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: hq_fer2013notest
+  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: 0.7052268506235075
+    - name: Precision
+      type: precision
+      value: 0.7048074435355876
+    - name: Recall
+      type: recall
+      value: 0.7052268506235075
+    - name: F1
+      type: f1
+      value: 0.7036260157126459
+---
+
+<!-- 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. -->
+
+# hq_fer2013notest
+
+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: 0.8294
+- Accuracy: 0.7052
+- Precision: 0.7048
+- Recall: 0.7052
+- F1: 0.7036
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 17
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.2982        | 1.0   | 353  | 1.2708          | 0.5635   | 0.5107    | 0.5635 | 0.5168 |
+| 1.0218        | 2.0   | 706  | 1.0159          | 0.6411   | 0.6397    | 0.6411 | 0.6301 |
+| 0.9437        | 3.0   | 1059 | 0.9452          | 0.6631   | 0.6698    | 0.6631 | 0.6556 |
+| 0.8282        | 4.0   | 1412 | 0.8873          | 0.6829   | 0.6798    | 0.6829 | 0.6743 |
+| 0.7717        | 5.0   | 1765 | 0.8612          | 0.6884   | 0.6888    | 0.6884 | 0.6835 |
+| 0.7678        | 6.0   | 2118 | 0.8473          | 0.6985   | 0.6989    | 0.6985 | 0.6966 |
+| 0.7096        | 7.0   | 2471 | 0.8363          | 0.7018   | 0.7001    | 0.7018 | 0.6989 |
+| 0.6803        | 8.0   | 2824 | 0.8333          | 0.7036   | 0.7036    | 0.7036 | 0.7019 |
+| 0.6521        | 9.0   | 3177 | 0.8309          | 0.7050   | 0.7039    | 0.7050 | 0.7028 |
+| 0.6671        | 10.0  | 3530 | 0.8294          | 0.7052   | 0.7048    | 0.7052 | 0.7036 |
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2