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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
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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: finetuned-FER2013 |
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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: 0.7011494252873564 |
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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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# finetuned-FER2013 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8313 |
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- Accuracy: 0.7011 |
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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-06 |
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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: 40 |
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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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| 1.7483 | 1.0 | 202 | 1.7005 | 0.3386 | |
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| 1.4419 | 2.0 | 404 | 1.3213 | 0.5315 | |
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| 1.2917 | 3.0 | 606 | 1.1559 | 0.5785 | |
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| 1.2437 | 4.0 | 808 | 1.0729 | 0.6162 | |
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| 1.1635 | 5.0 | 1010 | 1.0161 | 0.6311 | |
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| 1.1087 | 6.0 | 1212 | 0.9862 | 0.6465 | |
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| 1.0964 | 7.0 | 1414 | 0.9901 | 0.6440 | |
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| 1.0895 | 8.0 | 1616 | 0.9410 | 0.6555 | |
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| 1.0384 | 9.0 | 1818 | 0.9221 | 0.6628 | |
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| 1.0333 | 10.0 | 2020 | 0.9142 | 0.6681 | |
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| 1.0016 | 11.0 | 2222 | 0.9081 | 0.6681 | |
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| 0.9503 | 12.0 | 2424 | 0.9013 | 0.6712 | |
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| 0.9804 | 13.0 | 2626 | 0.8937 | 0.6771 | |
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| 0.9712 | 14.0 | 2828 | 0.8809 | 0.6830 | |
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| 1.0151 | 15.0 | 3030 | 0.8704 | 0.6855 | |
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| 0.9739 | 16.0 | 3232 | 0.8886 | 0.6775 | |
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| 0.9267 | 17.0 | 3434 | 0.8653 | 0.6855 | |
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| 0.9428 | 18.0 | 3636 | 0.8633 | 0.6848 | |
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| 0.9654 | 19.0 | 3838 | 0.8697 | 0.6809 | |
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| 0.9256 | 20.0 | 4040 | 0.8559 | 0.6855 | |
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| 0.9345 | 21.0 | 4242 | 0.8533 | 0.6883 | |
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| 0.9479 | 22.0 | 4444 | 0.8548 | 0.6907 | |
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| 0.8829 | 23.0 | 4646 | 0.8461 | 0.6851 | |
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| 0.8999 | 24.0 | 4848 | 0.8399 | 0.6883 | |
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| 0.9047 | 25.0 | 5050 | 0.8403 | 0.6973 | |
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| 0.9415 | 26.0 | 5252 | 0.8437 | 0.6952 | |
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| 0.937 | 27.0 | 5454 | 0.8393 | 0.6931 | |
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| 0.8692 | 28.0 | 5656 | 0.8331 | 0.6977 | |
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| 0.9396 | 29.0 | 5858 | 0.8418 | 0.6973 | |
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| 0.8712 | 30.0 | 6060 | 0.8392 | 0.6921 | |
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| 0.9426 | 31.0 | 6262 | 0.8324 | 0.7011 | |
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| 0.884 | 32.0 | 6464 | 0.8325 | 0.6959 | |
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| 0.8433 | 33.0 | 6666 | 0.8300 | 0.6987 | |
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| 0.8869 | 34.0 | 6868 | 0.8328 | 0.6963 | |
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| 0.89 | 35.0 | 7070 | 0.8324 | 0.6973 | |
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| 0.8639 | 36.0 | 7272 | 0.8317 | 0.6956 | |
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| 0.8844 | 37.0 | 7474 | 0.8315 | 0.6970 | |
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| 0.8621 | 38.0 | 7676 | 0.8334 | 0.6991 | |
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| 0.8942 | 39.0 | 7878 | 0.8350 | 0.6998 | |
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| 0.8609 | 40.0 | 8080 | 0.8313 | 0.7011 | |
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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 2.16.1 |
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- Tokenizers 0.15.0 |
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