cidaut_version_1
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: 0.0103
- 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9524 | 5 | 0.5816 | 0.6790 |
| 0.578 | 1.9048 | 10 | 0.2481 | 0.9506 |
| 0.578 | 2.8571 | 15 | 0.0853 | 0.9877 |
| 0.1389 | 4.0 | 21 | 0.0528 | 0.9877 |
| 0.1389 | 4.9524 | 26 | 0.0357 | 0.9877 |
| 0.0891 | 5.9048 | 31 | 0.0606 | 0.9815 |
| 0.0891 | 6.8571 | 36 | 0.0949 | 0.9753 |
| 0.1003 | 7.6190 | 40 | 0.0103 | 1.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3