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ongkn
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attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
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End of training

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  1. README.md +9 -14
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8177966101694916
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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
@@ -32,8 +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: 0.4652
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- - Accuracy: 0.8178
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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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- | 0.6272 | 1.5 | 25 | 0.5580 | 0.7013 |
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- | 0.4983 | 3.01 | 50 | 0.4751 | 0.7881 |
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- | 0.4137 | 4.51 | 75 | 0.5026 | 0.7733 |
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- | 0.3607 | 6.02 | 100 | 0.4532 | 0.7839 |
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- | 0.3154 | 7.52 | 125 | 0.4466 | 0.8157 |
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- | 0.3075 | 9.02 | 150 | 0.4491 | 0.8051 |
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- | 0.279 | 10.53 | 175 | 0.4388 | 0.8093 |
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- | 0.2509 | 12.03 | 200 | 0.4420 | 0.8326 |
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- | 0.2323 | 13.53 | 225 | 0.4474 | 0.8051 |
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- | 0.2148 | 15.04 | 250 | 0.4446 | 0.8242 |
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- | 0.2044 | 16.54 | 275 | 0.4652 | 0.8178 |
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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: 0.8072033898305084
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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: 0.5097
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+ - Accuracy: 0.8072
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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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+ | 0.4782 | 3.01 | 50 | 0.4715 | 0.7712 |
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+ | 0.3701 | 6.02 | 100 | 0.4314 | 0.8093 |
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+ | 0.2965 | 9.02 | 150 | 0.4668 | 0.7818 |
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+ | 0.2518 | 12.03 | 200 | 0.4341 | 0.8178 |
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+ | 0.2121 | 15.04 | 250 | 0.4847 | 0.8008 |
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+ | 0.1899 | 18.05 | 300 | 0.5097 | 0.8072 |
 
 
 
 
 
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  ### Framework versions
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