README.md

metadata

license: apache-2.0
base_model: 02shanky/vit-finetuned-cifar10
tags:
  - generated_from_trainer
datasets:
  - cifar10
metrics:
  - accuracy
model-index:
  - name: vit-finetuned-vanilla-cifar10-0
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: cifar10
          type: cifar10
          config: plain_text
          split: train
          args: plain_text
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9911111111111112

vit-finetuned-vanilla-cifar10-0

This model is a fine-tuned version of 02shanky/vit-finetuned-cifar10 on the cifar10 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0336
• Accuracy: 0.9911

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.306	1.0	633	0.0478	0.986
0.2268	2.0	1266	0.0336	0.9911

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1