lixiqi's picture
update model card README.md
55b830c
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-5e-05
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6833379771524102

beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-5e-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: 0.8610
  • Accuracy: 0.6833

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: 5e-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
1.1691 1.0 224 0.9764 0.6310
1.0304 2.0 448 0.8965 0.6666
0.9844 3.0 672 0.8610 0.6833

Framework versions

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