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vit_largeFunny8
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: 0.7080
- Accuracy: 0.6660
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 |
|---|---|---|---|---|
| 0.6298 | 0.53 | 100 | 0.6839 | 0.5653 |
| 0.4609 | 1.06 | 200 | 0.6515 | 0.6210 |
| 0.4163 | 1.59 | 300 | 0.6431 | 0.6253 |
| 0.2278 | 2.12 | 400 | 0.6650 | 0.6231 |
| 0.2874 | 2.65 | 500 | 0.6780 | 0.6424 |
| 0.1225 | 3.17 | 600 | 0.6798 | 0.6552 |
| 0.1296 | 3.7 | 700 | 0.7080 | 0.6660 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
