 | 0.0098 | 0.0 | 0.6135 | 0.0271 | 0.0 | 0.0098 | |
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| 0.4457 | 2.0 | 1438 | 0.5555 | 0.1130 | 0.1416 | 0.1927 | nan | 0.5224 | 0.0305 | 0.0 | 0.0135 | 0.0 | 0.5209 | 0.0305 | 0.0 | 0.0135 | |
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| 0.3272 | 3.0 | 2157 | 0.5639 | 0.1095 | 0.1373 | 0.1858 | nan | 0.5208 | 0.0197 | 0.0 | 0.0087 | 0.0 | 0.5192 | 0.0197 | 0.0 | 0.0087 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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