SPIE_MULTICLASS_MICROSOFT_2_1
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2947
- Accuracy: 0.8914
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: 1
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.7569 | 0.96 | 18 | 0.9553 | 0.6733 |
0.6777 | 1.9733 | 37 | 0.4582 | 0.8308 |
0.4062 | 2.9867 | 56 | 0.3590 | 0.8690 |
0.288 | 4.0 | 75 | 0.2981 | 0.8936 |
0.2815 | 4.8 | 90 | 0.2947 | 0.8914 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
microsoft/swin-tiny-patch4-window7-224