Isaacks/segformer-finetuned-ihc

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segformer-finetuned-ihc

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

• —eval_loss: 0.0326
• —evalmeaniou: 0.0
• —evalmeanaccuracy: nan
• —evaloverallaccuracy: nan
• —evalaccuracybackground: nan
• —evalaccuracytissue: nan
• —evalioubackground: 0.0
• —evalioutissue: 0.0
• —eval_runtime: 19.1281
• —evalsamplesper_second: 0.784
• —evalstepsper_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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 1337
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: polynomial
• —training_steps: 10000

Framework versions

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