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theofilusarifin
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image_classification

Image Classification
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Safetensors
vit
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End of training

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Files changed (4) hide show
  1. README.md +9 -7
  2. model.safetensors +1 -1
  3. runs/Feb16_20-43-46_f7d6dbdd4b89/events.out.tfevents.1708116227.f7d6dbdd4b89.728.0 +2 -2
  4. runs/Feb16_20-43-46_f7d6dbdd4b89/events.out.tfevents.1708123668.f7d6dbdd4b89.728.1 +3 -0
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: 0.3875
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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 [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: 1.7459
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- - Accuracy: 0.3875
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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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- | No log | 1.0 | 40 | 1.9270 | 0.2562 |
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- | No log | 2.0 | 80 | 1.7317 | 0.3688 |
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- | No log | 3.0 | 120 | 1.6761 | 0.3625 |
 
 
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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: 0.36875
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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: 1.5867
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+ - Accuracy: 0.3688
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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: 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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+ | No log | 1.0 | 40 | 1.8864 | 0.225 |
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+ | No log | 2.0 | 80 | 1.6548 | 0.3125 |
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+ | No log | 3.0 | 120 | 1.5627 | 0.4188 |
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+ | No log | 4.0 | 160 | 1.5115 | 0.4125 |
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+ | No log | 5.0 | 200 | 1.4971 | 0.3875 |
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  ### Framework versions
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