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Image Classification
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vit
Generated from Trainer
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End of training

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  1. README.md +19 -7
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
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: 0.00625
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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.1417
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- - Accuracy: 0.0063
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  ## Model description
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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: 3
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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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- | 1.6681 | 1.0 | 40 | 3.9658 | 0.0 |
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- | 0.939 | 2.0 | 80 | 4.1417 | 0.0063 |
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- | 0.575 | 3.0 | 120 | 4.1026 | 0.0063 |
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.0625
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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.5590
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+ - Accuracy: 0.0625
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  ## Model description
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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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+ | 1.6612 | 1.0 | 40 | 3.9513 | 0.0 |
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+ | 0.8129 | 2.0 | 80 | 3.9721 | 0.025 |
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+ | 0.3799 | 3.0 | 120 | 4.3376 | 0.0125 |
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+ | 0.0946 | 4.0 | 160 | 4.4142 | 0.0563 |
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+ | 0.019 | 5.0 | 200 | 4.5590 | 0.0625 |
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+ | 0.0062 | 6.0 | 240 | 4.9286 | 0.0437 |
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+ | 0.0039 | 7.0 | 280 | 5.0577 | 0.0437 |
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+ | 0.0028 | 8.0 | 320 | 5.1624 | 0.0437 |
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+ | 0.0024 | 9.0 | 360 | 5.2316 | 0.0437 |
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+ | 0.0023 | 10.0 | 400 | 5.2923 | 0.0437 |
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+ | 0.0019 | 11.0 | 440 | 5.3317 | 0.0375 |
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+ | 0.0017 | 12.0 | 480 | 5.3658 | 0.0375 |
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+ | 0.0016 | 13.0 | 520 | 5.3915 | 0.0375 |
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+ | 0.0016 | 14.0 | 560 | 5.4004 | 0.0375 |
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+ | 0.0016 | 15.0 | 600 | 5.4022 | 0.0375 |
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  ### Framework versions
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