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--- |
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library_name: transformers |
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base_model: carlosleao/vit-Facial-Expression-Recognition |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: RAFDB-Facial-Expression-Recognition |
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results: [] |
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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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# RAFDB-Facial-Expression-Recognition |
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This model is a fine-tuned version of [carlosleao/vit-Facial-Expression-Recognition](https://huggingface.co/carlosleao/vit-Facial-Expression-Recognition) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5906 |
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- Accuracy: 0.4159 |
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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: 3e-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: 8 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 30 |
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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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| 1.7235 | 2.0833 | 100 | 1.6571 | 0.3875 | |
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| 1.5738 | 4.1667 | 200 | 1.5756 | 0.3967 | |
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| 1.4811 | 6.25 | 300 | 1.5389 | 0.4166 | |
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| 1.3178 | 8.3333 | 400 | 1.5501 | 0.4003 | |
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| 1.095 | 10.4167 | 500 | 1.5906 | 0.4159 | |
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| 0.8081 | 12.5 | 600 | 1.7889 | 0.3641 | |
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| 0.594 | 14.5833 | 700 | 1.9123 | 0.3833 | |
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| 0.434 | 16.6667 | 800 | 2.1054 | 0.3638 | |
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| 0.3201 | 18.75 | 900 | 2.3273 | 0.3455 | |
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| 0.2472 | 20.8333 | 1000 | 2.3722 | 0.3510 | |
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| 0.1879 | 22.9167 | 1100 | 2.4218 | 0.3611 | |
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| 0.1255 | 25.0 | 1200 | 2.4329 | 0.3817 | |
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| 0.0749 | 27.0833 | 1300 | 2.5189 | 0.3585 | |
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| 0.0538 | 29.1667 | 1400 | 2.5638 | 0.3686 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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