Paper_Compared-swinv2-base
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7159
- Accuracy: 0.8533
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: 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 |
---|---|---|---|---|
1.6917 | 0.9492 | 14 | 0.7844 | 0.7562 |
0.7734 | 1.9661 | 29 | 0.4380 | 0.8521 |
0.1927 | 2.9831 | 44 | 0.4694 | 0.8544 |
0.0956 | 4.0 | 59 | 0.6487 | 0.8251 |
0.0638 | 4.9492 | 73 | 0.6688 | 0.8296 |
0.0343 | 5.9661 | 88 | 0.7615 | 0.8352 |
0.0182 | 6.9831 | 103 | 0.7470 | 0.8352 |
0.038 | 8.0 | 118 | 0.7666 | 0.8465 |
0.0057 | 8.9492 | 132 | 0.7086 | 0.8454 |
0.0062 | 9.4915 | 140 | 0.7159 | 0.8533 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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