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Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold2

Image Classification
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beit
Generated from Trainer
Eval Results
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End of training

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  1. README.md +27 -17
  2. model.safetensors +1 -1
  3. 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: 0.6521621621621622
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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 [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6935
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- - Accuracy: 0.6522
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  ## Model description
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@@ -52,29 +52,39 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-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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  - lr_scheduler_warmup_ratio: 0.1
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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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- | 1.2092 | 1.0 | 923 | 1.1486 | 0.6143 |
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- | 0.9013 | 2.0 | 1846 | 1.0409 | 0.6454 |
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- | 0.7034 | 3.0 | 2769 | 1.0086 | 0.6586 |
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- | 0.4555 | 4.0 | 3692 | 1.0728 | 0.6608 |
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- | 0.3588 | 5.0 | 4615 | 1.2071 | 0.65 |
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- | 0.238 | 6.0 | 5538 | 1.3226 | 0.6538 |
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- | 0.1299 | 7.0 | 6461 | 1.4741 | 0.6530 |
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- | 0.1362 | 8.0 | 7384 | 1.5820 | 0.6565 |
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- | 0.0943 | 9.0 | 8307 | 1.6687 | 0.6503 |
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- | 0.1229 | 10.0 | 9230 | 1.6935 | 0.6522 |
 
 
 
 
 
 
 
 
 
 
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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: 0.6437837837837838
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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 [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.1168
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+ - Accuracy: 0.6438
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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: 0.0001
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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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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+ | 1.0678 | 1.0 | 923 | 1.1860 | 0.5962 |
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+ | 0.9795 | 2.0 | 1846 | 1.0466 | 0.6414 |
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+ | 0.6213 | 3.0 | 2769 | 1.0577 | 0.6403 |
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+ | 0.3941 | 4.0 | 3692 | 1.2437 | 0.6424 |
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+ | 0.3011 | 5.0 | 4615 | 1.4589 | 0.6443 |
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+ | 0.1999 | 6.0 | 5538 | 1.7644 | 0.63 |
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+ | 0.039 | 7.0 | 6461 | 1.9747 | 0.64 |
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+ | 0.0664 | 8.0 | 7384 | 2.2470 | 0.6368 |
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+ | 0.0635 | 9.0 | 8307 | 2.4483 | 0.6451 |
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+ | 0.0688 | 10.0 | 9230 | 2.6192 | 0.6516 |
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+ | 0.0389 | 11.0 | 10153 | 2.7333 | 0.6470 |
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+ | 0.0075 | 12.0 | 11076 | 2.8548 | 0.6446 |
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+ | 0.0085 | 13.0 | 11999 | 2.9858 | 0.6416 |
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+ | 0.0018 | 14.0 | 12922 | 2.9790 | 0.6424 |
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+ | 0.0034 | 15.0 | 13845 | 3.0326 | 0.6443 |
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+ | 0.009 | 16.0 | 14768 | 3.0570 | 0.6473 |
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+ | 0.0005 | 17.0 | 15691 | 3.1227 | 0.6419 |
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+ | 0.0 | 18.0 | 16614 | 3.1155 | 0.6449 |
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+ | 0.0002 | 19.0 | 17537 | 3.1130 | 0.6454 |
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+ | 0.0002 | 20.0 | 18460 | 3.1168 | 0.6438 |
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  ### Framework versions
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