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: finetuned-affecthq
+  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: 0.7179302910528207
+    - name: Precision
+      type: precision
+      value: 0.7173911115103917
+    - name: Recall
+      type: recall
+      value: 0.7179302910528207
+    - name: F1
+      type: f1
+      value: 0.7166821507529032
+---
+
+<!-- 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-affecthq
+
+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: 0.8116
+- Accuracy: 0.7179
+- Precision: 0.7174
+- Recall: 0.7179
+- F1: 0.7167
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.5413        | 1.0   | 174  | 1.4810          | 0.4898   | 0.4867    | 0.4898 | 0.4409 |
+| 1.0367        | 2.0   | 348  | 1.0571          | 0.6155   | 0.6172    | 0.6155 | 0.6041 |
+| 0.9534        | 3.0   | 522  | 0.9673          | 0.6475   | 0.6476    | 0.6475 | 0.6375 |
+| 0.8532        | 4.0   | 696  | 0.9056          | 0.6748   | 0.6710    | 0.6748 | 0.6704 |
+| 0.8211        | 5.0   | 870  | 0.8707          | 0.6903   | 0.6912    | 0.6903 | 0.6836 |
+| 0.7797        | 6.0   | 1044 | 0.8472          | 0.7050   | 0.7050    | 0.7050 | 0.7019 |
+| 0.7816        | 7.0   | 1218 | 0.8298          | 0.7111   | 0.7099    | 0.7111 | 0.7096 |
+| 0.7135        | 8.0   | 1392 | 0.8186          | 0.7111   | 0.7116    | 0.7111 | 0.7105 |
+| 0.6697        | 9.0   | 1566 | 0.8143          | 0.7140   | 0.7124    | 0.7140 | 0.7126 |
+| 0.6765        | 10.0  | 1740 | 0.8116          | 0.7179   | 0.7174    | 0.7179 | 0.7167 |
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2