README.md

metadata

license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - image-classification
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: fine-tuned
    results: []

fine-tuned

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

• Loss: 7.3529
• Accuracy: 0.0596
• F1: 0.0075

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3773	2.54	1000	7.3529	0.0596	0.0075

Framework versions

• Transformers 4.33.3
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3