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--- |
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license: apache-2.0 |
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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: beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05-finetuned-SFEW-7e-05 |
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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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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.49596309111880044 |
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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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# beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05-finetuned-SFEW-7e-05 |
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This model is a fine-tuned version of [Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05](https://huggingface.co/Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05) on the image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5629 |
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- Accuracy: 0.4960 |
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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: 7e-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: 10 |
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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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| 2.1509 | 0.97 | 14 | 1.6920 | 0.3725 | |
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| 1.6764 | 1.97 | 28 | 1.5035 | 0.4694 | |
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| 1.2723 | 2.97 | 42 | 1.5061 | 0.4694 | |
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| 1.1746 | 3.97 | 56 | 1.5421 | 0.4729 | |
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| 0.9954 | 4.97 | 70 | 1.5657 | 0.4787 | |
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| 1.0029 | 5.97 | 84 | 1.5867 | 0.4844 | |
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| 0.9139 | 6.97 | 98 | 1.5943 | 0.4879 | |
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| 0.8335 | 7.97 | 112 | 1.6003 | 0.4890 | |
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| 0.8382 | 8.97 | 126 | 1.5629 | 0.4960 | |
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| 0.7169 | 9.97 | 140 | 1.5772 | 0.4856 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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