vit_itri_downsample_normal
This model is a fine-tuned version of google/vit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 6.6738
- Accuracy: 0.3355
- Precision: 0.4688
- Recall: 0.3355
- F1: 0.2701
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: 0.0001
- train_batch_size: 24
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3133 | 1.0 | 334 | 3.3993 | 0.3685 | 0.5578 | 0.3685 | 0.3520 |
| 0.0981 | 2.0 | 668 | 4.3016 | 0.3603 | 0.5583 | 0.3603 | 0.3196 |
| 0.0628 | 3.0 | 1002 | 4.9479 | 0.3386 | 0.3274 | 0.3386 | 0.2681 |
| 0.0466 | 4.0 | 1336 | 4.8740 | 0.3150 | 0.4302 | 0.3150 | 0.2640 |
| 0.0297 | 5.0 | 1670 | 6.3499 | 0.3087 | 0.2861 | 0.3087 | 0.2053 |
| 0.0195 | 6.0 | 2004 | 5.5555 | 0.3498 | 0.4355 | 0.3498 | 0.2700 |
| 0.0261 | 7.0 | 2338 | 5.7446 | 0.3446 | 0.4763 | 0.3446 | 0.2888 |
| 0.0186 | 8.0 | 2672 | 6.0125 | 0.3107 | 0.3748 | 0.3107 | 0.2341 |
| 0.0117 | 9.0 | 3006 | 5.8823 | 0.3099 | 0.3911 | 0.3099 | 0.2456 |
| 0.0116 | 10.0 | 3340 | 5.9882 | 0.3331 | 0.4533 | 0.3331 | 0.2682 |
| 0.0048 | 11.0 | 3674 | 5.7636 | 0.3028 | 0.4634 | 0.3028 | 0.2980 |
| 0.0095 | 12.0 | 4008 | 6.1077 | 0.3228 | 0.4431 | 0.3228 | 0.2770 |
| 0.0011 | 13.0 | 4342 | 6.2826 | 0.3135 | 0.4474 | 0.3135 | 0.2744 |
| 0.0021 | 14.0 | 4676 | 6.2547 | 0.3503 | 0.4589 | 0.3503 | 0.2997 |
| 0.0013 | 15.0 | 5010 | 6.2053 | 0.3472 | 0.4804 | 0.3472 | 0.3102 |
| 0.0009 | 16.0 | 5344 | 6.6696 | 0.3405 | 0.4513 | 0.3405 | 0.2825 |
| 0.0001 | 17.0 | 5678 | 6.8090 | 0.3467 | 0.4797 | 0.3467 | 0.2853 |
| 0.0015 | 18.0 | 6012 | 6.5591 | 0.3379 | 0.4661 | 0.3379 | 0.2813 |
| 0.0001 | 19.0 | 6346 | 6.6722 | 0.3345 | 0.4674 | 0.3345 | 0.2724 |
| 0.0004 | 20.0 | 6680 | 6.6738 | 0.3355 | 0.4688 | 0.3355 | 0.2701 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1