vit-base-beans / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: timm/resnet18.a1_in1k
tags:
  - image-classification
  - vision
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: vit-base-beans
    results: []

vit-base-beans

This model is a fine-tuned version of timm/resnet18.a1_in1k on the beans dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8550
  • Accuracy: 0.7895

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1337
  • 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
  • num_epochs: 15.0

Training results

Training Loss Epoch Step Accuracy Validation Loss
1.0881 1.0 130 0.4135 1.0902
1.0716 2.0 260 0.5038 1.0685
1.061 3.0 390 0.6241 1.0459
1.0514 4.0 520 0.6015 1.0407
1.05 5.0 650 0.6767 1.0332
1.0357 6.0 780 1.0109 0.6541
1.0012 7.0 910 0.9815 0.7368
0.9932 8.0 1040 0.9550 0.7669
0.9748 9.0 1170 0.9409 0.7669
0.9113 10.0 1300 0.9149 0.7820
0.9255 11.0 1430 0.8906 0.7895
0.8877 12.0 1560 0.8749 0.7895
0.9032 13.0 1690 0.8699 0.7970
0.9001 14.0 1820 0.8674 0.7820
0.8842 15.0 1950 0.8550 0.7895

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu118
  • Datasets 2.21.0
  • Tokenizers 0.20.0