Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: vit-finetune-scrap
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# vit-finetune-scrap
+
+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.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.39.0
+- Pytorch 2.2.1
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "carton boxes",
+    "1": "old newspapers",
+    "10": "used juice box",
+    "11": "used plastic bottles labels",
+    "2": "old newspapers with plastic bottles and plastic garbage",
+    "3": "paper boxes and plastic trash bags",
+    "4": "paper waste",
+    "5": "plastic bottles",
+    "6": "plastic bottles and plastic bags with paper boxes",
+    "7": "plastic bottles and plastic garbage",
+    "8": "plastic garbage",
+    "9": "plastic garbage and paper garbage"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "carton boxes": "0",
+    "old newspapers": "1",
+    "old newspapers with plastic bottles and plastic garbage": "2",
+    "paper boxes and plastic trash bags": "3",
+    "paper waste": "4",
+    "plastic bottles": "5",
+    "plastic bottles and plastic bags with paper boxes": "6",
+    "plastic bottles and plastic garbage": "7",
+    "plastic garbage": "8",
+    "plastic garbage and paper garbage": "9",
+    "used juice box": "10",
+    "used plastic bottles labels": "11"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.0"
+}

model.safetensors

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+size 343254736

preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

runs/Mar21_23-36-23_X5C922065N/events.out.tfevents.1711060589.X5C922065N.86888.14

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+size 6018

training_args.bin

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