Prot10 / vit-base-patch16-224-for-pre_evaluation

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Total runs: 21
24-hour runs: 0
7-day runs: -3
30-day runs: 7
Model's Last Updated: September 09 2023
image-classification

Introduction of vit-base-patch16-224-for-pre_evaluation

Model Details of vit-base-patch16-224-for-pre_evaluation

vit-base-patch16-224-for-pre_evaluation

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

  • Loss: 1.6048
  • Accuracy: 0.3929
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: 30
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.5774 0.98 16 1.5109 0.3022
1.4794 1.97 32 1.4942 0.3242
1.4536 2.95 48 1.4943 0.3187
1.421 4.0 65 1.4247 0.3407
1.3882 4.98 81 1.4944 0.3462
1.3579 5.97 97 1.4180 0.3571
1.2838 6.95 113 1.4693 0.3681
1.2695 8.0 130 1.4359 0.3434
1.2016 8.98 146 1.4656 0.3599
1.2087 9.97 162 1.4550 0.3379
1.206 10.95 178 1.5056 0.3516
1.1236 12.0 195 1.5003 0.3434
1.0534 12.98 211 1.5193 0.3269
1.0024 13.97 227 1.4890 0.3681
0.9767 14.95 243 1.5628 0.3434
0.9201 16.0 260 1.6306 0.3516
0.9136 16.98 276 1.5715 0.3626
0.8566 17.97 292 1.5966 0.3654
0.8273 18.95 308 1.6048 0.3929
0.7825 20.0 325 1.6175 0.3846
0.736 20.98 341 1.6526 0.3929
0.7008 21.97 357 1.6563 0.3736
0.6714 22.95 373 1.7319 0.3901
0.7039 24.0 390 1.6866 0.3929
0.628 24.98 406 1.7023 0.3791
0.6182 25.97 422 1.7301 0.3901
0.5957 26.95 438 1.7157 0.3846
0.5973 28.0 455 1.7478 0.3709
0.5655 28.98 471 1.7377 0.3736
0.5631 29.54 480 1.7374 0.3736
Framework versions
  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3

Runs of Prot10 vit-base-patch16-224-for-pre_evaluation on huggingface.co

21
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0
24-hour runs
0
3-day runs
-3
7-day runs
7
30-day runs

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Updated:June 05 2023