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: vit-base-patch16-224-in21k-face-recognition
+  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: 0.999957997311828
+---
+
+<!-- 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-base-patch16-224-in21k-face-recognition
+
+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: 0.0015
+- Accuracy: 1.0000
+
+## 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: 0.00012
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0368        | 1.0   | 372  | 0.0346          | 1.0000   |
+| 0.0094        | 2.0   | 744  | 0.0092          | 1.0000   |
+| 0.0046        | 3.0   | 1116 | 0.0047          | 1.0000   |
+| 0.0029        | 4.0   | 1488 | 0.0029          | 1.0      |
+| 0.0022        | 5.0   | 1860 | 0.0023          | 0.9999   |
+| 0.0017        | 6.0   | 2232 | 0.0017          | 1.0      |
+| 0.0015        | 7.0   | 2604 | 0.0015          | 1.0      |
+| 0.0014        | 8.0   | 2976 | 0.0015          | 1.0000   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 1.13.1+cu117
+- Datasets 2.13.2
+- Tokenizers 0.11.0