Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: finetuned-indian-food
+  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. -->
+
+# finetuned-indian-food
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.0027
+- Accuracy: 0.9996
+
+## 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: 0.0002
+- train_batch_size: 16
+- 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
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7056        | 0.1   | 100  | 0.5113          | 0.8881   |
+| 0.3027        | 0.21  | 200  | 0.1280          | 0.9796   |
+| 0.2823        | 0.31  | 300  | 0.1580          | 0.9656   |
+| 0.3273        | 0.42  | 400  | 0.0879          | 0.9837   |
+| 0.1808        | 0.52  | 500  | 0.0812          | 0.9822   |
+| 0.2101        | 0.63  | 600  | 0.0339          | 0.9937   |
+| 0.1495        | 0.73  | 700  | 0.0568          | 0.9833   |
+| 0.1296        | 0.84  | 800  | 0.0629          | 0.9844   |
+| 0.1462        | 0.94  | 900  | 0.0886          | 0.9733   |
+| 0.0519        | 1.04  | 1000 | 0.0544          | 0.9870   |
+| 0.3192        | 1.15  | 1100 | 0.0892          | 0.9726   |
+| 0.158         | 1.25  | 1200 | 0.0632          | 0.98     |
+| 0.0266        | 1.36  | 1300 | 0.0233          | 0.9944   |
+| 0.1832        | 1.46  | 1400 | 0.0292          | 0.9930   |
+| 0.1212        | 1.57  | 1500 | 0.0489          | 0.9852   |
+| 0.0994        | 1.67  | 1600 | 0.0142          | 0.9974   |
+| 0.0219        | 1.78  | 1700 | 0.0277          | 0.9930   |
+| 0.0664        | 1.88  | 1800 | 0.0158          | 0.9974   |
+| 0.0834        | 1.99  | 1900 | 0.0124          | 0.9978   |
+| 0.1093        | 2.09  | 2000 | 0.0140          | 0.9974   |
+| 0.1726        | 2.19  | 2100 | 0.0147          | 0.9963   |
+| 0.0476        | 2.3   | 2200 | 0.0058          | 0.9993   |
+| 0.0257        | 2.4   | 2300 | 0.0424          | 0.9911   |
+| 0.0215        | 2.51  | 2400 | 0.0076          | 0.9989   |
+| 0.0748        | 2.61  | 2500 | 0.0099          | 0.9974   |
+| 0.0059        | 2.72  | 2600 | 0.0053          | 0.9993   |
+| 0.0527        | 2.82  | 2700 | 0.0149          | 0.9963   |
+| 0.0203        | 2.93  | 2800 | 0.0041          | 0.9993   |
+| 0.0791        | 3.03  | 2900 | 0.0033          | 0.9989   |
+| 0.0389        | 3.13  | 3000 | 0.0033          | 0.9989   |
+| 0.0459        | 3.24  | 3100 | 0.0044          | 0.9989   |
+| 0.0276        | 3.34  | 3200 | 0.0031          | 0.9996   |
+| 0.0139        | 3.45  | 3300 | 0.0028          | 0.9996   |
+| 0.0076        | 3.55  | 3400 | 0.0055          | 0.9985   |
+| 0.0097        | 3.66  | 3500 | 0.0027          | 0.9996   |
+| 0.0193        | 3.76  | 3600 | 0.0026          | 0.9996   |
+| 0.0471        | 3.87  | 3700 | 0.0027          | 0.9996   |
+| 0.0282        | 3.97  | 3800 | 0.0027          | 0.9996   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

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": "10",
+    "1": "100",
+    "2": "1000",
+    "3": "2",
+    "4": "20",
+    "5": "200",
+    "6": "5",
+    "7": "50",
+    "8": "500"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "10": "0",
+    "100": "1",
+    "1000": "2",
+    "2": "3",
+    "20": "4",
+    "200": "5",
+    "5": "6",
+    "50": "7",
+    "500": "8"
+  },
+  "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": "4.32.1"
+}

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": "ViTFeatureExtractor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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+size 343290221

training_args.bin

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