README.md

metadata

license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - image-classification
  - tensorflow
  - vision
  - generated_from_keras_callback
model-index:
  - name: dhanesh123in/vit-base-patch16-224-in21k-finetuned-image-classification
    results: []

dhanesh123in/vit-base-patch16-224-in21k-finetuned-image-classification

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

• Train Loss: 0.7983
• Train Accuracy: 0.9624
• Validation Loss: 0.4438
• Validation Accuracy: 0.9624
• Epoch: 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:

• optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': 1.0, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 5170, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.7983	0.9624	0.4438	0.9624	0

Framework versions

• Transformers 4.36.0.dev0
• TensorFlow 2.15.0
• Datasets 2.15.0
• Tokenizers 0.15.0