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:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: emotion_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: 0.53125
+---
+
+<!-- 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. -->
+
+# emotion_classification
+
+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: 1.8129
+- Accuracy: 0.5312
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 30
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 40   | 1.4349          | 0.45     |
+| No log        | 2.0   | 80   | 1.4560          | 0.5      |
+| No log        | 3.0   | 120  | 1.5158          | 0.4813   |
+| No log        | 4.0   | 160  | 1.4489          | 0.5125   |
+| No log        | 5.0   | 200  | 1.8968          | 0.425    |
+| No log        | 6.0   | 240  | 1.6870          | 0.5062   |
+| No log        | 7.0   | 280  | 1.6759          | 0.4813   |
+| No log        | 8.0   | 320  | 1.6498          | 0.5312   |
+| No log        | 9.0   | 360  | 1.7581          | 0.5      |
+| No log        | 10.0  | 400  | 1.7798          | 0.5      |
+| No log        | 11.0  | 440  | 1.6983          | 0.525    |
+| No log        | 12.0  | 480  | 1.7756          | 0.5375   |
+| 0.1761        | 13.0  | 520  | 1.7346          | 0.5125   |
+| 0.1761        | 14.0  | 560  | 1.8079          | 0.525    |
+| 0.1761        | 15.0  | 600  | 1.7950          | 0.5188   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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