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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: glacier_segmentation_transformer |
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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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# glacier_segmentation_transformer |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0450 |
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- Mean Iou: 0.9316 |
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- Mean Accuracy: 0.9624 |
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- Overall Accuracy: 0.9702 |
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- Per Category Iou: [0.9489463592815923, 0.8807403310059301, 0.9650686948898038] |
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- Per Category Accuracy: [0.9718627711935148, 0.9278884306932264, 0.987556935702318] |
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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: 0.00018 |
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- train_batch_size: 100 |
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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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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------:|:-----------------------------------------------------------:| |
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| 0.0933 | 1.0 | 1405 | 0.0450 | 0.9316 | 0.9624 | 0.9702 | [0.9489463592815923, 0.8807403310059301, 0.9650686948898038] | [0.9718627711935148, 0.9278884306932264, 0.987556935702318] | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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