syaha commited on
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End of training

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README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.525
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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
@@ -33,8 +33,8 @@ 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: 1.4214
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- - Accuracy: 0.525
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  ## Model description
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@@ -58,28 +58,28 @@ The following hyperparameters were used during training:
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  - eval_batch_size: 32
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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: 15
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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 | 20 | 1.9534 | 0.325 |
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- | No log | 2.0 | 40 | 1.7394 | 0.425 |
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- | No log | 3.0 | 60 | 1.5766 | 0.5 |
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- | No log | 4.0 | 80 | 1.5163 | 0.475 |
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- | No log | 5.0 | 100 | 1.4214 | 0.525 |
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- | No log | 6.0 | 120 | 1.4110 | 0.4938 |
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- | No log | 7.0 | 140 | 1.3743 | 0.4813 |
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- | No log | 8.0 | 160 | 1.3190 | 0.5125 |
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- | No log | 9.0 | 180 | 1.3015 | 0.5125 |
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- | No log | 10.0 | 200 | 1.3349 | 0.475 |
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- | No log | 11.0 | 220 | 1.3449 | 0.4875 |
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- | No log | 12.0 | 240 | 1.3229 | 0.5188 |
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- | No log | 13.0 | 260 | 1.3345 | 0.5062 |
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- | No log | 14.0 | 280 | 1.3379 | 0.5125 |
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- | No log | 15.0 | 300 | 1.3352 | 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: 0.55625
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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: 1.2851
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+ - Accuracy: 0.5563
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  ## Model description
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  - eval_batch_size: 32
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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: cosine
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  - num_epochs: 15
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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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+ | 1.9706 | 1.0 | 20 | 1.9258 | 0.35 |
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+ | 1.672 | 2.0 | 40 | 1.7025 | 0.4625 |
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+ | 1.4489 | 3.0 | 60 | 1.5581 | 0.4313 |
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+ | 1.2031 | 4.0 | 80 | 1.4534 | 0.5 |
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+ | 0.9503 | 5.0 | 100 | 1.3794 | 0.5 |
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+ | 0.758 | 6.0 | 120 | 1.3283 | 0.5312 |
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+ | 0.6021 | 7.0 | 140 | 1.3007 | 0.5125 |
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+ | 0.4784 | 8.0 | 160 | 1.2851 | 0.5563 |
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+ | 0.3682 | 9.0 | 180 | 1.2815 | 0.525 |
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+ | 0.3117 | 10.0 | 200 | 1.3074 | 0.5125 |
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+ | 0.2753 | 11.0 | 220 | 1.2945 | 0.525 |
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+ | 0.2585 | 12.0 | 240 | 1.2903 | 0.5375 |
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+ | 0.2483 | 13.0 | 260 | 1.2903 | 0.5437 |
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+ | 0.245 | 14.0 | 280 | 1.2927 | 0.5375 |
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+ | 0.2459 | 15.0 | 300 | 1.2925 | 0.5375 |
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  ### Framework versions
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