swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2119
- Accuracy: 0.9122
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5888 | 1.0 | 41 | 0.4436 | 0.8348 |
0.3118 | 2.0 | 82 | 0.3028 | 0.8692 |
0.2284 | 3.0 | 123 | 0.2879 | 0.8795 |
0.203 | 4.0 | 164 | 0.2368 | 0.8950 |
0.2254 | 5.0 | 205 | 0.2276 | 0.8985 |
0.1976 | 6.0 | 246 | 0.2339 | 0.8967 |
0.1603 | 7.0 | 287 | 0.2191 | 0.9036 |
0.1556 | 8.0 | 328 | 0.2249 | 0.9036 |
0.1488 | 9.0 | 369 | 0.2018 | 0.9071 |
0.158 | 10.0 | 410 | 0.2119 | 0.9122 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
microsoft/swin-tiny-patch4-window7-224