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image_classification

This model is a fine-tuned version of nateraw/vit-age-classifier on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8469
  • Accuracy: 0.3438

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: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 512
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.3
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.8 1 1.8452 0.3125
No log 1.6 2 1.8435 0.35
No log 2.4 3 1.8282 0.3688
No log 4.0 5 1.8112 0.3563
No log 4.8 6 1.8180 0.3312
No log 5.6 7 1.8291 0.3375
No log 6.4 8 1.8036 0.3563
1.6711 8.0 10 1.8134 0.3375

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Evaluation results