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End of training

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  1. README.md +16 -9
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  license: apache-2.0
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- base_model: microsoft/resnet-50
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7061855670103093
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Cheese_xray
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- This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the chest-xray-classification dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4278
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- - Accuracy: 0.7062
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  ## Model description
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@@ -61,15 +61,22 @@ The following hyperparameters were used during training:
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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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- | 0.5547 | 0.99 | 63 | 0.5554 | 0.7062 |
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- | 0.4303 | 1.99 | 127 | 0.4387 | 0.7079 |
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- | 0.4377 | 2.96 | 189 | 0.4278 | 0.7062 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: barghavani/Cheese_xray
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8883161512027491
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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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  # Cheese_xray
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+ This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on the chest-xray-classification dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2827
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+ - Accuracy: 0.8883
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  ## Model description
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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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+ | 0.3993 | 0.99 | 63 | 0.4364 | 0.7165 |
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+ | 0.3454 | 1.99 | 127 | 0.3947 | 0.7680 |
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+ | 0.3327 | 3.0 | 191 | 0.3582 | 0.8591 |
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+ | 0.3329 | 4.0 | 255 | 0.3371 | 0.8746 |
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+ | 0.2992 | 4.99 | 318 | 0.3449 | 0.8643 |
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+ | 0.3289 | 5.99 | 382 | 0.3172 | 0.8832 |
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+ | 0.3309 | 7.0 | 446 | 0.2956 | 0.8935 |
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+ | 0.2875 | 8.0 | 510 | 0.2911 | 0.8883 |
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+ | 0.2764 | 8.99 | 573 | 0.2884 | 0.9124 |
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+ | 0.265 | 9.88 | 630 | 0.2827 | 0.8883 |
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  ### Framework versions
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