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  1. README.md +7 -15
  2. model.safetensors +1 -1
  3. runs/Dec28_04-03-25_08b39d765768/events.out.tfevents.1703736208.08b39d765768.16933.3 +2 -2
  4. runs/Dec28_04-09-49_08b39d765768/events.out.tfevents.1703736595.08b39d765768.16933.4 +3 -0
  5. training_args.bin +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: 0.785
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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: 0.9604
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- - Accuracy: 0.785
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0002
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- - train_batch_size: 48
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  - eval_batch_size: 8
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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: 5
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  - mixed_precision_training: Native AMP
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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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- | 0.8634 | 0.55 | 100 | 0.9266 | 0.6975 |
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- | 0.3225 | 1.09 | 200 | 0.8994 | 0.7325 |
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- | 0.2353 | 1.64 | 300 | 0.9683 | 0.73 |
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- | 0.1119 | 2.19 | 400 | 0.9247 | 0.7492 |
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- | 0.049 | 2.73 | 500 | 0.9663 | 0.7567 |
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- | 0.0537 | 3.28 | 600 | 1.0558 | 0.7567 |
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- | 0.0274 | 3.83 | 700 | 1.0344 | 0.7692 |
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- | 0.0102 | 4.37 | 800 | 0.9259 | 0.7942 |
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- | 0.0095 | 4.92 | 900 | 0.9604 | 0.785 |
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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: 0.7716666666666666
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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: 1.1645
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+ - Accuracy: 0.7717
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 16
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  - eval_batch_size: 8
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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: 1
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  - mixed_precision_training: Native AMP
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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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+ | 0.0072 | 0.91 | 500 | 1.1645 | 0.7717 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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