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End of training

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  1. README.md +11 -11
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  ---
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- license: other
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- base_model: apple/mobilevit-small
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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: 0.5693311582381729
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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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  # ARSL_letters_model
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- This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.7064
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- - Accuracy: 0.5693
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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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- | 3.2199 | 0.9902 | 76 | 3.1533 | 0.3613 |
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- | 2.9611 | 1.9935 | 153 | 2.8133 | 0.5473 |
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- | 2.8481 | 2.9707 | 228 | 2.7064 | 0.5693 |
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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:
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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: 0.7803571428571429
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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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  # ARSL_letters_model
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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: 2.3695
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+ - Accuracy: 0.7804
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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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+ | 3.0992 | 1.0 | 35 | 2.9555 | 0.5036 |
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+ | 2.5809 | 2.0 | 70 | 2.5300 | 0.7054 |
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+ | 2.357 | 3.0 | 105 | 2.3695 | 0.7804 |
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  ### Framework versions