vit-fire-detection

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.1685
• eval_precision: 0.9495
• eval_recall: 0.9497
• eval_accuracy: 0.9497
• eval_f1score: 0.9494
• eval_runtime: 40.9327
• eval_samples_per_second: 18.469
• eval_steps_per_second: 0.586
• epoch: 5.0
• step: 950

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: 0.0002
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 10

Framework versions

• Transformers 4.36.0
• Pytorch 2.1.1+cpu
• Datasets 2.15.0
• Tokenizers 0.15.0