ViT_face
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the face dataset. It achieves the following results on the evaluation set:
- Loss: 0.5240
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 38 | 0.9844 |
| No log | 2.0 | 76 | 0.8261 |
| No log | 3.0 | 114 | 0.6908 |
| No log | 4.0 | 152 | 0.6297 |
| No log | 5.0 | 190 | 0.5770 |
| No log | 6.0 | 228 | 0.5463 |
| No log | 7.0 | 266 | 0.5250 |
| No log | 8.0 | 304 | 0.5263 |
| No log | 9.0 | 342 | 0.5306 |
| No log | 10.0 | 380 | 0.5240 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21k