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flipped_results
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5433
- Accuracy: 0.4099
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: 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 |
|---|---|---|---|---|
| 1.3063 | 1.0 | 37 | 1.2485 | 0.4592 |
| 1.2272 | 2.0 | 74 | 1.1915 | 0.4626 |
| 1.1518 | 3.0 | 111 | 1.1770 | 0.4575 |
| 1.0504 | 4.0 | 148 | 1.1724 | 0.4745 |
| 0.9525 | 5.0 | 185 | 1.1966 | 0.4898 |
| 0.7485 | 6.0 | 222 | 1.2403 | 0.4626 |
| 0.5645 | 7.0 | 259 | 1.3973 | 0.4235 |
| 0.4645 | 8.0 | 296 | 1.4260 | 0.4898 |
| 0.374 | 9.0 | 333 | 1.5838 | 0.4405 |
| 0.2721 | 10.0 | 370 | 1.6747 | 0.4354 |
| 0.2679 | 11.0 | 407 | 1.7427 | 0.4507 |
| 0.2284 | 12.0 | 444 | 1.8097 | 0.4269 |
| 0.2003 | 13.0 | 481 | 1.9738 | 0.3997 |
| 0.1844 | 14.0 | 518 | 1.9745 | 0.4524 |
| 0.1631 | 15.0 | 555 | 2.0326 | 0.4456 |
| 0.1135 | 16.0 | 592 | 2.1294 | 0.4184 |
| 0.1188 | 17.0 | 629 | 2.1613 | 0.4065 |
| 0.1204 | 18.0 | 666 | 2.1795 | 0.4252 |
| 0.1083 | 19.0 | 703 | 2.2433 | 0.4167 |
| 0.0794 | 20.0 | 740 | 2.2762 | 0.4150 |
| 0.0589 | 21.0 | 777 | 2.3736 | 0.4065 |
| 0.0646 | 22.0 | 814 | 2.3644 | 0.4252 |
| 0.0744 | 23.0 | 851 | 2.4478 | 0.4099 |
| 0.0728 | 24.0 | 888 | 2.4367 | 0.4099 |
| 0.0382 | 25.0 | 925 | 2.5123 | 0.3997 |
| 0.033 | 26.0 | 962 | 2.5202 | 0.4031 |
| 0.0326 | 27.0 | 999 | 2.5145 | 0.4099 |
| 0.023 | 28.0 | 1036 | 2.5309 | 0.4099 |
| 0.0377 | 29.0 | 1073 | 2.5409 | 0.4099 |
| 0.0243 | 30.0 | 1110 | 2.5433 | 0.4099 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
