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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-Diabetic-Retinopathy
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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: 0.8090909090909091
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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-Diabetic-Retinopathy
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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: 0.5203
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- Accuracy: 0.8091
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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: 40
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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 | 5 | 1.6054 | 0.4909 |
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| 1.6039 | 2.0 | 10 | 1.5774 | 0.4909 |
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| 1.6039 | 3.0 | 15 | 1.4627 | 0.4909 |
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| 1.4766 | 4.0 | 20 | 1.3211 | 0.4909 |
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| 1.4766 | 5.0 | 25 | 1.2294 | 0.4909 |
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| 1.2308 | 6.0 | 30 | 1.0657 | 0.4909 |
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| 1.2308 | 7.0 | 35 | 0.9504 | 0.6545 |
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| 1.017 | 8.0 | 40 | 0.8463 | 0.7364 |
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| 1.017 | 9.0 | 45 | 0.7463 | 0.7455 |
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| 0.8345 | 10.0 | 50 | 0.6948 | 0.7455 |
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| 0.8345 | 11.0 | 55 | 0.6460 | 0.7545 |
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| 0.7594 | 12.0 | 60 | 0.6403 | 0.7545 |
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| 0.7594 | 13.0 | 65 | 0.6319 | 0.7545 |
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| 0.7228 | 14.0 | 70 | 0.5999 | 0.7455 |
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| 0.7228 | 15.0 | 75 | 0.5922 | 0.7545 |
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| 0.6851 | 16.0 | 80 | 0.5955 | 0.7636 |
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| 0.6851 | 17.0 | 85 | 0.5731 | 0.7545 |
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| 0.6549 | 18.0 | 90 | 0.5603 | 0.7818 |
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| 0.6549 | 19.0 | 95 | 0.5386 | 0.7818 |
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| 0.643 | 20.0 | 100 | 0.5424 | 0.7727 |
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| 0.643 | 21.0 | 105 | 0.5295 | 0.7909 |
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| 0.5951 | 22.0 | 110 | 0.5203 | 0.8091 |
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| 0.5951 | 23.0 | 115 | 0.5162 | 0.7909 |
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| 0.5913 | 24.0 | 120 | 0.5095 | 0.7818 |
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| 0.5913 | 25.0 | 125 | 0.5140 | 0.7909 |
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| 0.5462 | 26.0 | 130 | 0.5167 | 0.7636 |
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| 0.5462 | 27.0 | 135 | 0.4943 | 0.7909 |
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| 0.5538 | 28.0 | 140 | 0.4844 | 0.7636 |
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| 0.5538 | 29.0 | 145 | 0.4821 | 0.7727 |
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| 0.5497 | 30.0 | 150 | 0.4952 | 0.7727 |
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| 0.5497 | 31.0 | 155 | 0.4995 | 0.7818 |
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| 0.4923 | 32.0 | 160 | 0.4910 | 0.7727 |
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| 0.4923 | 33.0 | 165 | 0.5029 | 0.7818 |
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| 0.5228 | 34.0 | 170 | 0.5083 | 0.7818 |
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| 0.5228 | 35.0 | 175 | 0.4984 | 0.7909 |
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| 0.4986 | 36.0 | 180 | 0.4914 | 0.7909 |
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| 0.4986 | 37.0 | 185 | 0.4926 | 0.7909 |
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| 0.5154 | 38.0 | 190 | 0.4915 | 0.8 |
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| 0.5154 | 39.0 | 195 | 0.4886 | 0.8 |
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| 0.5081 | 40.0 | 200 | 0.4875 | 0.8 |
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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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