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_2
+  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: 0.51875
+---
+
+<!-- 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_2
+
+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: 1.3274
+- Accuracy: 0.5188
+
+## 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: 4e-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   | 1.9337          | 0.3563   |
+| No log        | 2.0   | 40   | 1.7116          | 0.3375   |
+| No log        | 3.0   | 60   | 1.5755          | 0.4562   |
+| No log        | 4.0   | 80   | 1.4939          | 0.45     |
+| No log        | 5.0   | 100  | 1.4377          | 0.5062   |
+| No log        | 6.0   | 120  | 1.4363          | 0.4562   |
+| No log        | 7.0   | 140  | 1.3615          | 0.5125   |
+| No log        | 8.0   | 160  | 1.3021          | 0.5375   |
+| No log        | 9.0   | 180  | 1.3307          | 0.525    |
+| No log        | 10.0  | 200  | 1.3085          | 0.4938   |
+| No log        | 11.0  | 220  | 1.2798          | 0.5813   |
+| No log        | 12.0  | 240  | 1.2707          | 0.525    |
+| No log        | 13.0  | 260  | 1.2339          | 0.55     |
+| No log        | 14.0  | 280  | 1.3053          | 0.5437   |
+| No log        | 15.0  | 300  | 1.3038          | 0.4938   |
+| No log        | 16.0  | 320  | 1.3088          | 0.5375   |
+| No log        | 17.0  | 340  | 1.3336          | 0.5312   |
+| No log        | 18.0  | 360  | 1.3053          | 0.5      |
+| No log        | 19.0  | 380  | 1.2206          | 0.5687   |
+| No log        | 20.0  | 400  | 1.2598          | 0.5312   |
+| No log        | 21.0  | 420  | 1.3332          | 0.5125   |
+| No log        | 22.0  | 440  | 1.3388          | 0.5312   |
+| No log        | 23.0  | 460  | 1.3129          | 0.5563   |
+| No log        | 24.0  | 480  | 1.3632          | 0.5062   |
+| 0.9153        | 25.0  | 500  | 1.4166          | 0.4688   |
+| 0.9153        | 26.0  | 520  | 1.4094          | 0.5      |
+| 0.9153        | 27.0  | 540  | 1.4294          | 0.475    |
+| 0.9153        | 28.0  | 560  | 1.4937          | 0.475    |
+| 0.9153        | 29.0  | 580  | 1.3897          | 0.4938   |
+| 0.9153        | 30.0  | 600  | 1.4565          | 0.475    |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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