End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-fruit-classifier
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9698795180722891
+---
+
+<!-- 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-fruit-classifier
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.0194
+- Accuracy: 0.9699
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.668         | 2.38  | 100  | 2.0731          | 0.9217   |
+| 1.6565        | 4.76  | 200  | 1.4216          | 0.9518   |
+| 1.1627        | 7.14  | 300  | 1.1256          | 0.9578   |
+| 0.9571        | 9.52  | 400  | 1.0224          | 0.9639   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- 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": "acerolas",
+    "1": "apples",
+    "10": "figs",
+    "11": "grapefruits",
+    "12": "grapes",
+    "13": "guava",
+    "14": "kiwifruit",
+    "15": "lemons",
+    "16": "limes",
+    "17": "mangos",
+    "18": "olives",
+    "19": "oranges",
+    "2": "apricots",
+    "20": "passionfruit",
+    "21": "peaches",
+    "22": "pears",
+    "23": "pineapples",
+    "24": "plums",
+    "25": "pomegranates",
+    "26": "raspberries",
+    "27": "strawberries",
+    "28": "tomatoes",
+    "29": "watermelons",
+    "3": "avocados",
+    "4": "bananas",
+    "5": "blackberries",
+    "6": "blueberries",
+    "7": "cantaloupes",
+    "8": "cherries",
+    "9": "coconuts"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "acerolas": "0",
+    "apples": "1",
+    "apricots": "2",
+    "avocados": "3",
+    "bananas": "4",
+    "blackberries": "5",
+    "blueberries": "6",
+    "cantaloupes": "7",
+    "cherries": "8",
+    "coconuts": "9",
+    "figs": "10",
+    "grapefruits": "11",
+    "grapes": "12",
+    "guava": "13",
+    "kiwifruit": "14",
+    "lemons": "15",
+    "limes": "16",
+    "mangos": "17",
+    "olives": "18",
+    "oranges": "19",
+    "passionfruit": "20",
+    "peaches": "21",
+    "pears": "22",
+    "pineapples": "23",
+    "plums": "24",
+    "pomegranates": "25",
+    "raspberries": "26",
+    "strawberries": "27",
+    "tomatoes": "28",
+    "watermelons": "29"
+  },
+  "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": "4.38.2"
+}

model.safetensors

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preprocessor_config.json

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+{
+  "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
+  }
+}

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