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vit-base-patch16-224-newly-trained

Image Classification
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Safetensors
vit
Generated from Trainer
Eval Results (legacy)
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Files changed (7) hide show
  1. README.md +10 -10
  2. all_results.json +13 -0
  3. eval_results.json +8 -0
  4. model.safetensors +1 -1
  5. train_results.json +8 -0
  6. trainer_state.json +133 -0
  7. 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: 0.961
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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](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: 0.2294
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- - Accuracy: 0.961
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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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- | 2.1404 | 0.14 | 10 | 1.6121 | 0.629 |
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- | 1.3709 | 0.28 | 20 | 0.8628 | 0.882 |
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- | 0.8772 | 0.43 | 30 | 0.5010 | 0.933 |
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- | 0.6335 | 0.57 | 40 | 0.3399 | 0.941 |
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- | 0.5387 | 0.71 | 50 | 0.2673 | 0.957 |
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- | 0.4319 | 0.85 | 60 | 0.2386 | 0.958 |
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- | 0.4591 | 0.99 | 70 | 0.2294 | 0.961 |
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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: 0.964
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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: 0.1996
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+ - Accuracy: 0.964
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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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+ | 2.2183 | 0.14 | 10 | 1.6296 | 0.629 |
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+ | 1.4213 | 0.28 | 20 | 0.8637 | 0.899 |
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+ | 0.86 | 0.43 | 30 | 0.4598 | 0.949 |
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+ | 0.614 | 0.57 | 40 | 0.2998 | 0.96 |
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+ | 0.48 | 0.71 | 50 | 0.2337 | 0.967 |
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+ | 0.4123 | 0.85 | 60 | 0.2091 | 0.964 |
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+ | 0.4511 | 0.99 | 70 | 0.1996 | 0.964 |
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  ### Framework versions
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