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vit-base-beans-demo-v7

Image Classification
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  1. README.md +8 -9
  2. model.safetensors +1 -1
  3. runs/Jun10_21-44-02_39bec5d8a054/events.out.tfevents.1718055847.39bec5d8a054.1252.0 +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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  - generated_from_trainer
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  metrics:
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  - accuracy
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  # vit-base-beans-demo-v7
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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 beans dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0422
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- - Accuracy: 0.9925
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  ## Model description
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- Descripcion amplia....
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  ## Intended uses & limitations
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.0686 | 1.5385 | 100 | 0.0794 | 0.9850 |
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- | 0.0125 | 3.0769 | 200 | 0.0422 | 0.9925 |
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  ### Framework versions
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- - Transformers 4.41.0
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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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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  metrics:
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  - accuracy
 
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  # vit-base-beans-demo-v7
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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: 0.0571
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+ - Accuracy: 0.9850
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  ## Model description
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+ More information needed
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  ## Intended uses & limitations
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.0862 | 1.5385 | 100 | 0.0492 | 0.9925 |
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+ | 0.031 | 3.0769 | 200 | 0.0571 | 0.9850 |
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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  - Tokenizers 0.19.1
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