End of training

README.md

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+---
+base_model: nateraw/vit-age-classifier
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: image_classification
+  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: 0.34375
+---
+
+<!-- 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. -->
+
+# image_classification
+
+This model is a fine-tuned version of [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8469
+- Accuracy: 0.3438
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 0.3
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.8   | 1    | 1.8452          | 0.3125   |
+| No log        | 1.6   | 2    | 1.8435          | 0.35     |
+| No log        | 2.4   | 3    | 1.8282          | 0.3688   |
+| No log        | 4.0   | 5    | 1.8112          | 0.3563   |
+| No log        | 4.8   | 6    | 1.8180          | 0.3312   |
+| No log        | 5.6   | 7    | 1.8291          | 0.3375   |
+| No log        | 6.4   | 8    | 1.8036          | 0.3563   |
+| 1.6711        | 8.0   | 10   | 1.8134          | 0.3375   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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