1_M_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned-v3
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1701
- Accuracy: 0.5118
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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3156 | 0.9995 | 1633 | 1.2976 | 0.4477 |
| 1.2943 | 1.9997 | 3267 | 1.2443 | 0.4668 |
| 1.2411 | 2.9998 | 4901 | 1.2229 | 0.4787 |
| 1.2368 | 4.0 | 6535 | 1.1967 | 0.4901 |
| 1.1973 | 4.9995 | 8168 | 1.1910 | 0.4927 |
| 1.2124 | 5.9997 | 9802 | 1.1811 | 0.4989 |
| 1.1753 | 6.9998 | 11436 | 1.1685 | 0.5062 |
| 1.1554 | 8.0 | 13070 | 1.1681 | 0.5080 |
| 1.1279 | 8.9995 | 14703 | 1.1685 | 0.5100 |
| 1.1121 | 9.9954 | 16330 | 1.1701 | 0.5118 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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