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-DAV5
results: []
swinv2-tiny-patch4-window8-256-dmae-humeda-DAV5
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: 1.1815
- Accuracy: 0.6346
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.0169 | 1.0 | 10 | 1.4927 | 0.3654 |
| 2.7431 | 2.0 | 20 | 1.2785 | 0.5577 |
| 2.1791 | 3.0 | 30 | 1.0628 | 0.5769 |
| 1.7293 | 4.0 | 40 | 1.0541 | 0.5577 |
| 1.3855 | 5.0 | 50 | 0.9817 | 0.6346 |
| 1.3507 | 6.0 | 60 | 0.9506 | 0.6154 |
| 1.186 | 7.0 | 70 | 0.9259 | 0.5962 |
| 1.1201 | 8.0 | 80 | 0.8867 | 0.6346 |
| 1.0185 | 9.0 | 90 | 0.9556 | 0.5769 |
| 0.981 | 10.0 | 100 | 0.9069 | 0.6923 |
| 0.8472 | 11.0 | 110 | 0.9413 | 0.6346 |
| 0.7333 | 12.0 | 120 | 0.9594 | 0.6346 |
| 0.7 | 13.0 | 130 | 0.9818 | 0.6538 |
| 0.7062 | 14.0 | 140 | 0.9588 | 0.6154 |
| 0.6666 | 15.0 | 150 | 1.1824 | 0.5769 |
| 0.6756 | 16.0 | 160 | 1.0542 | 0.6538 |
| 0.6148 | 17.0 | 170 | 1.0112 | 0.6346 |
| 0.6123 | 18.0 | 180 | 1.2390 | 0.5769 |
| 0.5931 | 19.0 | 190 | 1.0358 | 0.6923 |
| 0.5242 | 20.0 | 200 | 1.1471 | 0.6346 |
| 0.5499 | 21.0 | 210 | 1.0452 | 0.6731 |
| 0.4806 | 22.0 | 220 | 1.0887 | 0.6346 |
| 0.4294 | 23.0 | 230 | 1.1078 | 0.6346 |
| 0.5176 | 24.0 | 240 | 1.1218 | 0.5769 |
| 0.4051 | 25.0 | 250 | 1.1255 | 0.6731 |
| 0.4486 | 26.0 | 260 | 1.0775 | 0.6346 |
| 0.4262 | 27.0 | 270 | 1.0711 | 0.6731 |
| 0.4717 | 28.0 | 280 | 1.0975 | 0.6346 |
| 0.4067 | 29.0 | 290 | 1.0647 | 0.6731 |
| 0.3691 | 30.0 | 300 | 1.1139 | 0.6346 |
| 0.4446 | 31.0 | 310 | 1.1270 | 0.5962 |
| 0.3399 | 32.0 | 320 | 1.1498 | 0.6346 |
| 0.3449 | 33.0 | 330 | 1.1864 | 0.6346 |
| 0.4118 | 34.0 | 340 | 1.1989 | 0.5962 |
| 0.3945 | 35.0 | 350 | 1.1928 | 0.5962 |
| 0.3609 | 36.0 | 360 | 1.1815 | 0.6346 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0