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swinv2-base-patch4-window8-256-for-pre_evaluation
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window8-256 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4873
- Accuracy: 0.4106
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6064 | 1.0 | 16 | 1.5189 | 0.3073 |
| 1.5058 | 2.0 | 32 | 1.5056 | 0.3073 |
| 1.5176 | 3.0 | 48 | 1.5176 | 0.2961 |
| 1.4883 | 4.0 | 64 | 1.5130 | 0.3073 |
| 1.4446 | 5.0 | 80 | 1.4540 | 0.3296 |
| 1.4568 | 6.0 | 96 | 1.5154 | 0.3156 |
| 1.4106 | 7.0 | 112 | 1.4272 | 0.3883 |
| 1.3804 | 8.0 | 128 | 1.4185 | 0.3743 |
| 1.3725 | 9.0 | 144 | 1.3943 | 0.3911 |
| 1.3441 | 10.0 | 160 | 1.4510 | 0.4022 |
| 1.3335 | 11.0 | 176 | 1.4337 | 0.3827 |
| 1.3055 | 12.0 | 192 | 1.4633 | 0.3855 |
| 1.3303 | 13.0 | 208 | 1.4674 | 0.3883 |
| 1.2882 | 14.0 | 224 | 1.4388 | 0.3911 |
| 1.2362 | 15.0 | 240 | 1.4676 | 0.3855 |
| 1.2572 | 16.0 | 256 | 1.4805 | 0.3799 |
| 1.2164 | 17.0 | 272 | 1.4717 | 0.3939 |
| 1.221 | 18.0 | 288 | 1.4354 | 0.4078 |
| 1.1713 | 19.0 | 304 | 1.4836 | 0.4078 |
| 1.18 | 20.0 | 320 | 1.4873 | 0.4106 |
| 1.1349 | 21.0 | 336 | 1.4853 | 0.3855 |
| 1.1138 | 22.0 | 352 | 1.4927 | 0.3966 |
| 1.1402 | 23.0 | 368 | 1.4672 | 0.3994 |
| 1.1183 | 24.0 | 384 | 1.5033 | 0.4022 |
| 1.0834 | 25.0 | 400 | 1.5448 | 0.3855 |
| 1.0515 | 26.0 | 416 | 1.5131 | 0.3939 |
| 1.0745 | 27.0 | 432 | 1.5314 | 0.3827 |
| 1.0332 | 28.0 | 448 | 1.5474 | 0.3939 |
| 1.0679 | 29.0 | 464 | 1.5327 | 0.3855 |
| 1.0295 | 30.0 | 480 | 1.5402 | 0.3855 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
