swin_larger
This model was trained from scratch on the zindi dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7009
- eval_accuracy: 0.7617
- eval_runtime: 222.198
- eval_samples_per_second: 17.43
- eval_steps_per_second: 0.549
- epoch: 1.0
- step: 173
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: 50
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
