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metadata
license: other
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
base_model: nvidia/mit-b0
model-index:
  - name: histo_train_segformer
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - type: accuracy
            value: 0.875
            name: Accuracy

histo_train_segformer

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

  • Loss: 0.3830
  • Accuracy: 0.875

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: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2234 16.67 100 0.3830 0.875

Framework versions

  • Transformers 4.27.3
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2