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hushem_1x_beit_base_sgd_0001_fold1

This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6388
  • Accuracy: 0.1111

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 6 1.6742 0.1111
1.4975 2.0 12 1.6721 0.1111
1.4975 3.0 18 1.6701 0.1111
1.4871 4.0 24 1.6683 0.1111
1.4949 5.0 30 1.6664 0.1111
1.4949 6.0 36 1.6646 0.1111
1.4943 7.0 42 1.6628 0.1111
1.4943 8.0 48 1.6613 0.1111
1.5225 9.0 54 1.6596 0.1111
1.4389 10.0 60 1.6582 0.1111
1.4389 11.0 66 1.6569 0.1111
1.4732 12.0 72 1.6557 0.1111
1.4732 13.0 78 1.6545 0.1111
1.4384 14.0 84 1.6534 0.1111
1.4676 15.0 90 1.6523 0.1111
1.4676 16.0 96 1.6513 0.1111
1.4696 17.0 102 1.6502 0.1111
1.4696 18.0 108 1.6492 0.1111
1.4688 19.0 114 1.6483 0.1111
1.4525 20.0 120 1.6474 0.1111
1.4525 21.0 126 1.6467 0.1111
1.4642 22.0 132 1.6459 0.1111
1.4642 23.0 138 1.6451 0.1111
1.4184 24.0 144 1.6445 0.1111
1.4687 25.0 150 1.6439 0.1111
1.4687 26.0 156 1.6433 0.1111
1.4512 27.0 162 1.6428 0.1111
1.4512 28.0 168 1.6422 0.1111
1.4747 29.0 174 1.6417 0.1111
1.4313 30.0 180 1.6412 0.1111
1.4313 31.0 186 1.6408 0.1111
1.4333 32.0 192 1.6405 0.1111
1.4333 33.0 198 1.6401 0.1111
1.4855 34.0 204 1.6398 0.1111
1.4466 35.0 210 1.6396 0.1111
1.4466 36.0 216 1.6394 0.1111
1.4336 37.0 222 1.6392 0.1111
1.4336 38.0 228 1.6390 0.1111
1.4754 39.0 234 1.6389 0.1111
1.4452 40.0 240 1.6388 0.1111
1.4452 41.0 246 1.6388 0.1111
1.4335 42.0 252 1.6388 0.1111
1.4335 43.0 258 1.6388 0.1111
1.4391 44.0 264 1.6388 0.1111
1.4625 45.0 270 1.6388 0.1111
1.4625 46.0 276 1.6388 0.1111
1.4619 47.0 282 1.6388 0.1111
1.4619 48.0 288 1.6388 0.1111
1.4316 49.0 294 1.6388 0.1111
1.4278 50.0 300 1.6388 0.1111

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Safetensors
Model size
85.8M params
Tensor type
F32
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Finetuned from

Evaluation results