model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4897
- Accuracy: 0.6
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 80 | 1.7001 | 0.325 |
No log | 2.0 | 160 | 1.4642 | 0.4875 |
No log | 3.0 | 240 | 1.3522 | 0.4625 |
No log | 4.0 | 320 | 1.3493 | 0.4688 |
No log | 5.0 | 400 | 1.2052 | 0.55 |
No log | 6.0 | 480 | 1.2267 | 0.5563 |
1.2917 | 7.0 | 560 | 1.1744 | 0.6062 |
1.2917 | 8.0 | 640 | 1.2969 | 0.5437 |
1.2917 | 9.0 | 720 | 1.2519 | 0.5687 |
1.2917 | 10.0 | 800 | 1.3108 | 0.5125 |
1.2917 | 11.0 | 880 | 1.2725 | 0.5875 |
1.2917 | 12.0 | 960 | 1.3437 | 0.55 |
0.5002 | 13.0 | 1040 | 1.3790 | 0.5375 |
0.5002 | 14.0 | 1120 | 1.3432 | 0.625 |
0.5002 | 15.0 | 1200 | 1.4395 | 0.55 |
0.5002 | 16.0 | 1280 | 1.3672 | 0.5875 |
0.5002 | 17.0 | 1360 | 1.3928 | 0.575 |
0.5002 | 18.0 | 1440 | 1.3016 | 0.5875 |
0.2523 | 19.0 | 1520 | 1.4815 | 0.5625 |
0.2523 | 20.0 | 1600 | 1.3394 | 0.6062 |
0.2523 | 21.0 | 1680 | 1.3450 | 0.5938 |
0.2523 | 22.0 | 1760 | 1.3924 | 0.6312 |
0.2523 | 23.0 | 1840 | 1.4664 | 0.5813 |
0.2523 | 24.0 | 1920 | 1.2635 | 0.65 |
0.1723 | 25.0 | 2000 | 1.4154 | 0.5625 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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