Subhaaannn commited on
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End of training

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README.md CHANGED
@@ -3,11 +3,26 @@ license: apache-2.0
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
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  - name: image_classification
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -15,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # image_classification
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1721
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- - Accuracy: 0.9420
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  ## Model description
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@@ -37,21 +52,28 @@ 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: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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 | 52 | 0.2860 | 0.9179 |
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- | No log | 2.0 | 104 | 0.1864 | 0.9517 |
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- | No log | 3.0 | 156 | 0.1810 | 0.9565 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - imagefolder
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  metrics:
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  - accuracy
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  model-index:
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  - name: image_classification
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.575
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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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  # image_classification
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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: 1.4622
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+ - Accuracy: 0.575
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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: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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: 10
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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 | 1.5769 | 0.4625 |
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+ | No log | 2.0 | 80 | 1.5299 | 0.525 |
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+ | No log | 3.0 | 120 | 1.4961 | 0.55 |
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+ | No log | 4.0 | 160 | 1.5013 | 0.5188 |
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+ | No log | 5.0 | 200 | 1.4440 | 0.55 |
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+ | No log | 6.0 | 240 | 1.4333 | 0.5687 |
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+ | No log | 7.0 | 280 | 1.4314 | 0.5437 |
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+ | No log | 8.0 | 320 | 1.4307 | 0.5437 |
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+ | No log | 9.0 | 360 | 1.4264 | 0.5125 |
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+ | No log | 10.0 | 400 | 1.4369 | 0.525 |
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  ### Framework versions
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