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Image Classification
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vit
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Files changed (9) hide show
  1. README.md +8 -8
  2. all_results.json +9 -9
  3. eval_results.json +5 -5
  4. model.safetensors +1 -1
  5. runs/Dec15_02-37-22_d2a76fcee09b/events.out.tfevents.1702608328.d2a76fcee09b.2614.10 +3 -0
  6. runs/Dec15_02-45-48_d2a76fcee09b/events.out.tfevents.1702608352.d2a76fcee09b.2614.11 +3 -0
  7. train_results.json +4 -4
  8. trainer_state.json +111 -111
  9. 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: 0.9009259259259259
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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: 0.5926
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- - Accuracy: 0.9009
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  ## Model description
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@@ -52,7 +52,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 48
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  - eval_batch_size: 8
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  - seed: 42
@@ -65,10 +65,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.128 | 1.11 | 100 | 0.7718 | 0.8685 |
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- | 0.0236 | 2.22 | 200 | 0.6526 | 0.8852 |
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- | 0.004 | 3.33 | 300 | 0.5478 | 0.9009 |
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- | 0.0024 | 4.44 | 400 | 0.5926 | 0.9009 |
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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: 0.9111111111111111
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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: 0.5822
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+ - Accuracy: 0.9111
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 48
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.0006 | 1.11 | 100 | 0.6744 | 0.9 |
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+ | 0.0048 | 2.22 | 200 | 0.6603 | 0.8991 |
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+ | 0.0015 | 3.33 | 300 | 0.6312 | 0.9 |
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+ | 0.0015 | 4.44 | 400 | 0.5822 | 0.9111 |
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  ### Framework versions
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