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Chest_Xray

Image Classification
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vit
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  1. README.md +21 -10
  2. model.safetensors +1 -1
  3. runs/Mar01_05-24-16_1863594b9454/events.out.tfevents.1709270657.1863594b9454.4016.10 +2 -2
README.md CHANGED
@@ -17,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8203
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  - Accuracy: 0.0
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  ## Model description
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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: 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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.1804 | 1.0 | 1 | 0.5835 | 1.0 |
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- | 0.1783 | 2.0 | 2 | 0.6265 | 1.0 |
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- | 0.1681 | 3.0 | 3 | 0.7192 | 0.0 |
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- | 0.1621 | 4.0 | 4 | 0.8203 | 0.0 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9023
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  - Accuracy: 0.0
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.3519 | 1.0 | 1 | 0.6382 | 1.0 |
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+ | 0.3553 | 2.0 | 2 | 0.6606 | 1.0 |
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+ | 0.3529 | 3.0 | 3 | 0.6968 | 0.0 |
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+ | 0.3463 | 4.0 | 4 | 0.7017 | 0.0 |
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+ | 0.3303 | 5.0 | 5 | 0.7334 | 0.0 |
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+ | 0.3234 | 6.0 | 6 | 0.7407 | 0.0 |
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+ | 0.3224 | 7.0 | 7 | 0.7700 | 0.0 |
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+ | 0.3096 | 8.0 | 8 | 0.8130 | 0.0 |
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+ | 0.3094 | 9.0 | 9 | 0.8389 | 0.0 |
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+ | 0.3142 | 10.0 | 10 | 0.7915 | 0.0 |
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+ | 0.3154 | 11.0 | 11 | 0.7925 | 0.0 |
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+ | 0.28 | 12.0 | 12 | 0.8965 | 0.0 |
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+ | 0.2873 | 13.0 | 13 | 0.8330 | 0.0 |
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+ | 0.2671 | 14.0 | 14 | 0.9175 | 0.0 |
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+ | 0.2788 | 15.0 | 15 | 0.9023 | 0.0 |
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  ### Framework versions
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