Aradam_ViTL-16-384-2e-4-batch_16_epoch_4_classes_24
This model is a fine-tuned version of google/vit-large-patch16-384 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1097
- Accuracy: 0.9698
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: 0.0002
- 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: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1511 | 0.03 | 100 | 0.8900 | 0.7471 |
0.8497 | 0.07 | 200 | 0.8558 | 0.7687 |
0.6297 | 0.1 | 300 | 0.5995 | 0.8132 |
0.5735 | 0.14 | 400 | 0.4456 | 0.8649 |
0.307 | 0.17 | 500 | 0.4031 | 0.8851 |
0.3961 | 0.21 | 600 | 0.4865 | 0.8506 |
0.6511 | 0.24 | 700 | 0.5270 | 0.8491 |
0.4526 | 0.28 | 800 | 0.6105 | 0.8376 |
0.4071 | 0.31 | 900 | 0.3936 | 0.8937 |
0.2729 | 0.35 | 1000 | 0.3287 | 0.8994 |
0.4277 | 0.38 | 1100 | 0.5402 | 0.8621 |
0.2588 | 0.42 | 1200 | 0.3344 | 0.9023 |
0.3034 | 0.45 | 1300 | 0.3269 | 0.8922 |
0.2463 | 0.49 | 1400 | 0.4931 | 0.8563 |
0.1999 | 0.52 | 1500 | 0.3622 | 0.9037 |
0.1483 | 0.56 | 1600 | 0.3114 | 0.9066 |
0.1266 | 0.59 | 1700 | 0.3893 | 0.8894 |
0.1131 | 0.63 | 1800 | 0.2696 | 0.9267 |
0.4377 | 0.66 | 1900 | 0.2953 | 0.9224 |
0.1578 | 0.7 | 2000 | 0.3059 | 0.9109 |
0.1273 | 0.73 | 2100 | 0.2474 | 0.9267 |
0.077 | 0.77 | 2200 | 0.2231 | 0.9382 |
0.0855 | 0.8 | 2300 | 0.2795 | 0.9368 |
0.0756 | 0.84 | 2400 | 0.2858 | 0.9210 |
0.2635 | 0.87 | 2500 | 0.2563 | 0.9353 |
0.1622 | 0.91 | 2600 | 0.2727 | 0.9325 |
0.1941 | 0.94 | 2700 | 0.2450 | 0.9239 |
0.0144 | 0.98 | 2800 | 0.2113 | 0.9454 |
0.0617 | 1.01 | 2900 | 0.1612 | 0.9454 |
0.0188 | 1.04 | 3000 | 0.2029 | 0.9425 |
0.0731 | 1.08 | 3100 | 0.1762 | 0.9612 |
0.0846 | 1.11 | 3200 | 0.1612 | 0.9569 |
0.0586 | 1.15 | 3300 | 0.2737 | 0.9353 |
0.0258 | 1.18 | 3400 | 0.1310 | 0.9670 |
0.0665 | 1.22 | 3500 | 0.1515 | 0.9540 |
0.0143 | 1.25 | 3600 | 0.2254 | 0.9440 |
0.0842 | 1.29 | 3700 | 0.2393 | 0.9468 |
0.0019 | 1.32 | 3800 | 0.1660 | 0.9526 |
0.013 | 1.36 | 3900 | 0.1413 | 0.9684 |
0.0177 | 1.39 | 4000 | 0.1455 | 0.9641 |
0.0128 | 1.43 | 4100 | 0.1291 | 0.9641 |
0.0222 | 1.46 | 4200 | 0.1567 | 0.9526 |
0.0017 | 1.5 | 4300 | 0.1640 | 0.9569 |
0.0009 | 1.53 | 4400 | 0.1861 | 0.9612 |
0.0007 | 1.57 | 4500 | 0.1440 | 0.9713 |
0.0026 | 1.6 | 4600 | 0.0940 | 0.9784 |
0.0006 | 1.64 | 4700 | 0.1282 | 0.9655 |
0.0023 | 1.67 | 4800 | 0.1341 | 0.9698 |
0.0002 | 1.71 | 4900 | 0.1099 | 0.9727 |
0.0013 | 1.74 | 5000 | 0.0872 | 0.9756 |
0.0001 | 1.78 | 5100 | 0.0908 | 0.9784 |
0.0006 | 1.81 | 5200 | 0.1034 | 0.9727 |
0.0009 | 1.85 | 5300 | 0.0940 | 0.9727 |
0.0 | 1.88 | 5400 | 0.1236 | 0.9655 |
0.0003 | 1.92 | 5500 | 0.1180 | 0.9684 |
0.0001 | 1.95 | 5600 | 0.1091 | 0.9698 |
0.0001 | 1.99 | 5700 | 0.1097 | 0.9698 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ZaneHorrible/ViTL_16_384_1e_4_batch_16_epoch_4_classes_24
Base model
google/vit-large-patch16-384
Finetuned
this model