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--- |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: segformer-class-classWeights-augmentation |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8620689655172413 |
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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-class-classWeights-augmentation |
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4872 |
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- Accuracy: 0.8621 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 1 | 1.1700 | 0.2759 | |
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| No log | 2.0 | 3 | 1.0351 | 0.3793 | |
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| No log | 3.0 | 5 | 0.9731 | 0.5172 | |
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| No log | 4.0 | 6 | 0.9362 | 0.5172 | |
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| No log | 5.0 | 7 | 0.8890 | 0.5517 | |
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| No log | 6.0 | 9 | 0.7596 | 0.7586 | |
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| 0.5024 | 7.0 | 11 | 0.6531 | 0.8621 | |
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| 0.5024 | 8.0 | 12 | 0.6170 | 0.8621 | |
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| 0.5024 | 9.0 | 13 | 0.5878 | 0.8966 | |
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| 0.5024 | 10.0 | 15 | 0.5418 | 0.8621 | |
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| 0.5024 | 11.0 | 17 | 0.5122 | 0.8621 | |
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| 0.5024 | 12.0 | 18 | 0.5021 | 0.8621 | |
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| 0.5024 | 13.0 | 19 | 0.4928 | 0.8621 | |
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| 0.3117 | 13.33 | 20 | 0.4872 | 0.8621 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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