results
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2708
- Accuracy: 0.625
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7925 | 1.0 | 80 | 1.2881 | 0.5625 |
| 0.8274 | 2.0 | 160 | 1.2765 | 0.525 |
| 0.3026 | 3.0 | 240 | 1.1460 | 0.55 |
| 0.0789 | 4.0 | 320 | 1.1513 | 0.5938 |
| 0.0204 | 5.0 | 400 | 1.2303 | 0.5938 |
| 0.0178 | 6.0 | 480 | 1.2826 | 0.6188 |
| 0.0118 | 7.0 | 560 | 1.2708 | 0.625 |
| 0.0089 | 8.0 | 640 | 1.2886 | 0.6188 |
| 0.0107 | 9.0 | 720 | 1.3031 | 0.6062 |
| 0.0086 | 10.0 | 800 | 1.3060 | 0.6062 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0
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Model tree for saccanip/emotion-vit
Base model
google/vit-base-patch16-224