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: 0.6875
  • Accuracy: 0.8647

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: 20.0

Training results

Training Loss Epoch Step Accuracy Validation Loss
1.0864 1.0 130 0.4286 1.0878
1.0629 2.0 260 0.5489 1.0594
1.0434 3.0 390 0.6767 1.0230
1.0214 4.0 520 0.6767 0.9965
1.0026 5.0 650 0.7444 0.9569
0.9753 6.0 780 0.7820 0.9288
0.9252 7.0 910 0.7970 0.8875
0.9192 8.0 1040 0.8120 0.8506
0.9008 9.0 1170 0.8045 0.8338
0.8079 10.0 1300 0.8421 0.8104
0.8332 11.0 1430 0.8346 0.7806
0.8103 12.0 1560 0.8346 0.7586
0.8149 13.0 1690 0.8421 0.7571
0.8186 14.0 1820 0.8271 0.7540
0.7929 15.0 1950 0.8120 0.7412
0.774 16.0 2080 0.7370 0.8496
0.7613 17.0 2210 0.7059 0.8496
0.7778 18.0 2340 0.6930 0.8271
0.8081 19.0 2470 0.6890 0.8647
0.7916 20.0 2600 0.6875 0.8647

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.4.1+cu118
  • Datasets 2.21.0
  • Tokenizers 0.20.0