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vit_large_valid_test_turnFunnyUpdate
This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8393
- Accuracy: 0.5902
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6625 | 0.53 | 100 | 0.7073 | 0.5541 |
0.5001 | 1.05 | 200 | 0.6925 | 0.5456 |
0.5026 | 1.58 | 300 | 0.7123 | 0.5520 |
0.2673 | 2.11 | 400 | 0.7391 | 0.5541 |
0.2611 | 2.63 | 500 | 0.7592 | 0.5860 |
0.167 | 3.16 | 600 | 0.8018 | 0.5902 |
0.2071 | 3.68 | 700 | 0.8393 | 0.5902 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3