results
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: 1.0865
- Accuracy: 0.4576
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 8 | 1.1023 | 0.2632 |
| 1.103 | 2.0 | 16 | 1.0984 | 0.2807 |
| 1.099 | 3.0 | 24 | 1.0956 | 0.2807 |
| 1.0996 | 4.0 | 32 | 1.0915 | 0.3684 |
| 1.0974 | 5.0 | 40 | 1.0904 | 0.4035 |
| 1.0974 | 6.0 | 48 | 1.0904 | 0.3684 |
| 1.0938 | 7.0 | 56 | 1.0894 | 0.3509 |
| 1.0891 | 8.0 | 64 | 1.0889 | 0.3509 |
| 1.0897 | 9.0 | 72 | 1.0877 | 0.4035 |
| 1.0911 | 10.0 | 80 | 1.0873 | 0.3684 |
Framework versions
- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1