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krishna-exe
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brain-tumor-classification

Image Classification
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Safetensors
swin
Generated from Trainer
Eval Results (legacy)
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xet
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  1. README.md +14 -12
  2. runs/Oct10_11-22-23_e11ecca18f17/events.out.tfevents.1728559355.e11ecca18f17.609.2 +2 -2
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8685015290519877
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.3496
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- - Accuracy: 0.8685
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  ## Model description
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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: 3
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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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- | 0.5239 | 1.0 | 23 | 0.5283 | 0.7890 |
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- | 0.3716 | 2.0 | 46 | 0.3934 | 0.8410 |
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- | 0.2964 | 3.0 | 69 | 0.3496 | 0.8685 |
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9477351916376306
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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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  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: 0.1158
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+ - Accuracy: 0.9477
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  ## Model description
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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: 4
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+ - total_train_batch_size: 64
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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: 5
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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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+ | 0.5761 | 0.9877 | 40 | 0.4113 | 0.8432 |
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+ | 0.3871 | 2.0 | 81 | 0.2570 | 0.9024 |
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+ | 0.2586 | 2.9877 | 121 | 0.1910 | 0.9408 |
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+ | 0.2164 | 4.0 | 162 | 0.1312 | 0.9443 |
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+ | 0.1757 | 4.9383 | 200 | 0.1158 | 0.9477 |
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  ### Framework versions
runs/Oct10_11-22-23_e11ecca18f17/events.out.tfevents.1728559355.e11ecca18f17.609.2 CHANGED
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