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krishna-exe
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brain-tumor-classification

Image Classification
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swin
Generated from Trainer
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  1. README.md +14 -14
  2. model.safetensors +1 -1
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: 0.9651567944250871
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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: 0.1167
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- - Accuracy: 0.9652
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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 Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.0628 | 0.9877 | 40 | 0.1494 | 0.9512 |
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- | 0.0499 | 2.0 | 81 | 0.1830 | 0.9373 |
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- | 0.0697 | 2.9877 | 121 | 0.1094 | 0.9547 |
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- | 0.0646 | 4.0 | 162 | 0.1318 | 0.9582 |
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- | 0.0481 | 4.9383 | 200 | 0.1167 | 0.9652 |
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  ### Framework versions
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- - Transformers 4.44.2
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.0.1
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- - Tokenizers 0.19.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9372822299651568
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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: 0.1636
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+ - Accuracy: 0.9373
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.8509 | 0.9877 | 20 | 0.5305 | 0.8467 |
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+ | 0.4478 | 1.9753 | 40 | 0.3092 | 0.9094 |
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+ | 0.3313 | 2.9630 | 60 | 0.2422 | 0.9233 |
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+ | 0.2777 | 4.0 | 81 | 0.1716 | 0.9373 |
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+ | 0.2465 | 4.9383 | 100 | 0.1636 | 0.9373 |
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  ### Framework versions
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+ - Transformers 4.46.0.dev0
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  - Pytorch 2.4.1+cu121
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  - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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