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: vit-base-aihub_model-v2
+  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: 0.8373493975903614
+    - name: Precision
+      type: precision
+      value: 0.8745971666076694
+    - name: Recall
+      type: recall
+      value: 0.7993336310123969
+    - name: F1
+      type: f1
+      value: 0.8036849674785987
+---
+
+<!-- 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-aihub_model-v2
+
+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: 1.1993
+- Accuracy: 0.8373
+- Precision: 0.8746
+- Recall: 0.7993
+- F1: 0.8037
+
+## 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: 5e-05
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 512
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 3    | 1.6294          | 0.6747   | 0.6434    | 0.6238 | 0.5944 |
+| No log        | 2.0   | 6    | 1.4495          | 0.7530   | 0.7776    | 0.7018 | 0.6875 |
+| No log        | 3.0   | 9    | 1.3163          | 0.8373   | 0.8563    | 0.7993 | 0.8022 |
+| 1.5378        | 4.0   | 12   | 1.2327          | 0.8373   | 0.8736    | 0.7993 | 0.8035 |
+| 1.5378        | 5.0   | 15   | 1.1993          | 0.8373   | 0.8746    | 0.7993 | 0.8037 |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3