resnet-50-finetuned-dog-vs-cat
This model is a fine-tuned version of microsoft/resnet-50 on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:
- Loss: 0.0577
- Accuracy: 0.9919
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3357 | 1.0 | 164 | 0.2255 | 0.9868 |
| 0.1683 | 2.0 | 329 | 0.0577 | 0.9919 |
| 0.1448 | 2.99 | 492 | 0.0460 | 0.9919 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2