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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: segformer-b5-finetuned-ce-head-batch2 |
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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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# segformer-b5-finetuned-ce-head-batch2 |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0575 |
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- Mean Iou: 0.7701 |
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- Mean Accuracy: 0.8473 |
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- Overall Accuracy: 0.9774 |
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- Accuracy Bg: 0.9891 |
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- Accuracy Head: 0.7054 |
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- Iou Bg: 0.9768 |
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- Iou Head: 0.5634 |
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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: 3e-05 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Bg | Accuracy Head | Iou Bg | Iou Head | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------:|:-------------:|:------:|:--------:| |
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| 0.0192 | 2.9412 | 100 | 0.0164 | 0.8513 | 0.9095 | 0.9934 | 0.9968 | 0.8221 | 0.9933 | 0.7094 | |
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| 0.0071 | 5.8824 | 200 | 0.0197 | 0.8495 | 0.8819 | 0.9933 | 0.9982 | 0.7656 | 0.9932 | 0.7058 | |
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| 0.0345 | 8.8235 | 300 | 0.0154 | 0.8745 | 0.9312 | 0.9940 | 0.9968 | 0.8657 | 0.9939 | 0.7551 | |
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| 0.0056 | 11.7647 | 400 | 0.0158 | 0.8668 | 0.9375 | 0.9937 | 0.9961 | 0.8789 | 0.9936 | 0.7401 | |
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| 0.0217 | 14.7059 | 500 | 0.0149 | 0.8736 | 0.9306 | 0.9936 | 0.9966 | 0.8646 | 0.9934 | 0.7538 | |
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| 0.0924 | 17.6471 | 600 | 0.0133 | 0.8738 | 0.9438 | 0.9943 | 0.9963 | 0.8913 | 0.9942 | 0.7534 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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