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End of training
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metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya1_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8445945945945946

Boya1_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2

This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4945
  • Accuracy: 0.8446

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4285 1.0 923 0.4438 0.8349
0.3029 2.0 1846 0.4037 0.8522
0.1901 3.0 2769 0.4945 0.8446

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1
  • Datasets 2.12.0
  • Tokenizers 0.13.2