README.md

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