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Akhil123
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emotions_classifier

Image Classification
Transformers
TensorFlow
vit
generated_from_keras_callback
Inference Endpoints
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emotions_classifier / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_keras_callback
model-index:
  - name: Akhil123/emotions_classifier
    results: []

Akhil123/emotions_classifier

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:

  • Train Loss: 2.0827
  • Validation Loss: 2.0793
  • Train Accuracy: 0.1437
  • Epoch: 19

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 12800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Epoch
1.9720 1.6874 0.225 0
2.0874 2.0802 0.125 1
2.0744 2.0407 0.2313 2
2.0540 2.0760 0.1688 3
2.1039 2.0796 0.1125 4
2.0813 2.0794 0.1187 5
2.0802 2.0797 0.1187 6
2.0793 2.0790 0.125 7
2.0657 2.0128 0.2 8
2.0724 2.0920 0.125 9
2.0896 2.0744 0.1187 10
2.0844 2.0824 0.1187 11
2.0819 2.0755 0.125 12
2.0614 2.0392 0.1562 13
2.0676 2.0812 0.1187 14
2.0810 2.0792 0.1187 15
2.0826 2.0813 0.1187 16
2.0788 2.0770 0.15 17
2.0797 2.0733 0.125 18
2.0827 2.0793 0.1437 19

Framework versions

  • Transformers 4.31.0
  • TensorFlow 2.12.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3