beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05
This model is a fine-tuned version of lixiqi/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-7e-05 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0127
- Accuracy: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.9364 | 0.97 | 27 | 0.1873 | 0.9645 |
0.3365 | 1.97 | 54 | 0.0951 | 0.9848 |
0.2482 | 2.97 | 81 | 0.0562 | 0.9949 |
0.1844 | 3.97 | 108 | 0.0213 | 0.9949 |
0.1693 | 4.97 | 135 | 0.0127 | 1.0 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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