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Jakir057
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finetuned-indian-food

Image Classification
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PyTorch
vit
Generated from Trainer
Inference Endpoints
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finetuned-indian-food / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: finetuned-indian-food
    results: []

finetuned-indian-food

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: 0.0027
  • Accuracy: 0.9996

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: 0.0002
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7056 0.1 100 0.5113 0.8881
0.3027 0.21 200 0.1280 0.9796
0.2823 0.31 300 0.1580 0.9656
0.3273 0.42 400 0.0879 0.9837
0.1808 0.52 500 0.0812 0.9822
0.2101 0.63 600 0.0339 0.9937
0.1495 0.73 700 0.0568 0.9833
0.1296 0.84 800 0.0629 0.9844
0.1462 0.94 900 0.0886 0.9733
0.0519 1.04 1000 0.0544 0.9870
0.3192 1.15 1100 0.0892 0.9726
0.158 1.25 1200 0.0632 0.98
0.0266 1.36 1300 0.0233 0.9944
0.1832 1.46 1400 0.0292 0.9930
0.1212 1.57 1500 0.0489 0.9852
0.0994 1.67 1600 0.0142 0.9974
0.0219 1.78 1700 0.0277 0.9930
0.0664 1.88 1800 0.0158 0.9974
0.0834 1.99 1900 0.0124 0.9978
0.1093 2.09 2000 0.0140 0.9974
0.1726 2.19 2100 0.0147 0.9963
0.0476 2.3 2200 0.0058 0.9993
0.0257 2.4 2300 0.0424 0.9911
0.0215 2.51 2400 0.0076 0.9989
0.0748 2.61 2500 0.0099 0.9974
0.0059 2.72 2600 0.0053 0.9993
0.0527 2.82 2700 0.0149 0.9963
0.0203 2.93 2800 0.0041 0.9993
0.0791 3.03 2900 0.0033 0.9989
0.0389 3.13 3000 0.0033 0.9989
0.0459 3.24 3100 0.0044 0.9989
0.0276 3.34 3200 0.0031 0.9996
0.0139 3.45 3300 0.0028 0.9996
0.0076 3.55 3400 0.0055 0.9985
0.0097 3.66 3500 0.0027 0.9996
0.0193 3.76 3600 0.0026 0.9996
0.0471 3.87 3700 0.0027 0.9996
0.0282 3.97 3800 0.0027 0.9996

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3