segformer-b0-finetuned-fish-almogm

This model is a fine-tuned version of nvidia/mit-b0 on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0068
• eval_mean_iou: 0.4831
• eval_mean_accuracy: 1.0000
• eval_overall_accuracy: 1.0000
• eval_accuracy_background: 1.0000
• eval_accuracy_fish: nan
• eval_iou_background: 0.9662
• eval_iou_fish: 0.0
• eval_runtime: 62.449
• eval_samples_per_second: 0.801
• eval_steps_per_second: 0.4
• epoch: 6.46
• step: 640

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: 6e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.0
• Tokenizers 0.13.2