SPIE_MULTICLASS_MICROSOFT_2_3
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: 0.2856
- Accuracy: 0.8967
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: 3
- 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 |
---|---|---|---|---|
1.6911 | 0.96 | 18 | 0.7916 | 0.7306 |
0.5972 | 1.9733 | 37 | 0.4421 | 0.8332 |
0.42 | 2.9867 | 56 | 0.3346 | 0.8801 |
0.34 | 4.0 | 75 | 0.2811 | 0.8993 |
0.2616 | 4.8 | 90 | 0.2856 | 0.8967 |
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