update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: google-vit-base-patch16-224-face
+  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: 0.6960989202368513
+    - name: Precision
+      type: precision
+      value: 0.6966334506335445
+    - name: Recall
+      type: recall
+      value: 0.6960989202368513
+    - name: F1
+      type: f1
+      value: 0.6957934361657124
+---
+
+<!-- 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. -->
+
+# google-vit-base-patch16-224-face
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3257
+- Accuracy: 0.6961
+- Precision: 0.6966
+- Recall: 0.6961
+- F1: 0.6958
+
+## 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 | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.8364        | 0.99  | 89   | 0.9453          | 0.6484   | 0.6462    | 0.6484 | 0.6385 |
+| 0.7433        | 1.99  | 178  | 0.8876          | 0.6778   | 0.6794    | 0.6778 | 0.6730 |
+| 0.4732        | 2.99  | 267  | 0.9043          | 0.6872   | 0.6907    | 0.6872 | 0.6841 |
+| 0.2861        | 3.99  | 356  | 0.9865          | 0.6848   | 0.6808    | 0.6848 | 0.6813 |
+| 0.1234        | 4.99  | 445  | 1.1048          | 0.6853   | 0.6907    | 0.6853 | 0.6872 |
+| 0.0599        | 5.99  | 534  | 1.2362          | 0.6890   | 0.6897    | 0.6890 | 0.6876 |
+| 0.0289        | 6.99  | 623  | 1.3141          | 0.6931   | 0.6926    | 0.6931 | 0.6921 |
+| 0.0134        | 7.99  | 712  | 1.3257          | 0.6961   | 0.6966    | 0.6961 | 0.6958 |
+
+
+### Framework versions
+
+- Transformers 4.24.0.dev0
+- Pytorch 1.11.0+cu102
+- Datasets 2.6.1
+- Tokenizers 0.13.1