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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-9e-05
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6840345500139314

beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-9e-05

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the image_folder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8481
  • Accuracy: 0.6840

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: 9e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • 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
1.1839 1.0 224 1.0266 0.6120
1.0333 2.0 448 0.9063 0.6608
0.9655 3.0 672 0.8481 0.6840

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1