DouglasBraga
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README.md
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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: swin-tiny-patch4-window7-224-finetuned-eurosat-leukemia-1000
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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: 0.885
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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-eurosat-leukemia-1000
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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: 0.3423
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- Accuracy: 0.885
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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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| 0.6899 | 0.9825 | 14 | 0.6198 | 0.6 |
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| 0.5494 | 1.9649 | 28 | 0.4008 | 0.805 |
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| 0.376 | 2.9474 | 42 | 0.4086 | 0.815 |
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| 0.2852 | 4.0 | 57 | 0.4454 | 0.81 |
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| 0.184 | 4.9825 | 71 | 0.8481 | 0.715 |
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| 0.183 | 5.9649 | 85 | 0.1870 | 0.94 |
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| 0.1465 | 6.9474 | 99 | 0.7121 | 0.8 |
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| 0.1319 | 8.0 | 114 | 0.2078 | 0.945 |
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| 0.1054 | 8.9825 | 128 | 0.3321 | 0.885 |
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| 0.096 | 9.8246 | 140 | 0.3423 | 0.885 |
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### Framework versions
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- Transformers 4.40.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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model.safetensors
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