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--- |
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library_name: transformers |
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license: other |
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base_model: nvidia/mit-b0 |
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tags: |
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- vision |
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- image-segmentation |
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- generated_from_trainer |
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model-index: |
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- name: mit-b0_whitefly |
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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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# mit-b0_whitefly |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2644 |
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- Mean Iou: 0.4948 |
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- Mean Accuracy: 0.4968 |
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- Overall Accuracy: 0.9893 |
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- Accuracy Background: 0.9907 |
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- Accuracy Whitefly: 0.0029 |
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- Iou Background: 0.9893 |
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- Iou Whitefly: 0.0004 |
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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: 6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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_ratio: 0.05 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Whitefly | Iou Background | Iou Whitefly | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-----------------:|:--------------:|:------------:| |
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| 0.6275 | 0.4 | 20 | 0.6849 | 0.3529 | 0.4550 | 0.7049 | 0.7056 | 0.2044 | 0.7048 | 0.0010 | |
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| 0.4423 | 0.8 | 40 | 0.5826 | 0.4745 | 0.5157 | 0.9468 | 0.9480 | 0.0834 | 0.9468 | 0.0022 | |
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| 0.3793 | 1.2 | 60 | 0.4444 | 0.4868 | 0.4927 | 0.9731 | 0.9744 | 0.0110 | 0.9731 | 0.0006 | |
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| 0.3102 | 1.6 | 80 | 0.3347 | 0.4976 | 0.4986 | 0.9949 | 0.9963 | 0.0009 | 0.9949 | 0.0002 | |
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| 0.272 | 2.0 | 100 | 0.3100 | 0.4983 | 0.4991 | 0.9963 | 0.9977 | 0.0004 | 0.9963 | 0.0002 | |
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| 0.3003 | 2.4 | 120 | 0.2579 | 0.4983 | 0.4991 | 0.9965 | 0.9979 | 0.0003 | 0.9965 | 0.0001 | |
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| 0.2558 | 2.8 | 140 | 0.2644 | 0.4948 | 0.4968 | 0.9893 | 0.9907 | 0.0029 | 0.9893 | 0.0004 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.6.0+cpu |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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