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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: 0.9655172413793104 |
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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: 0.0355 |
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- Accuracy: 0.9655 |
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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: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 40 |
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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 | 0.89 | 6 | 1.0977 | 0.5517 | |
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| 1.0215 | 1.93 | 13 | 0.6858 | 0.7931 | |
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| 0.6364 | 2.96 | 20 | 0.9383 | 0.6897 | |
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| 0.6364 | 4.0 | 27 | 0.2391 | 0.9310 | |
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| 0.2716 | 4.89 | 33 | 0.1767 | 0.8966 | |
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| 0.2295 | 5.93 | 40 | 0.2729 | 0.9310 | |
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| 0.2295 | 6.96 | 47 | 0.1429 | 0.9655 | |
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| 0.1311 | 8.0 | 54 | 0.1929 | 0.9655 | |
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| 0.1503 | 8.89 | 60 | 0.1718 | 0.9655 | |
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| 0.1503 | 9.93 | 67 | 0.1631 | 0.9655 | |
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| 0.1554 | 10.96 | 74 | 0.2690 | 0.9655 | |
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| 0.1157 | 12.0 | 81 | 0.1331 | 0.9655 | |
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| 0.1157 | 12.89 | 87 | 0.0512 | 0.9655 | |
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| 0.1093 | 13.93 | 94 | 0.0273 | 1.0 | |
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| 0.134 | 14.96 | 101 | 0.0356 | 0.9655 | |
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| 0.134 | 16.0 | 108 | 0.0477 | 0.9655 | |
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| 0.0926 | 16.89 | 114 | 0.0381 | 0.9655 | |
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| 0.1363 | 17.78 | 120 | 0.0355 | 0.9655 | |
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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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