results / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results
    results: []

results

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

  • Loss: 0.1114
  • Accuracy: 0.9687

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6639 0.1829 100 0.6155 0.6554
0.4191 0.3657 200 0.3088 0.8959
0.1698 0.5486 300 0.5321 0.7281
0.0749 0.7314 400 0.5087 0.7900
0.0484 0.9143 500 0.4649 0.8185
0.0323 1.0971 600 0.6888 0.762
0.0264 1.28 700 0.1395 0.9513
0.0224 1.4629 800 0.0661 0.9776
0.02 1.6457 900 0.1173 0.9581
0.0168 1.8286 1000 0.3498 0.889
0.013 2.0114 1100 0.1053 0.9655
0.0087 2.1943 1200 0.3601 0.8947
0.0081 2.3771 1300 0.1508 0.9535
0.0073 2.56 1400 0.2090 0.9390
0.0056 2.7429 1500 0.1136 0.9649
0.005 2.9257 1600 0.2656 0.9206
0.0036 3.1086 1700 0.1320 0.9595
0.002 3.2914 1800 0.1068 0.9686
0.0018 3.4743 1900 0.1091 0.9690
0.0019 3.6571 2000 0.1114 0.9687
0.0018 3.84 2100 0.0968 0.9719

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1