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: 0.59375
+---
+
+<!-- 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: 1.2453
+- Accuracy: 0.5938
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 20   | 1.9465          | 0.325    |
+| No log        | 2.0   | 40   | 1.7314          | 0.4375   |
+| No log        | 3.0   | 60   | 1.5249          | 0.5375   |
+| No log        | 4.0   | 80   | 1.4166          | 0.4875   |
+| No log        | 5.0   | 100  | 1.3605          | 0.55     |
+| No log        | 6.0   | 120  | 1.3204          | 0.5563   |
+| No log        | 7.0   | 140  | 1.2074          | 0.6      |
+| No log        | 8.0   | 160  | 1.2138          | 0.6      |
+| No log        | 9.0   | 180  | 1.2600          | 0.5625   |
+| No log        | 10.0  | 200  | 1.2103          | 0.5563   |
+| No log        | 11.0  | 220  | 1.1736          | 0.5687   |
+| No log        | 12.0  | 240  | 1.2462          | 0.5687   |
+| No log        | 13.0  | 260  | 1.2009          | 0.5813   |
+| No log        | 14.0  | 280  | 1.2105          | 0.5437   |
+| No log        | 15.0  | 300  | 1.2705          | 0.5125   |
+| No log        | 16.0  | 320  | 1.2135          | 0.5938   |
+| No log        | 17.0  | 340  | 1.2089          | 0.5563   |
+| No log        | 18.0  | 360  | 1.2818          | 0.5375   |
+| No log        | 19.0  | 380  | 1.3076          | 0.5062   |
+| No log        | 20.0  | 400  | 1.2479          | 0.55     |
+| No log        | 21.0  | 420  | 1.2218          | 0.55     |
+| No log        | 22.0  | 440  | 1.0957          | 0.6188   |
+| No log        | 23.0  | 460  | 1.2437          | 0.5875   |
+| No log        | 24.0  | 480  | 1.3598          | 0.5125   |
+| 0.8126        | 25.0  | 500  | 1.2759          | 0.55     |
+| 0.8126        | 26.0  | 520  | 1.1474          | 0.6      |
+| 0.8126        | 27.0  | 540  | 1.1115          | 0.6375   |
+| 0.8126        | 28.0  | 560  | 1.1715          | 0.5687   |
+| 0.8126        | 29.0  | 580  | 1.3133          | 0.5625   |
+| 0.8126        | 30.0  | 600  | 1.2526          | 0.5437   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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