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Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold1

Image Classification
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beit
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Eval Results
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End of training

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  1. README.md +13 -13
  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: 0.6576160738528374
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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: 1.6677
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- - Accuracy: 0.6576
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.0818 | 1.0 | 924 | 1.0982 | 0.6288 |
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- | 0.953 | 2.0 | 1848 | 1.0920 | 0.6253 |
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- | 0.7864 | 3.0 | 2772 | 0.9856 | 0.6690 |
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- | 0.4622 | 4.0 | 3696 | 1.0683 | 0.6630 |
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- | 0.4803 | 5.0 | 4620 | 1.2094 | 0.6606 |
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- | 0.2207 | 6.0 | 5544 | 1.3429 | 0.6516 |
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- | 0.1535 | 7.0 | 6468 | 1.4692 | 0.6511 |
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- | 0.1284 | 8.0 | 7392 | 1.5894 | 0.6541 |
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- | 0.1152 | 9.0 | 8316 | 1.6418 | 0.6644 |
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- | 0.1009 | 10.0 | 9240 | 1.6677 | 0.6576 |
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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: 0.6581591094216671
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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: 1.6175
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+ - Accuracy: 0.6582
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.0967 | 1.0 | 924 | 1.1282 | 0.6305 |
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+ | 0.9514 | 2.0 | 1848 | 1.0677 | 0.6335 |
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+ | 0.8134 | 3.0 | 2772 | 0.9657 | 0.6761 |
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+ | 0.5172 | 4.0 | 3696 | 1.0638 | 0.6641 |
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+ | 0.4644 | 5.0 | 4620 | 1.1745 | 0.6655 |
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+ | 0.3079 | 6.0 | 5544 | 1.2914 | 0.6601 |
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+ | 0.1569 | 7.0 | 6468 | 1.4210 | 0.6636 |
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+ | 0.1324 | 8.0 | 7392 | 1.5083 | 0.6603 |
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+ | 0.0833 | 9.0 | 8316 | 1.5875 | 0.6644 |
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+ | 0.1019 | 10.0 | 9240 | 1.6175 | 0.6582 |
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  ### Framework versions
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