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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: earthquake
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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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# earthquake
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the gokceKy/earthquake dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6395
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- Mean Iou: 0.1763
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- Mean Accuracy: 0.4255
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- Overall Accuracy: 0.6211
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- Accuracy Background: nan
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- Accuracy Car: nan
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- Accuracy Earthquake-roads: 0.4591
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- Accuracy Other: 0.8175
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- Accuracy Road: 0.0
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- Accuracy Road-cracks: nan
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- Accuracy Sky: nan
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- Accuracy Wall: nan
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- Iou Background: 0.0
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- Iou Car: 0.0
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- Iou Earthquake-roads: 0.4499
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- Iou Other: 0.7841
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- Iou Road: 0.0
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- Iou Road-cracks: 0.0
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- Iou Sky: 0.0
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- Iou Wall: nan
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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: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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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 Car | Accuracy Earthquake-roads | Accuracy Other | Accuracy Road | Accuracy Road-cracks | Accuracy Sky | Accuracy Wall | Iou Background | Iou Car | Iou Earthquake-roads | Iou Other | Iou Road | Iou Road-cracks | Iou Sky | Iou Wall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------:|:-------------------------:|:--------------:|:-------------:|:--------------------:|:------------:|:-------------:|:--------------:|:-------:|:--------------------:|:---------:|:--------:|:---------------:|:-------:|:--------:|
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| 1.0736 | 2.5 | 5 | 1.6917 | 0.1818 | 0.3763 | 0.5984 | nan | nan | 0.3113 | 0.8176 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.3077 | 0.7830 | 0.0 | 0.0 | nan | nan |
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| 0.8949 | 5.0 | 10 | 1.6395 | 0.1763 | 0.4255 | 0.6211 | nan | nan | 0.4591 | 0.8175 | 0.0 | nan | nan | nan | 0.0 | 0.0 | 0.4499 | 0.7841 | 0.0 | 0.0 | 0.0 | nan |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.4.1+cpu
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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