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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-finetuned-ve-Ub200
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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: validation
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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: 0.47058823529411764
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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-finetuned-ve-Ub200
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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: 1.5977
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- Accuracy: 0.4706
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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 | 0.92 | 6 | 7.9891 | 0.0980 |
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| No log | 2.0 | 13 | 7.4848 | 0.0980 |
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| No log | 2.92 | 19 | 6.2378 | 0.0980 |
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| No log | 4.0 | 26 | 4.8900 | 0.0980 |
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| No log | 4.92 | 32 | 3.8155 | 0.0980 |
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| No log | 6.0 | 39 | 2.7342 | 0.0980 |
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| No log | 6.92 | 45 | 2.0612 | 0.0980 |
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| No log | 8.0 | 52 | 1.5977 | 0.4706 |
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| No log | 8.92 | 58 | 1.3671 | 0.4706 |
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| No log | 10.0 | 65 | 1.2122 | 0.4706 |
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| No log | 10.92 | 71 | 1.1823 | 0.4706 |
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| No log | 12.0 | 78 | 1.1835 | 0.4706 |
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| No log | 12.92 | 84 | 1.1838 | 0.4706 |
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| No log | 14.0 | 91 | 1.1778 | 0.4706 |
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| No log | 14.92 | 97 | 1.1769 | 0.4706 |
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| 3.2267 | 16.0 | 104 | 1.1762 | 0.4706 |
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| 3.2267 | 16.92 | 110 | 1.1758 | 0.4706 |
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| 3.2267 | 18.0 | 117 | 1.1770 | 0.4706 |
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| 3.2267 | 18.46 | 120 | 1.1771 | 0.4706 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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