beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05-finetuned-SFEW-7e-05
This model is a fine-tuned version of Celal11/beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013CKPlus-7e-05 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 1.5629
- Accuracy: 0.4960
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1509 | 0.97 | 14 | 1.6920 | 0.3725 |
| 1.6764 | 1.97 | 28 | 1.5035 | 0.4694 |
| 1.2723 | 2.97 | 42 | 1.5061 | 0.4694 |
| 1.1746 | 3.97 | 56 | 1.5421 | 0.4729 |
| 0.9954 | 4.97 | 70 | 1.5657 | 0.4787 |
| 1.0029 | 5.97 | 84 | 1.5867 | 0.4844 |
| 0.9139 | 6.97 | 98 | 1.5943 | 0.4879 |
| 0.8335 | 7.97 | 112 | 1.6003 | 0.4890 |
| 0.8382 | 8.97 | 126 | 1.5629 | 0.4960 |
| 0.7169 | 9.97 | 140 | 1.5772 | 0.4856 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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