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finetuned-breast_cancer_images

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vit
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update model card README.md

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@@ -16,10 +16,8 @@ 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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- - Train Accuracy: 0.8288
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- - Train Loss: 0.0140
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- - Accuracy: 0.8797
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- - Loss: 0.0111
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  ## Model description
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@@ -44,28 +42,54 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Accuracy | Loss | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
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- | No log | 0.25 | 10 | 0.6456 | 0.0227 | 0.0208 |
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- | No log | 0.25 | 10 | 0.6456 | 0.0227 | 0.0208 |
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- | No log | 0.5 | 20 | 0.7563 | 0.0203 | 0.0193 |
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- | No log | 0.5 | 20 | 0.7563 | 0.0203 | 0.0193 |
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- | No log | 0.75 | 30 | 0.6994 | 0.0191 | 0.0168 |
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- | No log | 0.75 | 30 | 0.6994 | 0.0191 | 0.0168 |
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- | No log | 1.0 | 40 | 0.7595 | 0.0185 | 0.0166 |
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- | No log | 1.0 | 40 | 0.7595 | 0.0185 | 0.0166 |
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- | No log | 1.25 | 50 | 0.8797 | 0.0156 | 0.0121 |
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- | No log | 1.25 | 50 | 0.8797 | 0.0156 | 0.0121 |
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- | No log | 1.5 | 60 | 0.8639 | 0.0152 | 0.0114 |
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- | No log | 1.5 | 60 | 0.8639 | 0.0152 | 0.0114 |
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- | No log | 1.75 | 70 | 0.8671 | 0.0150 | 0.0115 |
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- | No log | 1.75 | 70 | 0.8671 | 0.0150 | 0.0115 |
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- | No log | 2.0 | 80 | 0.8797 | 0.0140 | 0.0111 |
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- | No log | 2.0 | 80 | 0.8797 | 0.0140 | 0.0111 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.2529
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+ - Accuracy: 0.9525
 
 
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  ## Model description
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  - seed: 42
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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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+ - num_epochs: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Accuracy | Loss | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
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+ | No log | 2.5 | 100 | 0.8924 | 0.0151 | 0.0105 |
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+ | No log | 2.5 | 100 | 0.8924 | 0.0151 | 0.0105 |
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+ | No log | 5.0 | 200 | 0.8481 | 0.0156 | 0.0130 |
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+ | No log | 5.0 | 200 | 0.8481 | 0.0156 | 0.0130 |
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+ | No log | 7.5 | 300 | 0.8892 | 0.0137 | 0.0103 |
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+ | No log | 7.5 | 300 | 0.8892 | 0.0137 | 0.0103 |
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+ | No log | 10.0 | 400 | 0.9051 | 0.0130 | 0.0089 |
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+ | No log | 10.0 | 400 | 0.9051 | 0.0130 | 0.0089 |
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+ | No log | 12.5 | 500 | 0.9051 | 0.0117 | 0.0088 |
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+ | No log | 12.5 | 500 | 0.9051 | 0.0117 | 0.0088 |
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+ | No log | 15.0 | 600 | 0.8956 | 0.0127 | 0.0117 |
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+ | No log | 15.0 | 600 | 0.8956 | 0.0127 | 0.0117 |
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+ | No log | 17.5 | 700 | 0.9241 | 0.0100 | 0.0082 |
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+ | No log | 17.5 | 700 | 0.9241 | 0.0100 | 0.0082 |
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+ | No log | 20.0 | 800 | 0.9367 | 0.0103 | 0.0073 |
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+ | No log | 20.0 | 800 | 0.9367 | 0.0103 | 0.0073 |
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+ | No log | 22.5 | 900 | 0.9209 | 0.0106 | 0.0079 |
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+ | No log | 22.5 | 900 | 0.9209 | 0.0106 | 0.0079 |
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+ | No log | 25.0 | 1000 | 0.9367 | 0.0095 | 0.0067 |
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+ | No log | 25.0 | 1000 | 0.9367 | 0.0095 | 0.0067 |
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+ | No log | 25.0 | 1000 | 0.2138 | 0.9367 |
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+ | No log | 27.5 | 1100 | 0.9494 | 0.0081 | 0.0069 |
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+ | No log | 27.5 | 1100 | 0.9494 | 0.0081 | 0.0069 |
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+ | No log | 30.0 | 1200 | 0.9494 | 0.0089 | 0.0077 |
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+ | No log | 30.0 | 1200 | 0.9494 | 0.0089 | 0.0077 |
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+ | No log | 32.5 | 1300 | 0.9430 | 0.0078 | 0.0074 |
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+ | No log | 32.5 | 1300 | 0.9430 | 0.0078 | 0.0074 |
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+ | No log | 35.0 | 1400 | 0.9462 | 0.0087 | 0.0086 |
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+ | No log | 35.0 | 1400 | 0.9462 | 0.0087 | 0.0086 |
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+ | No log | 37.5 | 1500 | 0.9430 | 0.0080 | 0.0084 |
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+ | No log | 37.5 | 1500 | 0.9430 | 0.0080 | 0.0084 |
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+ | No log | 40.0 | 1600 | 0.9494 | 0.0082 | 0.0070 |
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+ | No log | 40.0 | 1600 | 0.9494 | 0.0082 | 0.0070 |
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+ | No log | 42.5 | 1700 | 0.9399 | 0.0076 | 0.0091 |
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+ | No log | 42.5 | 1700 | 0.9399 | 0.0076 | 0.0091 |
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+ | No log | 45.0 | 1800 | 0.9462 | 0.0077 | 0.0095 |
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+ | No log | 45.0 | 1800 | 0.9462 | 0.0077 | 0.0095 |
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+ | No log | 47.5 | 1900 | 0.9525 | 0.0065 | 0.0080 |
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+ | No log | 47.5 | 1900 | 0.9525 | 0.0065 | 0.0080 |
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+ | No log | 50.0 | 2000 | 0.9525 | 0.0060 | 0.0079 |
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+ | No log | 50.0 | 2000 | 0.9525 | 0.0060 | 0.0079 |
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+ | No log | 50.0 | 2000 | 0.2529 | 0.9525 |
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  ### Framework versions