Amanaccessassist's picture
End of training
8746290 verified
|
raw
history blame
2.63 kB
metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: finetuned-mango-types
    results: []

finetuned-mango-types

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5751
  • Accuracy: 0.9292

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.9926 1.0 22 1.9526 0.3833
1.7976 2.0 44 1.7500 0.6083
1.5678 3.0 66 1.5025 0.7583
1.3907 4.0 88 1.2804 0.9
1.0873 5.0 110 1.1005 0.9042
0.9511 6.0 132 1.0130 0.8875
0.8476 7.0 154 0.9424 0.8833
0.7511 8.0 176 0.8325 0.9042
0.6985 9.0 198 0.7894 0.9083
0.6515 10.0 220 0.8052 0.8792
0.5775 11.0 242 0.7600 0.8792
0.5458 12.0 264 0.6684 0.925
0.5331 13.0 286 0.7148 0.8917
0.4823 14.0 308 0.6849 0.9125
0.4579 15.0 330 0.6414 0.9167
0.4435 16.0 352 0.6557 0.8833
0.4411 17.0 374 0.5968 0.9083
0.453 18.0 396 0.5751 0.9292
0.445 19.0 418 0.6035 0.9083
0.4357 20.0 440 0.6010 0.9083

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2