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vit-base-patch16-224-finetuned-imageclds
This model is a fine-tuned version of google/vit-base-patch16-224 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0010
- Accuracy: 0.9997
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0213 | 1.0 | 241 | 0.0067 | 0.9981 |
| 0.0251 | 2.0 | 482 | 0.0025 | 0.9994 |
| 0.0243 | 3.0 | 723 | 0.0146 | 0.9938 |
| 0.022 | 4.0 | 964 | 0.0010 | 0.9997 |
| 0.0206 | 5.0 | 1205 | 0.0019 | 0.9997 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
