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End of training

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  1. README.md +7 -10
  2. model.safetensors +1 -1
  3. runs/Nov12_19-19-49_DESKTOP-4PF3H2T/events.out.tfevents.1699798790.DESKTOP-4PF3H2T.10564.0 +2 -2
  4. runs/Nov12_19-19-49_DESKTOP-4PF3H2T/events.out.tfevents.1699799040.DESKTOP-4PF3H2T.10564.1 +3 -0
README.md CHANGED
@@ -17,8 +17,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0422
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- - Accuracy: 0.9833
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  ## Model description
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@@ -41,22 +41,19 @@ The following hyperparameters were used during training:
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 1337
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 64
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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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- - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 5
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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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- | 0.0941 | 1.0 | 106 | 0.0764 | 0.9708 |
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- | 0.0769 | 2.0 | 212 | 0.0707 | 0.9733 |
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- | 0.0505 | 2.99 | 318 | 0.0718 | 0.9675 |
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- | 0.0314 | 4.0 | 425 | 0.0494 | 0.9817 |
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- | 0.0274 | 4.99 | 530 | 0.0514 | 0.9817 |
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  ### Framework versions
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0043
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+ - Accuracy: 1.0
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  ## Model description
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 1337
 
 
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.0047 | 1.0 | 50 | 0.0043 | 1.0 |
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+ | 0.0027 | 2.0 | 100 | 0.0026 | 1.0 |
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+ | 0.0019 | 3.0 | 150 | 0.0019 | 1.0 |
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+ | 0.0016 | 4.0 | 200 | 0.0016 | 1.0 |
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+ | 0.0015 | 5.0 | 250 | 0.0015 | 1.0 |
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  ### Framework versions
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