vit-base-railspace

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vit-base-beans-demo-v5

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0292
• Accuracy: 0.9926

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

          precision    recall  f1-score   support

       0       1.00      1.00      1.00     11315
       1       0.92      0.94      0.93       204
       2       0.95      0.97      0.96       714
       3       0.87      0.98      0.92       171

macro avg 0.93 0.97 0.95 12404 weighted avg 0.99 0.99 0.99 12404 accuracy 0.99 12404

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: 4
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2