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vit_largeFunnyUpdate
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: 0.8459
- Accuracy: 0.5963
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 |
|---|---|---|---|---|
| 0.6664 | 0.53 | 100 | 0.7045 | 0.5424 |
| 0.4984 | 1.05 | 200 | 0.6890 | 0.5507 |
| 0.4817 | 1.58 | 300 | 0.6993 | 0.5839 |
| 0.2473 | 2.11 | 400 | 0.7159 | 0.5901 |
| 0.3043 | 2.63 | 500 | 0.7544 | 0.5880 |
| 0.1542 | 3.16 | 600 | 0.8031 | 0.5921 |
| 0.1686 | 3.68 | 700 | 0.8459 | 0.5963 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
