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--- |
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license: apache-2.0 |
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base_model: microsoft/swinv2-tiny-patch4-window8-256 |
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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: swinv2-tiny-patch4-window8-256-finetuned-gardner-exp-max |
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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: 0.8355704697986577 |
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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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# swinv2-tiny-patch4-window8-256-finetuned-gardner-exp-max |
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This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5500 |
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- Accuracy: 0.8356 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 15 |
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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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| 1.6043 | 0.97 | 14 | 1.5288 | 0.5415 | |
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| 1.4967 | 2.0 | 29 | 1.1719 | 0.5415 | |
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| 1.1276 | 2.97 | 43 | 1.0525 | 0.5463 | |
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| 1.0796 | 4.0 | 58 | 0.9086 | 0.6537 | |
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| 0.9387 | 4.97 | 72 | 0.8500 | 0.6439 | |
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| 0.9232 | 6.0 | 87 | 0.8190 | 0.6732 | |
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| 0.8456 | 6.97 | 101 | 0.8042 | 0.6878 | |
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| 0.8348 | 8.0 | 116 | 0.7770 | 0.6927 | |
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| 0.8057 | 8.97 | 130 | 0.7457 | 0.7073 | |
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| 0.8033 | 10.0 | 145 | 0.7353 | 0.7024 | |
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| 0.7822 | 10.97 | 159 | 0.7166 | 0.7122 | |
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| 0.7594 | 12.0 | 174 | 0.7188 | 0.7171 | |
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| 0.7777 | 12.97 | 188 | 0.7086 | 0.7171 | |
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| 0.7445 | 14.0 | 203 | 0.7139 | 0.6878 | |
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| 0.7513 | 14.48 | 210 | 0.7139 | 0.6878 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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