resnet-50-finetuned-cats_vs_dogs
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: 0.0889
- Accuracy: 0.9893
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 |
|---|---|---|---|---|
| 0.4648 | 1.0 | 128 | 0.3423 | 0.9781 |
| 0.2417 | 2.0 | 256 | 0.1214 | 0.9866 |
| 0.2032 | 2.99 | 384 | 0.0889 | 0.9893 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
microsoft/resnet-50