beit-base-patch16-224-pt22k-ft22k-finetuned-mnist
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the mnist dataset. It achieves the following results on the evaluation set:
- Loss: 0.0202
- Accuracy: 0.9935
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: 5e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3376 | 1.0 | 937 | 0.0446 | 0.9855 |
| 0.318 | 2.0 | 1874 | 0.0262 | 0.9916 |
| 0.2374 | 3.0 | 2811 | 0.0202 | 0.9935 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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