Conversion_at_month_2_Class_Weighted_Loss-swin-base-patch4-window7-224_class_weight
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4821
- Accuracy: 1.0
- Precision Macro: 1.0
- Recall Macro: 1.0
- F1 Macro: 1.0
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: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 2 | 0.7139 | 0.875 | 0.4375 | 0.5 | 0.4667 |
| No log | 2.0 | 4 | 1.1869 | 0.875 | 0.4375 | 0.5 | 0.4667 |
| No log | 3.0 | 6 | 1.9141 | 0.875 | 0.4375 | 0.5 | 0.4667 |
| No log | 4.0 | 8 | 3.7772 | 0.875 | 0.4375 | 0.5 | 0.4667 |
| 1.4632 | 5.0 | 10 | 3.9050 | 0.875 | 0.4375 | 0.5 | 0.4667 |
| 1.4632 | 6.0 | 12 | 6.2791 | 0.875 | 0.4375 | 0.5 | 0.4667 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2