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image_classification
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: 1.3383
- Accuracy: 0.5625
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 80 | 1.6519 | 0.3312 |
| No log | 2.0 | 160 | 1.4509 | 0.4125 |
| No log | 3.0 | 240 | 1.3641 | 0.5062 |
| No log | 4.0 | 320 | 1.2676 | 0.5875 |
| No log | 5.0 | 400 | 1.2718 | 0.5188 |
| No log | 6.0 | 480 | 1.2250 | 0.5125 |
| 1.2828 | 7.0 | 560 | 1.1933 | 0.55 |
| 1.2828 | 8.0 | 640 | 1.1538 | 0.575 |
| 1.2828 | 9.0 | 720 | 1.2479 | 0.55 |
| 1.2828 | 10.0 | 800 | 1.2487 | 0.575 |
| 1.2828 | 11.0 | 880 | 1.2418 | 0.5938 |
| 1.2828 | 12.0 | 960 | 1.1514 | 0.6062 |
| 0.5147 | 13.0 | 1040 | 1.2563 | 0.5563 |
| 0.5147 | 14.0 | 1120 | 1.2933 | 0.5813 |
| 0.5147 | 15.0 | 1200 | 1.2857 | 0.5813 |
| 0.5147 | 16.0 | 1280 | 1.3044 | 0.575 |
| 0.5147 | 17.0 | 1360 | 1.4134 | 0.5687 |
| 0.5147 | 18.0 | 1440 | 1.3277 | 0.5875 |
| 0.2675 | 19.0 | 1520 | 1.2963 | 0.575 |
| 0.2675 | 20.0 | 1600 | 1.2049 | 0.6125 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
