convnext-base-384-finetuned-alzheimer-MRI
This model is a fine-tuned version of facebook/convnext-base-384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8576
- Accuracy: 0.5805
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: 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9877 | 1.0 | 36 | 0.9405 | 0.5625 |
| 0.8723 | 2.0 | 72 | 0.8801 | 0.5957 |
| 0.8327 | 3.0 | 108 | 0.8639 | 0.5977 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0