update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: finetuned-indian-food
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9521785334750266
+---
+
+<!-- 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 the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2139
+- Accuracy: 0.9522
+
+## 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0846        | 0.3   | 100  | 0.9561          | 0.8555   |
+| 0.7894        | 0.6   | 200  | 0.5871          | 0.8927   |
+| 0.6233        | 0.9   | 300  | 0.4447          | 0.9107   |
+| 0.3619        | 1.2   | 400  | 0.4355          | 0.8937   |
+| 0.34          | 1.5   | 500  | 0.3712          | 0.9118   |
+| 0.3413        | 1.8   | 600  | 0.4088          | 0.8916   |
+| 0.3619        | 2.1   | 700  | 0.3741          | 0.9044   |
+| 0.2135        | 2.4   | 800  | 0.3286          | 0.9160   |
+| 0.2166        | 2.7   | 900  | 0.2758          | 0.9416   |
+| 0.1557        | 3.0   | 1000 | 0.2679          | 0.9330   |
+| 0.1115        | 3.3   | 1100 | 0.2529          | 0.9362   |
+| 0.1571        | 3.6   | 1200 | 0.2360          | 0.9469   |
+| 0.1079        | 3.9   | 1300 | 0.2139          | 0.9522   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1