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beitv2-base-beans

Image Classification
Transformers
Safetensors
timm
timm_wrapper
vision
Generated from Trainer
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beitv2-base-beans / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: timm/beitv2_base_patch16_224.in1k_ft_in22k
tags:
  - image-classification
  - vision
  - timm
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: beitv2-base-beans
    results: []

beitv2-base-beans

This model is a fine-tuned version of timm/beitv2_base_patch16_224.in1k_ft_in22k on the AI-Lab-Makerere/beans dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0003
  • Accuracy: 1.0

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 OptimizerNames.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: 50.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0435 1.0 130 0.1193 0.9624
0.1536 2.0 260 0.0023 1.0
0.183 3.0 390 0.0015 1.0
0.2256 4.0 520 0.0386 0.9850
0.0555 5.0 650 0.0340 0.9850
0.0713 6.0 780 0.0728 0.9925
0.0082 7.0 910 0.0411 0.9925
0.0085 8.0 1040 0.1002 0.9850
0.0733 9.0 1170 0.0004 1.0
0.0215 10.0 1300 0.0003 1.0
0.0501 11.0 1430 0.0634 0.9774
0.0338 12.0 1560 0.0248 0.9925
0.0045 13.0 1690 0.0939 0.9850
0.0013 14.0 1820 0.0373 0.9850
0.0002 15.0 1950 0.0515 0.9925
0.0074 16.0 2080 0.0017 1.0
0.0005 17.0 2210 0.0588 0.9925
0.0046 18.0 2340 0.0715 0.9850
0.0618 19.0 2470 0.0003 1.0
0.0007 20.0 2600 0.0697 0.9850
0.0001 21.0 2730 0.1105 0.9774
0.0214 22.0 2860 0.0930 0.9850
0.0004 23.0 2990 0.0272 0.9925
0.1619 24.0 3120 0.0024 1.0
0.0015 25.0 3250 0.0003 1.0
0.0148 26.0 3380 0.1312 0.9774
0.0482 27.0 3510 0.0873 0.9850
0.0001 28.0 3640 0.0721 0.9850
0.0954 29.0 3770 0.0143 0.9925
0.1373 30.0 3900 0.0449 0.9925
0.0076 31.0 4030 0.0435 0.9925
0.0028 32.0 4160 0.0101 0.9925
0.0001 33.0 4290 0.0414 0.9850
0.001 34.0 4420 0.0017 1.0
0.0055 35.0 4550 0.0733 0.9925
0.1471 36.0 4680 0.1221 0.9774
0.0484 37.0 4810 0.1473 0.9850
0.0014 38.0 4940 0.0748 0.9925
0.1825 39.0 5070 0.1072 0.9850
0.0 40.0 5200 0.0687 0.9925
0.0081 41.0 5330 0.1147 0.9850
0.0557 42.0 5460 0.0630 0.9850
0.0 43.0 5590 0.0162 0.9925
0.0 44.0 5720 0.0463 0.9925
0.0197 45.0 5850 0.0757 0.9850
0.1442 46.0 5980 0.0941 0.9850
0.0019 47.0 6110 0.0760 0.9850
0.0001 48.0 6240 0.0885 0.9850
0.0854 49.0 6370 0.0788 0.9850
0.0005 50.0 6500 0.0707 0.9850

Framework versions

  • Transformers 4.54.1
  • Pytorch 2.7.1+cu126
  • Datasets 4.0.0
  • Tokenizers 0.21.4