beit-base-patch16-224-pt22k-ft22k-finetunedt
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0147
- 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: 5e-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 |
|---|---|---|---|---|
| 0.4714 | 1.0 | 25 | 0.0147 | 1.0 |
| 0.0089 | 2.0 | 50 | 0.0008 | 1.0 |
| 0.0101 | 3.0 | 75 | 0.0003 | 1.0 |
| 0.0021 | 4.0 | 100 | 0.0002 | 1.0 |
| 0.0028 | 5.0 | 125 | 0.0001 | 1.0 |
| 0.0016 | 6.0 | 150 | 0.0001 | 1.0 |
| 0.0044 | 7.0 | 175 | 0.0001 | 1.0 |
| 0.0007 | 8.0 | 200 | 0.0001 | 1.0 |
| 0.0013 | 9.0 | 225 | 0.0001 | 1.0 |
| 0.0004 | 10.0 | 250 | 0.0001 | 1.0 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2