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krishnachnani
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vit-base-beans

Image Classification
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vit
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  1. README.md +8 -10
  2. model.safetensors +1 -1
  3. runs/Apr03_23-33-41_4da9d9357a4f/events.out.tfevents.1712187225.4da9d9357a4f.2580.0 +2 -2
README.md CHANGED
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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:
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- - image-classification
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- - vision
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  - generated_from_trainer
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  datasets:
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  - imagefolder
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 1.0
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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
@@ -34,8 +32,8 @@ 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 the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6096
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- - Accuracy: 1.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 1 | 0.6096 | 1.0 |
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- | No log | 2.0 | 2 | 0.6162 | 1.0 |
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- | No log | 3.0 | 3 | 0.6205 | 1.0 |
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- | No log | 4.0 | 4 | 0.6236 | 1.0 |
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- | No log | 5.0 | 5 | 0.6252 | 1.0 |
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  ### Framework versions
 
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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:
 
 
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  - generated_from_trainer
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  datasets:
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  - imagefolder
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.640625
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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-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6651
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+ - Accuracy: 0.6406
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 2 | 0.6905 | 0.5625 |
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+ | No log | 2.0 | 4 | 0.6797 | 0.6562 |
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+ | No log | 3.0 | 6 | 0.6719 | 0.6562 |
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+ | No log | 4.0 | 8 | 0.6671 | 0.6562 |
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+ | 0.6483 | 5.0 | 10 | 0.6651 | 0.6406 |
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  ### Framework versions
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