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: 0.55625
+---
+
+<!-- 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: 1.3006
+- Accuracy: 0.5563
+
+## 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: 0.0001
+- train_batch_size: 30
+- eval_batch_size: 30
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 22   | 1.8368          | 0.425    |
+| No log        | 2.0   | 44   | 1.6260          | 0.375    |
+| No log        | 3.0   | 66   | 1.4368          | 0.5      |
+| No log        | 4.0   | 88   | 1.3790          | 0.5062   |
+| No log        | 5.0   | 110  | 1.3382          | 0.5125   |
+| No log        | 6.0   | 132  | 1.3136          | 0.4938   |
+| No log        | 7.0   | 154  | 1.2557          | 0.4938   |
+| No log        | 8.0   | 176  | 1.2959          | 0.5      |
+| No log        | 9.0   | 198  | 1.2810          | 0.5125   |
+| No log        | 10.0  | 220  | 1.2689          | 0.5563   |
+| No log        | 11.0  | 242  | 1.3548          | 0.4875   |
+| No log        | 12.0  | 264  | 1.2026          | 0.5563   |
+| No log        | 13.0  | 286  | 1.2096          | 0.575    |
+| No log        | 14.0  | 308  | 1.3175          | 0.525    |
+| No log        | 15.0  | 330  | 1.3121          | 0.5312   |
+| No log        | 16.0  | 352  | 1.4260          | 0.5312   |
+| No log        | 17.0  | 374  | 1.4547          | 0.5062   |
+| No log        | 18.0  | 396  | 1.3529          | 0.525    |
+| No log        | 19.0  | 418  | 1.2386          | 0.5938   |
+| No log        | 20.0  | 440  | 1.3504          | 0.5375   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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