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---
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library_name: transformers
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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: swin-tiny-patch4-window7-224-finetuned-leukemia-08-2024.v1.1
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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: 0.8807511737089202
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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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# swin-tiny-patch4-window7-224-finetuned-leukemia-08-2024.v1.1
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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: 0.6068
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- Accuracy: 0.8808
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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: 10
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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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| 0.3578 | 0.9984 | 312 | 1.7841 | 0.4263 |
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| 0.2403 | 2.0 | 625 | 0.9414 | 0.6808 |
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| 0.1815 | 2.9984 | 937 | 0.6044 | 0.7784 |
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| 0.2062 | 4.0 | 1250 | 0.5284 | 0.7643 |
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| 0.1212 | 4.9984 | 1562 | 0.4432 | 0.8488 |
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| 0.0723 | 6.0 | 1875 | 0.8276 | 0.7925 |
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| 0.0656 | 6.9984 | 2187 | 0.3423 | 0.8958 |
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| 0.0419 | 8.0 | 2500 | 0.5879 | 0.8770 |
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| 0.0469 | 8.9984 | 2812 | 0.5126 | 0.8854 |
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| 0.0302 | 9.984 | 3120 | 0.6068 | 0.8808 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu118
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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