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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: emotion_model |
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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: 0.4125 |
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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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# emotion_model |
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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: 1.6373 |
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- Accuracy: 0.4125 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-07 |
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- train_batch_size: 10 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.0746 | 1.0 | 64 | 1.6373 | 0.4125 | |
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| 1.0732 | 2.0 | 128 | 1.6375 | 0.4125 | |
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| 1.0719 | 3.0 | 192 | 1.6372 | 0.4062 | |
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| 1.0708 | 4.0 | 256 | 1.6372 | 0.4125 | |
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| 1.0698 | 5.0 | 320 | 1.6370 | 0.4062 | |
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| 1.0689 | 6.0 | 384 | 1.6368 | 0.4062 | |
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| 1.068 | 7.0 | 448 | 1.6367 | 0.4062 | |
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| 1.0673 | 8.0 | 512 | 1.6366 | 0.4062 | |
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| 1.0666 | 9.0 | 576 | 1.6366 | 0.4062 | |
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| 1.066 | 10.0 | 640 | 1.6366 | 0.4062 | |
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| 1.0656 | 11.0 | 704 | 1.6365 | 0.4062 | |
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| 1.0652 | 12.0 | 768 | 1.6364 | 0.4062 | |
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| 1.0649 | 13.0 | 832 | 1.6364 | 0.4062 | |
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| 1.0647 | 14.0 | 896 | 1.6364 | 0.4062 | |
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| 1.0646 | 15.0 | 960 | 1.6364 | 0.4062 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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