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tsec_vit_model

Image Classification
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vit
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  1. README.md +16 -31
  2. model.safetensors +1 -1
README.md CHANGED
@@ -3,26 +3,11 @@ 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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  - accuracy
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  model-index:
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  - name: tsec_vit_model
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- results:
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- - task:
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- name: Image Classification
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- type: image-classification
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- dataset:
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- name: imagefolder
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- type: imagefolder
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- config: default
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- split: train
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- args: default
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.7689873417721519
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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 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # tsec_vit_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: 0.4821
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- - Accuracy: 0.7690
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  ## Model description
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@@ -65,18 +50,18 @@ 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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- | 0.4963 | 0.9873 | 39 | 0.5699 | 0.6725 |
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- | 0.4959 | 2.0 | 79 | 0.5485 | 0.7152 |
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- | 0.4879 | 2.9873 | 118 | 0.4886 | 0.7690 |
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- | 0.5243 | 4.0 | 158 | 0.5133 | 0.7468 |
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- | 0.4654 | 4.9873 | 197 | 0.4927 | 0.7516 |
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- | 0.4776 | 6.0 | 237 | 0.4901 | 0.7642 |
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- | 0.4767 | 6.9873 | 276 | 0.4652 | 0.7816 |
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- | 0.4465 | 8.0 | 316 | 0.4795 | 0.7642 |
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- | 0.467 | 8.9873 | 355 | 0.4691 | 0.7484 |
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- | 0.4121 | 9.8734 | 390 | 0.4821 | 0.7690 |
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  ### Framework versions
 
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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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  model-index:
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  - name: tsec_vit_model
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  # tsec_vit_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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2717
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+ - Accuracy: 0.8866
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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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+ | 0.4387 | 1.0 | 280 | 0.4179 | 0.8151 |
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+ | 0.4239 | 2.0 | 560 | 0.3611 | 0.8399 |
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+ | 0.3148 | 3.0 | 840 | 0.3156 | 0.8600 |
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+ | 0.2988 | 4.0 | 1120 | 0.3002 | 0.8729 |
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+ | 0.2498 | 5.0 | 1400 | 0.3087 | 0.8694 |
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+ | 0.3028 | 6.0 | 1680 | 0.2966 | 0.8716 |
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+ | 0.2179 | 7.0 | 1960 | 0.2742 | 0.8808 |
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+ | 0.2274 | 8.0 | 2240 | 0.2861 | 0.8814 |
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+ | 0.2195 | 9.0 | 2520 | 0.2626 | 0.8895 |
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+ | 0.1886 | 10.0 | 2800 | 0.2717 | 0.8866 |
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  ### Framework versions
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