cat_dog_classifier
This model is a fine-tuned version of microsoft/resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0884
- Accuracy: 0.9688
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 293 | 0.1872 | 0.9440 |
| 0.3326 | 2.0 | 586 | 0.1120 | 0.9590 |
| 0.3326 | 3.0 | 879 | 0.0877 | 0.9677 |
| 0.1182 | 4.0 | 1172 | 0.0940 | 0.9641 |
| 0.1182 | 5.0 | 1465 | 0.0884 | 0.9688 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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Base model
microsoft/resnet-50