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afraid15chicken
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finetuned-arsenic

Image Classification
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vit
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  1. README.md +24 -24
  2. model.safetensors +1 -1
  3. runs/Oct07_16-01-53_efd0d9aa04b4/events.out.tfevents.1728316916.efd0d9aa04b4.3229.0 +3 -0
  4. training_args.bin +1 -1
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: 0.9993451211525868
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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-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: 0.0026
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- - Accuracy: 0.9993
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  ## Model description
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@@ -66,27 +66,27 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.2214 | 0.1848 | 100 | 0.2314 | 0.9247 |
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- | 0.2189 | 0.3697 | 200 | 0.1578 | 0.9404 |
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- | 0.2104 | 0.5545 | 300 | 0.1063 | 0.9673 |
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- | 0.2138 | 0.7394 | 400 | 0.0998 | 0.9718 |
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- | 0.2149 | 0.9242 | 500 | 0.0644 | 0.9790 |
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- | 0.1439 | 1.1091 | 600 | 0.0757 | 0.9646 |
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- | 0.1038 | 1.2939 | 700 | 0.1316 | 0.9574 |
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- | 0.0458 | 1.4787 | 800 | 0.0282 | 0.9902 |
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- | 0.0078 | 1.6636 | 900 | 0.1226 | 0.9718 |
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- | 0.0286 | 1.8484 | 1000 | 0.0584 | 0.9856 |
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- | 0.0493 | 2.0333 | 1100 | 0.1419 | 0.9633 |
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- | 0.0028 | 2.2181 | 1200 | 0.0232 | 0.9948 |
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- | 0.0292 | 2.4030 | 1300 | 0.0171 | 0.9935 |
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- | 0.0402 | 2.5878 | 1400 | 0.0061 | 0.9987 |
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- | 0.043 | 2.7726 | 1500 | 0.0497 | 0.9889 |
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- | 0.0224 | 2.9575 | 1600 | 0.0062 | 0.9987 |
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- | 0.0021 | 3.1423 | 1700 | 0.0092 | 0.9974 |
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- | 0.0025 | 3.3272 | 1800 | 0.0041 | 0.9987 |
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- | 0.0018 | 3.5120 | 1900 | 0.0054 | 0.9974 |
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- | 0.0034 | 3.6969 | 2000 | 0.0052 | 0.9980 |
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- | 0.0072 | 3.8817 | 2100 | 0.0026 | 0.9993 |
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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: 0.9986902423051736
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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: 0.0066
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+ - Accuracy: 0.9987
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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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+ | 0.1855 | 0.1848 | 100 | 0.1918 | 0.9312 |
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+ | 0.1792 | 0.3697 | 200 | 0.1740 | 0.9365 |
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+ | 0.1688 | 0.5545 | 300 | 0.0782 | 0.9692 |
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+ | 0.1238 | 0.7394 | 400 | 0.2158 | 0.9227 |
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+ | 0.0969 | 0.9242 | 500 | 0.0449 | 0.9843 |
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+ | 0.0326 | 1.1091 | 600 | 0.1554 | 0.9574 |
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+ | 0.1057 | 1.2939 | 700 | 0.0845 | 0.9738 |
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+ | 0.0805 | 1.4787 | 800 | 0.0712 | 0.9823 |
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+ | 0.0889 | 1.6636 | 900 | 0.0718 | 0.9797 |
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+ | 0.0503 | 1.8484 | 1000 | 0.0251 | 0.9935 |
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+ | 0.0225 | 2.0333 | 1100 | 0.0177 | 0.9967 |
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+ | 0.0049 | 2.2181 | 1200 | 0.0246 | 0.9921 |
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+ | 0.0152 | 2.4030 | 1300 | 0.0083 | 0.9987 |
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+ | 0.08 | 2.5878 | 1400 | 0.0214 | 0.9941 |
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+ | 0.0043 | 2.7726 | 1500 | 0.0069 | 0.9980 |
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+ | 0.0501 | 2.9575 | 1600 | 0.0151 | 0.9967 |
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+ | 0.0186 | 3.1423 | 1700 | 0.0078 | 0.9974 |
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+ | 0.0033 | 3.3272 | 1800 | 0.0139 | 0.9961 |
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+ | 0.0023 | 3.5120 | 1900 | 0.0076 | 0.9987 |
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+ | 0.0054 | 3.6969 | 2000 | 0.0048 | 0.9993 |
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+ | 0.0168 | 3.8817 | 2100 | 0.0066 | 0.9987 |
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  ### Framework versions
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