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CIDAUTv2

Image Classification
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End of training

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  1. README.md +14 -9
  2. model.safetensors +1 -1
  3. runs/Nov07_16-52-38_62e4925951f1/events.out.tfevents.1730998360.62e4925951f1.77.0 +2 -2
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: 0.6527777777777778
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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 [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6279
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- - Accuracy: 0.6528
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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: 5
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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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- | No log | 1.0 | 4 | 0.8011 | 0.5741 |
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- | No log | 2.0 | 8 | 0.6474 | 0.6759 |
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- | 0.7485 | 3.0 | 12 | 0.6923 | 0.5463 |
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- | 0.7485 | 4.0 | 16 | 0.6292 | 0.6713 |
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- | 0.6057 | 5.0 | 20 | 0.6279 | 0.6528 |
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.75
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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 [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5012
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+ - Accuracy: 0.75
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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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+ | No log | 1.0 | 4 | 0.7104 | 0.5139 |
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+ | No log | 2.0 | 8 | 0.6436 | 0.6065 |
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+ | 0.685 | 3.0 | 12 | 0.6004 | 0.6944 |
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+ | 0.685 | 4.0 | 16 | 0.5978 | 0.6759 |
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+ | 0.5422 | 5.0 | 20 | 0.5582 | 0.7222 |
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+ | 0.5422 | 6.0 | 24 | 0.5222 | 0.7361 |
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+ | 0.5422 | 7.0 | 28 | 0.5060 | 0.7222 |
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+ | 0.4521 | 8.0 | 32 | 0.4957 | 0.7269 |
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+ | 0.4521 | 9.0 | 36 | 0.4781 | 0.75 |
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+ | 0.3741 | 10.0 | 40 | 0.5012 | 0.75 |
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  ### Framework versions
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