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ongkn
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attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +13 -15
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: 0.777292576419214
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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: 0.5360
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- - Accuracy: 0.7773
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 69
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5827 | 0.58 | 150 | 0.5508 | 0.7031 |
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- | 0.5214 | 1.16 | 300 | 0.5115 | 0.7598 |
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- | 0.4925 | 1.74 | 450 | 0.4870 | 0.7555 |
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- | 0.4148 | 2.33 | 600 | 0.4447 | 0.7948 |
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- | 0.4025 | 2.91 | 750 | 0.5507 | 0.7424 |
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- | 0.3627 | 3.49 | 900 | 0.4578 | 0.7904 |
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- | 0.3441 | 4.07 | 1050 | 0.4699 | 0.8188 |
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- | 0.3257 | 4.65 | 1200 | 0.4729 | 0.7817 |
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- | 0.2488 | 5.23 | 1350 | 0.4971 | 0.7817 |
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- | 0.3127 | 5.81 | 1500 | 0.5360 | 0.7773 |
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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: 0.8209606986899564
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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: 0.4646
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+ - Accuracy: 0.8210
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 69
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4933 | 1.16 | 150 | 0.5369 | 0.7183 |
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+ | 0.445 | 2.33 | 300 | 0.4573 | 0.7860 |
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+ | 0.3926 | 3.49 | 450 | 0.4551 | 0.7751 |
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+ | 0.2821 | 4.65 | 600 | 0.5172 | 0.7795 |
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+ | 0.2778 | 5.81 | 750 | 0.4400 | 0.7991 |
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+ | 0.2352 | 6.98 | 900 | 0.4533 | 0.8057 |
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+ | 0.2244 | 8.14 | 1050 | 0.4721 | 0.8079 |
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+ | 0.1838 | 9.3 | 1200 | 0.4646 | 0.8210 |
 
 
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  ### Framework versions