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Larbz-7
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vit-xray-pneumonia-classification

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End of training

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  1. README.md +10 -20
  2. model.safetensors +1 -1
  3. runs/May02_01-04-09_feaf4e2f980d/events.out.tfevents.1714611854.feaf4e2f980d.396.0 +2 -2
README.md CHANGED
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- base_model: google/vit-base-patch16-224-in21k
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  metrics:
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  - accuracy
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  model-index:
@@ -17,8 +17,8 @@ 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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- - Loss: 0.0771
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- - Accuracy: 0.9734
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  ## Model description
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@@ -51,23 +51,13 @@ The following hyperparameters were used during training:
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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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- | 0.4723 | 0.9882 | 63 | 0.2182 | 0.9313 |
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- | 0.2004 | 1.9922 | 127 | 0.1308 | 0.9545 |
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- | 0.1669 | 2.9961 | 191 | 0.1130 | 0.9622 |
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- | 0.127 | 4.0 | 255 | 0.1188 | 0.9562 |
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- | 0.1381 | 4.9882 | 318 | 0.1452 | 0.9468 |
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- | 0.1195 | 5.9922 | 382 | 0.0966 | 0.9648 |
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- | 0.1121 | 6.9961 | 446 | 0.0933 | 0.9665 |
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- | 0.0985 | 8.0 | 510 | 0.0900 | 0.9657 |
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- | 0.0915 | 8.9882 | 573 | 0.0980 | 0.9665 |
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- | 0.078 | 9.9922 | 637 | 0.0858 | 0.9725 |
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- | 0.0812 | 10.9961 | 701 | 0.0964 | 0.9682 |
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- | 0.0806 | 12.0 | 765 | 0.0820 | 0.9682 |
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- | 0.0754 | 12.9882 | 828 | 0.0924 | 0.9674 |
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- | 0.06 | 13.9922 | 892 | 0.0822 | 0.9734 |
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- | 0.0685 | 14.8235 | 945 | 0.0771 | 0.9734 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
5
  - generated_from_trainer
 
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  metrics:
7
  - accuracy
8
  model-index:
 
17
 
18
  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: 0.1602
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+ - Accuracy: 0.9313
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  ## Model description
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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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+ | 0.4638 | 0.9882 | 63 | 0.2024 | 0.9236 |
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+ | 0.1987 | 1.9922 | 127 | 0.1342 | 0.9588 |
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+ | 0.1637 | 2.9961 | 191 | 0.1534 | 0.9442 |
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+ | 0.16 | 4.0 | 255 | 0.1365 | 0.9485 |
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+ | 0.1344 | 4.9882 | 318 | 0.1602 | 0.9313 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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