metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-dmae-humeda-DAV45
results: []
swinv2-tiny-patch4-window8-256-dmae-humeda-DAV45
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7812
- Accuracy: 0.7841
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.1945 | 1.0 | 20 | 1.2588 | 0.4545 |
| 4.5836 | 2.0 | 40 | 0.9658 | 0.7159 |
| 2.9056 | 3.0 | 60 | 0.7737 | 0.7273 |
| 2.8061 | 4.0 | 80 | 0.6738 | 0.7727 |
| 1.9405 | 5.0 | 100 | 0.6261 | 0.7614 |
| 1.4425 | 6.0 | 120 | 0.8127 | 0.75 |
| 1.3554 | 7.0 | 140 | 0.7812 | 0.7841 |
| 1.2975 | 8.0 | 160 | 0.8405 | 0.75 |
| 0.812 | 9.0 | 180 | 1.0777 | 0.7159 |
| 0.7984 | 10.0 | 200 | 0.9404 | 0.7159 |
| 0.7895 | 11.0 | 220 | 1.0902 | 0.7045 |
| 0.7333 | 12.0 | 240 | 1.0998 | 0.75 |
| 0.6073 | 13.0 | 260 | 1.2734 | 0.7386 |
| 0.6548 | 14.0 | 280 | 1.3034 | 0.7159 |
| 0.5538 | 15.0 | 300 | 1.1890 | 0.75 |
| 0.556 | 16.0 | 320 | 1.3662 | 0.75 |
| 0.5273 | 17.0 | 340 | 1.2833 | 0.7273 |
| 0.3863 | 18.0 | 360 | 1.2976 | 0.7159 |
| 0.5185 | 19.0 | 380 | 1.2461 | 0.7386 |
| 0.475 | 20.0 | 400 | 1.2543 | 0.7386 |
| 0.3021 | 21.0 | 420 | 1.3143 | 0.7727 |
| 0.3334 | 22.0 | 440 | 1.2873 | 0.75 |
| 0.3773 | 23.0 | 460 | 1.3992 | 0.7386 |
| 0.2606 | 24.0 | 480 | 1.5181 | 0.7159 |
| 0.3344 | 25.0 | 500 | 1.4330 | 0.7614 |
| 0.3349 | 26.0 | 520 | 1.4165 | 0.7841 |
| 0.3246 | 27.0 | 540 | 1.3634 | 0.7614 |
| 0.3395 | 28.0 | 560 | 1.3985 | 0.7614 |
| 0.2606 | 29.0 | 580 | 1.3866 | 0.7614 |
| 0.2212 | 30.0 | 600 | 1.4849 | 0.75 |
| 0.2266 | 31.0 | 620 | 1.4230 | 0.7727 |
| 0.2525 | 32.0 | 640 | 1.4288 | 0.7727 |
| 0.2241 | 33.0 | 660 | 1.4497 | 0.7614 |
| 0.1816 | 34.0 | 680 | 1.4347 | 0.7614 |
| 0.2529 | 35.0 | 700 | 1.4278 | 0.75 |
| 0.189 | 36.0 | 720 | 1.4290 | 0.75 |
| 0.2491 | 37.0 | 740 | 1.4449 | 0.7614 |
| 0.2562 | 38.0 | 760 | 1.4514 | 0.75 |
| 0.1872 | 39.0 | 780 | 1.4522 | 0.75 |
| 0.223 | 39.9351 | 798 | 1.4527 | 0.75 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0