SimpleCNN-mnist
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0726
- Accuracy: 0.9775
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: 0.001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- 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: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|
| 0.1168 | 0.469 | 469 | 0.0998 | 0.9709 |
| 0.0912 | 1.4690 | 938 | 0.0751 | 0.9756 |
| 0.0759 | 2.062 | 1000 | 0.0726 | 0.9775 |
Framework versions
- Transformers 5.6.1
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
