swinv2-tiny-patch4-window8-256-RD-da-colab
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 10.2420
- Accuracy: 0.5036
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1347 | 1.0 | 96 | 10.0386 | 0.4982 |
| 0.1556 | 2.0 | 192 | 9.5018 | 0.5 |
| 0.1051 | 3.0 | 288 | 9.9516 | 0.4982 |
| 0.1154 | 4.0 | 384 | 10.8351 | 0.4945 |
| 0.0909 | 5.0 | 480 | 11.6091 | 0.4945 |
| 0.0923 | 6.0 | 576 | 9.0530 | 0.5 |
| 0.1089 | 7.0 | 672 | 11.6765 | 0.4927 |
| 0.0959 | 8.0 | 768 | 11.5132 | 0.4982 |
| 0.1266 | 9.0 | 864 | 10.2420 | 0.5036 |
| 0.106 | 10.0 | 960 | 11.1262 | 0.4945 |
| 0.0831 | 11.0 | 1056 | 11.5815 | 0.4964 |
| 0.0819 | 12.0 | 1152 | 11.6394 | 0.4964 |
| 0.0862 | 13.0 | 1248 | 10.9660 | 0.4982 |
| 0.0754 | 14.0 | 1344 | 9.5463 | 0.4982 |
| 0.06 | 15.0 | 1440 | 10.2678 | 0.4964 |
| 0.0828 | 16.0 | 1536 | 11.4973 | 0.4927 |
| 0.0675 | 17.0 | 1632 | 10.5019 | 0.4964 |
| 0.0687 | 18.0 | 1728 | 10.6483 | 0.4982 |
| 0.0548 | 19.0 | 1824 | 11.2166 | 0.4964 |
| 0.0658 | 20.0 | 1920 | 11.5459 | 0.4945 |
| 0.0565 | 21.0 | 2016 | 11.5899 | 0.4945 |
| 0.0807 | 22.0 | 2112 | 10.7066 | 0.5 |
| 0.0289 | 23.0 | 2208 | 10.6253 | 0.4982 |
| 0.0755 | 24.0 | 2304 | 10.4856 | 0.5018 |
| 0.0483 | 25.0 | 2400 | 11.3838 | 0.4964 |
| 0.0732 | 26.0 | 2496 | 11.1971 | 0.4927 |
| 0.1424 | 27.0 | 2592 | 11.4581 | 0.4945 |
| 0.0814 | 28.0 | 2688 | 11.3341 | 0.4945 |
| 0.101 | 29.0 | 2784 | 11.5705 | 0.4927 |
| 0.0894 | 30.0 | 2880 | 11.5259 | 0.4927 |
| 0.0707 | 31.0 | 2976 | 11.1753 | 0.4945 |
| 0.1289 | 32.0 | 3072 | 10.5668 | 0.4964 |
| 0.0991 | 33.0 | 3168 | 11.1013 | 0.4945 |
| 0.0615 | 34.0 | 3264 | 11.0973 | 0.4945 |
| 0.0784 | 35.0 | 3360 | 11.0716 | 0.4945 |
| 0.0792 | 36.0 | 3456 | 11.0241 | 0.4945 |
| 0.1032 | 37.0 | 3552 | 11.2338 | 0.4945 |
| 0.0837 | 38.0 | 3648 | 11.4256 | 0.4927 |
| 0.0722 | 39.0 | 3744 | 11.3971 | 0.4945 |
| 0.079 | 40.0 | 3840 | 11.3523 | 0.4945 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3