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segformer-finetuned-ihc

This model is a fine-tuned version of nvidia/mit-b0 on the Isaacks/ihc_slide_tissue dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.0326
  • eval_mean_iou: 0.0
  • eval_mean_accuracy: nan
  • eval_overall_accuracy: nan
  • eval_accuracy_background: nan
  • eval_accuracy_tissue: nan
  • eval_iou_background: 0.0
  • eval_iou_tissue: 0.0
  • eval_runtime: 19.1281
  • eval_samples_per_second: 0.784
  • eval_steps_per_second: 0.105
  • epoch: 9.15
  • step: 183

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: 8
  • eval_batch_size: 8
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: polynomial
  • training_steps: 10000

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.2
  • Tokenizers 0.13.3
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