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_model_1
+  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: 0.36875
+---
+
+<!-- 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_model_1
+
+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: 1.5998
+- Accuracy: 0.3688
+
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 5    | 2.0612          | 0.1812   |
+| 2.0585        | 2.0   | 10   | 2.0091          | 0.3125   |
+| 2.0585        | 3.0   | 15   | 1.9362          | 0.375    |
+| 1.9064        | 4.0   | 20   | 1.8335          | 0.3812   |
+| 1.9064        | 5.0   | 25   | 1.7466          | 0.35     |
+| 1.7196        | 6.0   | 30   | 1.6906          | 0.3312   |
+| 1.7196        | 7.0   | 35   | 1.6453          | 0.375    |
+| 1.5947        | 8.0   | 40   | 1.6180          | 0.4125   |
+| 1.5947        | 9.0   | 45   | 1.5876          | 0.4375   |
+| 1.5433        | 10.0  | 50   | 1.5849          | 0.4062   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

model.safetensors

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