vit-base-patch16-224_rice-leaf-disease-augmented-v4_tl

This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5193
  • Accuracy: 0.8087

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: 0.0003
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • 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: cosine_with_restarts
  • lr_scheduler_warmup_steps: 256
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Accuracy Validation Loss
2.1191 0.5 64 0.2047 2.0173
1.8193 1.0 128 0.4832 1.6229
1.44 1.5 192 0.6174 1.2769
1.1762 2.0 256 0.6980 1.0259
0.9676 2.5 320 0.6980 0.9041
0.8685 3.0 384 0.7383 0.7951
0.7844 3.5 448 0.7517 0.7532
0.733 4.0 512 0.7785 0.7018
0.7003 4.5 576 0.7651 0.6940
0.6781 5.0 640 0.7651 0.6819
0.6612 5.5 704 0.7550 0.6835
0.666 6.0 768 0.7718 0.6758
0.6791 6.5 832 0.7617 0.6722
0.6181 7.0 896 0.7752 0.6301
0.6064 7.5 960 0.7919 0.6013
0.5787 8.0 1024 0.7953 0.5856
0.5507 8.5 1088 0.7919 0.5859
0.5554 9.0 1152 0.7953 0.5857
0.536 9.5 1216 0.7987 0.5689
0.5298 10.0 1280 0.8020 0.5709
0.5244 10.5 1344 0.8054 0.5704
0.5301 11.0 1408 0.8054 0.5655
0.5172 11.5 1472 0.8020 0.5619
0.499 12.0 1536 0.8154 0.5307
0.4796 12.5 1600 0.8087 0.5256
0.477 13.0 1664 0.8087 0.5268
0.4648 13.5 1728 0.8054 0.5203
0.4564 14.0 1792 0.8087 0.5198
0.46 14.5 1856 0.5198 0.8121
0.4465 15.0 1920 0.5193 0.8087

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0
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