End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: emotion_classifier
+  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: 0.4875
+---
+
+<!-- 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_classifier
+
+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: 1.5654
+- Accuracy: 0.4875
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 40   | 2.0725          | 0.1437   |
+| No log        | 2.0   | 80   | 2.0190          | 0.2313   |
+| No log        | 3.0   | 120  | 1.9191          | 0.325    |
+| No log        | 4.0   | 160  | 1.7563          | 0.4062   |
+| No log        | 5.0   | 200  | 1.6603          | 0.45     |
+| No log        | 6.0   | 240  | 1.6096          | 0.4625   |
+| No log        | 7.0   | 280  | 1.5654          | 0.4875   |
+| No log        | 8.0   | 320  | 1.5510          | 0.4813   |
+| No log        | 9.0   | 360  | 1.5434          | 0.4813   |
+| No log        | 10.0  | 400  | 1.5364          | 0.4875   |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.5.1+cpu
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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