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--- |
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license: apache-2.0 |
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base_model: motheecreator/vit-Facial-Expression-Recognition |
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tags: |
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- generated_from_trainer |
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datasets: |
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- image_folder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-Facial-Expression-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: image_folder |
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type: image_folder |
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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: 0.7444126074498567 |
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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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# vit-Facial-Expression-Recognition |
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This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7038 |
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- Accuracy: 0.7444 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 0.7175 | 1.0 | 654 | 0.7309 | 0.7081 | |
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| 0.6952 | 2.0 | 1308 | 0.7379 | 0.6931 | |
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| 0.5041 | 3.0 | 1962 | 0.7444 | 0.7038 | |
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| 0.2461 | 4.0 | 2617 | 0.7393 | 0.7843 | |
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| 0.1846 | 5.0 | 3270 | 0.7391 | 0.8219 | |
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| 0.276 | 6.0 | 3924 | 0.8876 | 0.7335 | |
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| 0.2217 | 7.0 | 4578 | 0.9752 | 0.7255 | |
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| 0.0646 | 8.0 | 5232 | 1.0957 | 0.7263 | |
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| 0.063 | 9.0 | 5887 | 1.1335 | 0.7263 | |
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| 0.0562 | 10.0 | 6540 | 1.1663 | 0.7307 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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