SoulPerforms commited on
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End of training

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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: 0.4625
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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: 1.5155
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- - Accuracy: 0.4625
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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: 8
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  - eval_batch_size: 16
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  - seed: 42
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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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- - num_epochs: 3
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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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- | No log | 1.0 | 80 | 1.7066 | 0.3625 |
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- | No log | 2.0 | 160 | 1.5551 | 0.4562 |
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- | No log | 3.0 | 240 | 1.5011 | 0.5062 |
 
 
 
 
 
 
 
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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: 0.525
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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: 1.3417
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+ - Accuracy: 0.525
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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: 42
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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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+ - num_epochs: 10
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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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+ | No log | 1.0 | 40 | 1.9000 | 0.2313 |
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+ | No log | 2.0 | 80 | 1.6538 | 0.3187 |
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+ | No log | 3.0 | 120 | 1.5717 | 0.4188 |
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+ | No log | 4.0 | 160 | 1.4244 | 0.525 |
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+ | No log | 5.0 | 200 | 1.3908 | 0.4875 |
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+ | No log | 6.0 | 240 | 1.3223 | 0.5437 |
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+ | No log | 7.0 | 280 | 1.3717 | 0.4938 |
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+ | No log | 8.0 | 320 | 1.3408 | 0.5 |
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+ | No log | 9.0 | 360 | 1.2935 | 0.5125 |
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+ | No log | 10.0 | 400 | 1.2982 | 0.5188 |
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  ### Framework versions
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