swinv2_zindi

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12-192-22k on the zindi dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.6328
• eval_accuracy: 0.7434
• eval_runtime: 234.8425
• eval_samples_per_second: 16.492
• eval_steps_per_second: 0.519
• epoch: 3.0
• step: 520

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: 5

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0