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rgai_emotion_recognition

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: rgai_emotion_recognition
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.58125
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # rgai_emotion_recognition
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3077
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+ - Accuracy: 0.5813
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.0698 | 1.0 | 25 | 2.0921 | 0.1125 |
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+ | 1.973 | 2.0 | 50 | 1.9930 | 0.1938 |
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+ | 1.8091 | 3.0 | 75 | 1.8374 | 0.3937 |
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+ | 1.5732 | 4.0 | 100 | 1.6804 | 0.475 |
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+ | 1.4087 | 5.0 | 125 | 1.5660 | 0.5125 |
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+ | 1.2653 | 6.0 | 150 | 1.4769 | 0.5375 |
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+ | 1.1443 | 7.0 | 175 | 1.4084 | 0.55 |
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+ | 0.9888 | 8.0 | 200 | 1.3633 | 0.5625 |
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+ | 0.9029 | 9.0 | 225 | 1.3305 | 0.55 |
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+ | 0.8372 | 10.0 | 250 | 1.3077 | 0.5813 |
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+ | 0.7569 | 11.0 | 275 | 1.2983 | 0.5625 |
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+ | 0.6886 | 12.0 | 300 | 1.2806 | 0.5687 |
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+ | 0.6216 | 13.0 | 325 | 1.2718 | 0.5687 |
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+ | 0.6385 | 14.0 | 350 | 1.2700 | 0.5563 |
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+ | 0.6029 | 15.0 | 375 | 1.2693 | 0.5625 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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