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finetuned-bangladeshi-traditional-food

Image Classification
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TensorBoard
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vit
Generated from Trainer
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  1. README.md +7 -9
  2. model.safetensors +1 -1
  3. runs/Dec09_11-22-48_85cc5ef1c5bf/events.out.tfevents.1733743382.85cc5ef1c5bf.23.1 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -3,7 +3,6 @@ library_name: transformers
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  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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- - image-classification
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -17,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # finetuned-bangladeshi-traditional-food
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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 indian_food_images dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3590
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- - Accuracy: 0.9450
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  ## Model description
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@@ -45,17 +44,16 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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  - mixed_precision_training: Native AMP
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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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- | 1.1822 | 1.0 | 48 | 0.9452 | 0.8822 |
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- | 0.5747 | 2.0 | 96 | 0.5520 | 0.9110 |
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- | 0.3112 | 3.0 | 144 | 0.3952 | 0.9346 |
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- | 0.2416 | 4.0 | 192 | 0.3590 | 0.9450 |
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  ### Framework versions
 
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  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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  # finetuned-bangladeshi-traditional-food
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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: 0.2552
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+ - Accuracy: 0.9398
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  ## Model description
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 3
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  - mixed_precision_training: Native AMP
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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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+ | 0.1809 | 1.0 | 48 | 0.3544 | 0.9136 |
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+ | 0.0946 | 2.0 | 96 | 0.2911 | 0.9319 |
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+ | 0.0625 | 3.0 | 144 | 0.2552 | 0.9398 |
 
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  ### Framework versions
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