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metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - image-classification
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: finetuned-for-YogaPosesv6
    results: []

finetuned-for-YogaPosesv6

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the yoga_pose_images dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0562
  • Accuracy: 0.9938

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.9954 0.8772 100 0.8301 0.8505
0.3505 1.7544 200 0.1881 0.9907
0.1524 2.6316 300 0.0901 0.9844
0.152 3.5088 400 0.1241 0.9688
0.1314 4.3860 500 0.0562 0.9938
0.1187 5.2632 600 0.1232 0.9720
0.0936 6.1404 700 0.0893 0.9688
0.0753 7.0175 800 0.1510 0.9626
0.0155 7.8947 900 0.0536 0.9907
0.0181 8.7719 1000 0.0515 0.9907
0.0037 9.6491 1100 0.0570 0.9907
0.0121 10.5263 1200 0.0570 0.9907
0.0065 11.4035 1300 0.0565 0.9907

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3