End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- fair_face
+metrics:
+- accuracy
+model-index:
+- name: initial_ViT_model
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: fair_face
+      type: fair_face
+      config: '0.25'
+      split: train[:5000]
+      args: '0.25'
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.152
+---
+
+<!-- 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. -->
+
+# initial_ViT_model
+
+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 fair_face dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.1666
+- Accuracy: 0.152
+
+## 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: 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: 0.2
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 4.7179        | 3.17  | 50   | 4.5313          | 0.094    |
+| 4.3281        | 6.35  | 100  | 4.2542          | 0.122    |
+| 4.1225        | 9.52  | 150  | 4.1666          | 0.152    |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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