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README.md CHANGED
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  ---
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  base_model: d071696/vit-finetune-scrap
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  tags:
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- - image-classification
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- - image-feature-extraction
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- - image-to-text
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  - generated_from_trainer
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  datasets:
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- - arrow
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- metrics:
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- - accuracy
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  model-index:
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  - name: vit-finetune-scrap
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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: d071696/scraps1
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- type: arrow
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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: 0.9963782696177063
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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
@@ -32,10 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-finetune-scrap
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- This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the d071696/scraps1 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.0129
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- - Accuracy: 0.9964
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  ## Model description
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@@ -64,9 +43,6 @@ The following hyperparameters were used during training:
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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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- | 0.0035 | 3.22 | 1000 | 0.2143 | 0.9486 |
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  ### Framework versions
 
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  ---
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  base_model: d071696/vit-finetune-scrap
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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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  model-index:
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  - name: vit-finetune-scrap
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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
 
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  # vit-finetune-scrap
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+ This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the imagefolder dataset.
 
 
 
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  ## Model description
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  ### Training results
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  ### Framework versions
config.json CHANGED
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  "hidden_dropout_prob": 0.0,
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  "hidden_size": 768,
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  "id2label": {
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- "0": "aluminium",
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- "1": "batteries",
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- "10": "takeaway cups",
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- "2": "cardboard",
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- "3": "disposable plates",
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- "4": "glass",
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- "5": "hard plastic",
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- "6": "paper",
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- "7": "paper towel",
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- "8": "polystyrene",
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- "9": "soft plastics"
 
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  },
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  "image_size": 224,
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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- "aluminium": "0",
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- "batteries": "1",
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- "cardboard": "2",
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- "disposable plates": "3",
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- "glass": "4",
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- "hard plastic": "5",
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- "paper": "6",
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- "paper towel": "7",
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- "polystyrene": "8",
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- "soft plastics": "9",
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- "takeaway cups": "10"
 
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  },
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  "layer_norm_eps": 1e-12,
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  "model_type": "vit",
 
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  "hidden_dropout_prob": 0.0,
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  "hidden_size": 768,
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  "id2label": {
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+ "0": "carton boxes",
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+ "1": "old newspapers",
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+ "10": "used juice box",
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+ "11": "used plastic bottles labels",
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+ "2": "old newspapers with plastic bottles and plastic garbage",
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+ "3": "paper boxes and plastic trash bags",
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+ "4": "paper waste",
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+ "5": "plastic bottles",
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+ "6": "plastic bottles and plastic bags with paper boxes",
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+ "7": "plastic bottles and plastic garbage",
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+ "8": "plastic garbage",
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+ "9": "plastic garbage and paper garbage"
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  },
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  "image_size": 224,
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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  "label2id": {
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+ "carton boxes": "0",
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+ "old newspapers": "1",
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+ "old newspapers with plastic bottles and plastic garbage": "2",
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+ "paper boxes and plastic trash bags": "3",
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+ "paper waste": "4",
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+ "plastic bottles": "5",
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+ "plastic bottles and plastic bags with paper boxes": "6",
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+ "plastic bottles and plastic garbage": "7",
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+ "plastic garbage": "8",
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+ "plastic garbage and paper garbage": "9",
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+ "used juice box": "10",
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+ "used plastic bottles labels": "11"
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  },
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  "layer_norm_eps": 1e-12,
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  "model_type": "vit",
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